From 334c9ab5f8ab1d585e0395e9e341c147d72d9a00 Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?Tobias=20=20Vl=C4=87ek?= Date: Wed, 13 Nov 2024 16:11:12 +0100 Subject: [PATCH] Built site for gh-pages --- .nojekyll | 2 +- general/cheatsheet 2.html | 1237 ++++++++++++++ general/cheatsheet 2.pdf | Bin 0 -> 39674 bytes general/cheatsheet.html | 79 +- general/cheatsheet.pdf | Bin 39682 -> 39676 bytes general/faq 2.html | 725 ++++++++ general/faq.html | 35 + general/faq.pdf | Bin 17124 -> 17129 bytes general/literature.html | 35 + general/literature.pdf | Bin 20910 -> 20916 bytes general/syllabus.html | 35 + general/syllabus.pdf | Bin 15043 -> 15041 bytes index.html | 35 + index.pdf | Bin 22896 -> 22896 bytes part-01/lecture-optimal-stopping 3.pdf | Bin 0 -> 1123957 bytes part-01/lecture-optimal-stopping.html | 35 + part-01/lecture-optimal-stopping.pdf | Bin 1123958 -> 1123959 bytes part-01/lecture-presentation 3.html | 1555 +++++++++++++++++ part-01/tutorial-01-variables 3.html | 1051 ++++++++++++ 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2.pdf create mode 100644 part-02/tutorial-06-explore-exploit 3.ipynb create mode 100644 part-03/lecture-caching 2.html create mode 100644 part-03/tutorial-07-recap 2.html create mode 100644 part-03/tutorial-08-functions 2.html diff --git a/.nojekyll b/.nojekyll index 0a1009a..e49c3eb 100644 --- a/.nojekyll +++ b/.nojekyll @@ -1 +1 @@ -a37363c4 \ No newline at end of file +92040e7a \ No newline at end of file diff --git a/general/cheatsheet 2.html b/general/cheatsheet 2.html new file mode 100644 index 0000000..cdd47c2 --- /dev/null +++ b/general/cheatsheet 2.html @@ -0,0 +1,1237 @@ + + + + + + + + + +Cheatsheet – Programming: Everyday Decision-Making Algorithms + + + + + + + + + + + + + + + + + + + + + + + + + + +
+
+ +
+ +
+ + +
+ + + +
+ +
+
+

Cheatsheet

+

Useful commands and tips

+
+ + + +
+ + + + +
+ + + +
+ + +
+

Variables and Types

+
+

Variables

+
    +
  • Definition: Containers for storing information.
    • +
  • Example: x = 10
    • +
+
+
+

Data Types

+
    +
  • Integers (int): Whole numbers (e.g., count of dates).
    • +
  • Floats (float): Decimal numbers (e.g., compatibility score).
    • +
  • Booleans (bool): True/False values (e.g., availability).
    • +
  • Strings (str): Text values (e.g., names).
    • +
+
  name = "Alexander"  # String variable
+  flags = 0           # Integer variable
+  butterflies = True  # Boolean variable
+
+
+

Type Conversion

+
    +
  • Checking: Use type() to check the type of a variable.
    • +
  • Conversion: +
      +
    • int(): Converts to integer.
      • +
    • float(): Converts to float.
      • +
    • str(): Converts to string.
      • +
    • bool(): Converts to boolean.
      • +
    • +
+
+
+

String Formatting

+
    +
  • Concatenation: Combine strings using +.
    • +
  • Formatting: Use f"..." for formatted strings.
    • +
+
+
name = "Alexander"
+print(f"Hello, {name}!")
+
+
Hello, Alexander!
+
+
+
+
+
+

Comparisons

+
+

Comparison Operators

+ +++++ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
SymbolMeaningExample
==Equal toscore == 100
!=Not equal todegree != “Computer Science”
<Less thansalary < 80000
>Greater thanexperience > 5
<=Less than or equal toage <= 65
>=Greater than or equal totest_score >= 80
+
+
+

Logical Operators

+ +++++ + + + + + + + + + + + + + + + + + + + + + + + + +
SymbolMeaningExample
andBoth conditions must be truescore > 80 and experience > 5
orAt least one condition must be truescore > 80 or experience > 5
notCondition must be falsenot (score > 80)
+
+
+
+

Decision-Making

+
+

if Statements

+
    +
  • Structure:
    • +
+
if condition:
+    # code to execute if condition is True
+
    +
  • Example:
    • +
+
+
flat_rating = 8
+if flat_rating >= 7:
+    print("This is a good apartment!")
+
+
This is a good apartment!
+
+
+
+
+

if-else Statements

+
    +
  • Structure:
    • +
+
if condition:
+    # code to execute if condition is True
+else:
+    # code to execute if condition is False
+
    +
  • Example:
    • +
+
+
flat_rating = 4
+if flat_rating >= 7:
+    print("Apply for this flat!")
+else:
+    print("Keep searching!")
+
+
Keep searching!
+
+
+
+
+

if-elif-else Statements

+
    +
  • Structure:
    • +
+
if condition:
+    # code to execute if condition is True
+elif condition:
+    # code to execute if condition is False
+else:
+    # code to execute if condition is False
+
    +
  • Example:
    • +
+
+
flat_rating = 8
+if flat_rating >= 9:
+    print("Amazing flat - apply immediately!")
+elif flat_rating >= 7:
+    print("Good flat - consider applying")
+else:
+    print("Keep looking")
+
+
Good flat - consider applying
+
+
+
+
+

Complex Conditions

+
    +
  • Nested if Statements: Use if statements inside other if statements.
    • +
  • Logical Operators: Combine conditions using and, or, not.
    • +
  • Structure:
    • +
+
if (condition1) and (condition2):
+    # code if both conditions are True
+elif (condition1) or (condition2):
+    # code if at least one condition is True
+else:
+    # code if none of the conditions are True
+
    +
  • Example:
    • +
+
+
flat_rating = 9
+price = 900
+if (flat_rating >= 9) and (price < 1000):
+    print("Amazing flat - apply immediately!")
+
+
Amazing flat - apply immediately!
+
+
+
+
+
+

Lists and Tuples

+
+
+

Lists

+
    +
  • Definition: Ordered, mutable collections of items.
    • +
  • Creation: Use square brackets [].
    • +
+
+
ratings = [4.5, 3.8, 4.2]
+restaurants = ["Magic Place", "Sushi Bar", "Coffee Shop"]
+
+
+

Accessing Elements

+
    +
  • Indexing: Use [index] to access elements.
    • +
+
+
print(restaurants[0])  # Access the first element
+
+
Magic Place
+
+
+
    +
  • Negative Indexing: Use [-1] to access the last element.
    • +
+
+
print(restaurants[-1])  # Access the last element
+
+
Coffee Shop
+
+
+
    +
  • Slicing: Use [start:end] to access a range of elements.
    • +
+
+
print(restaurants[0:2])  # Access the first two elements
+
+
['Magic Place', 'Sushi Bar']
+
+
+
+
+

Adding Elements

+
    +
  • Appending: Use append() to add an element to the end of the list.
    • +
+
+
restaurants.append("Pasta Place")
+
+
    +
  • Inserting: Use insert() to add an element at a specific index.
    • +
+
+
restaurants.insert(0, "Pasta Magic")
+
+
+
+

Removing Elements

+
    +
  • Removing: Use remove() to remove an element by value.
    • +
+
+
restaurants.remove("Pasta Place")
+
+
    +
  • Removing by Index: Use pop() to remove an element by index.
    • +
+
+
restaurants.pop(0)
+
+
'Pasta Magic'
+
+
+
+
+

Nested Lists

+
    +
  • Definition: Lists containing other lists or tuples.
    • +
  • Accessing: Use nested indexing.
    • +
+
+
restaurant_data = [
+    ["Pasta Place", 4.5, 3],
+    ["Sushi Bar", 4.2, 1]
+]
+print(restaurants[0][1])  # Access the second element of the first list
+
+
a
+
+
+
+
+

Tuples

+
    +
  • Definition: Ordered, immutable collections of items.
    • +
  • Creation: Use parentheses ().
    • +
  • Immutability: Once created, cannot be changed.
    • +
  • Memory Efficiency: Use less memory than lists.
    • +
  • Use Cases: Ideal for fixed data (e.g., restaurant location).
    • +
+
+
ratings = (4.5, 3.8, 4.2)
+restaurant_info = ("Pasta Place", "Italian", 2020)
+
+
+
+
+

Loops

+
+

for Loops

+
    +
  • Definition: Iterate over a sequence of items.
    • +
  • Structure:
    • +
+
for item in sequence:
+    # code to execute for each item
+
    +
  • Example:
    • +
+
+
treatments = ["Standard Drug", "New Drug A", "New Drug B"]
+for treatment in treatments:
+    print(f"Evaluating efficacy of {treatment}")
+
+
Evaluating efficacy of Standard Drug
+Evaluating efficacy of New Drug A
+Evaluating efficacy of New Drug B
+
+
+
+
+

Range in for Loops

+
    +
  • Definition: Generate a sequence of numbers.
    • +
  • Structure:
    • +
+
range(start, stop, step)
+
    +
  • Example:
    • +
+
+
for phase in range(5):  # 0 to 4
+    print(f"Starting Phase {phase + 1}")
+
+
Starting Phase 1
+Starting Phase 2
+Starting Phase 3
+Starting Phase 4
+Starting Phase 5
+
+
+
+
for phase in range(1, 5):  # 1 to 4
+    print(f"Starting Phase {phase}")
+
+
Starting Phase 1
+Starting Phase 2
+Starting Phase 3
+Starting Phase 4
+
+
+
+
for phase in range(1, 5, 2):  # 1 to 4, step 2
+    print(f"Starting Phase {phase}")
+
+
Starting Phase 1
+Starting Phase 3
+
+
+
+
+

break and continue

+
    +
  • break: Exit the loop.
    • +
  • continue: Skip the current iteration and continue with the next.
    • +
+
+
efficacy_scores = [45, 60, 75, 85, 90]
+for score in efficacy_scores:
+    if score < 50:
+        continue
+        print(f"Treatment efficacy: {score}%")
+    if score >= 85:
+        break
+
+
+
+

Tuple unpacking

+
    +
  • Definition: Assign elements of a tuple to variables.
    • +
  • Structure:
    • +
  • Example:
    • +
+
+
restaurant_info = ("Pasta Place", "Italian", 2020)
+name, cuisine, year = restaurant_info
+print(name)
+print(cuisine)
+print(year)
+
+
Pasta Place
+Italian
+2020
+
+
+
+
+

while Loops

+
    +
  • Definition: Execute code repeatedly as long as a condition is true.
    • +
  • Structure:
    • +
+
while condition:
+    # code to execute while condition is True
+
    +
  • Example:
    • +
+
+
phase = 1
+while phase <= 5:
+    print(f"Starting Phase {phase}")
+    phase += 1
+
+
Starting Phase 1
+Starting Phase 2
+Starting Phase 3
+Starting Phase 4
+Starting Phase 5
+
+
+ + +
+
+ +
+ +
+ + + + + + \ No newline at end of file diff --git a/general/cheatsheet 2.pdf b/general/cheatsheet 2.pdf new file mode 100644 index 0000000000000000000000000000000000000000..0c877fbc3bcb9ef53ee0fe548b29daa93bd1b18c GIT binary patch literal 39674 zcma&NV{j*Z*EJg3wr$(C&53Q>wkF9x_QbX(wr$(?awRbddS(W881lp0t5+BfA|@gSV`~^bK1K;ETURq@MhROZS2Hm)69-c>MmaNk z3s*}bW)5xv0T>roXEP%^7|-=M#d?^2A-Jut=ue>;GWly9Dts{X&CrcOVHzIp*Y6l< z-GW^bj|2}dX#?k52#`lnrB%lM*Zb2`&p%V0FdLx2X@kWePr#-bYOri{$sG)$-G<&` z43R86lLe9M+{=J44!sL2j$+daym0vR)D1XzZI&wua!2P8Awze3B#&Gw&g zyR~H<4msd@UNm13V`-ua350e0IJ^wk;QFbyt|wu?!?_|U4C8?N7kj8m9?dIQ%LfWiuKCysHYA^F zF3-9+WAO@p2FQc2JXNM`3h?NsNPo&z5JwFjmUfD*uV#Y~4`E=U8EtkDvhMK`1{CV; zkrk>zvs=IRLtu}MNO?jELZPp8p~TFt$VW@94P`7de|qB8Y4Xs$bXw;HUrx(9V#cNL z;pO_RT4$Dso#ZwXW8)GM15_CSu)jQ2vwZMxJVa+K9iRZ_MjIr`uoBQ6U_pEr_afyX zVrmR5s3K=>fwAK3#2f|!N!?yJx51`XyHJz;HK3R=*`^fxIw}k9SKq62cnPuV3 zJe1bdc^(v!!g~)eMNY94^IIf-DjvAJ(Mhl>avzZ)@~idI?M&2DL)Ruhj 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b/general/cheatsheet.html index 7260e3d..47d9e1c 100644 --- a/general/cheatsheet.html +++ b/general/cheatsheet.html @@ -220,6 +220,41 @@ 06 - Exploration + + + +
  • +
    + + +
    +
    • @@ -356,7 +391,7 @@

    String Formatting

  • Concatenation: Combine strings using +.
  • Formatting: Use f"..." for formatted strings.
    • -
    +
    name = "Alexander"
 print(f"Hello, {name}!")
    @@ -463,7 +498,7 @@

    if Statements

    • Example:
    -
    +
    flat_rating = 8
 if flat_rating >= 7:
     print("This is a good apartment!")
    @@ -484,7 +519,7 @@

    if-else Statements

    • Example:
    -
    +
    flat_rating = 4
 if flat_rating >= 7:
     print("Apply for this flat!")
@@ -509,7 +544,7 @@ 
    if-elif-else State
 
      
 
    • Example:
      • 
 
    
-
    
+
    
 
    flat_rating = 8
 if flat_rating >= 9:
     print("Amazing flat - apply immediately!")
@@ -538,7 +573,7 @@ 
    Complex Conditions
    
 
      
 
    • Example:
      • 
 
    
-
    
+
    
 
    flat_rating = 9
 price = 900
 if (flat_rating >= 9) and (price < 1000):
@@ -558,7 +593,7 @@ 
    Lists
    
 
  • Definition: Ordered, mutable collections of items.
    • 
 
  • Creation: Use square brackets [].
    • 
 
-
    
+
    
 
    ratings = [4.5, 3.8, 4.2]
 restaurants = ["Magic Place", "Sushi Bar", "Coffee Shop"]
    
 
    
@@ -567,7 +602,7 @@ 
    Accessing Elements
    
 
      
 
    • Indexing: Use [index] to access elements.
      • 
 
    
-
    
+
    
 
    print(restaurants[0])  # Access the first element
    
 
    
 
    Magic Place
    
@@ -576,7 +611,7 @@ 
    Accessing Elements
    
 
      
 
    • Negative Indexing: Use [-1] to access the last element.
      • 
 
    
-
    
+
    
 
    print(restaurants[-1])  # Access the last element
    
 
    
 
    Coffee Shop
    
@@ -585,7 +620,7 @@ 
    Accessing Elements
    
 
      
 
    • Slicing: Use [start:end] to access a range of elements.
      • 
 
    
-
    
+
    
 
    print(restaurants[0:2])  # Access the first two elements
    
 
    
 
    ['Magic Place', 'Sushi Bar']
    
@@ -597,13 +632,13 @@ 
    Adding Elements
    
 
      
 
    • Appending: Use append() to add an element to the end of the list.
      • 
 
    
-
    
+
    
 
    restaurants.append("Pasta Place")
    
 
    
 
      
 
    • Inserting: Use insert() to add an element at a specific index.
      • 
 
    
-
    
+
    
 
    restaurants.insert(0, "Pasta Magic")
    
 
    
 
@@ -612,13 +647,13 @@ 
    Removing Elements
    
 
      
 
    • Removing: Use remove() to remove an element by value.
      • 
 
    
-
    
+
    
 
    restaurants.remove("Pasta Place")
    
 
    
 
      
 
    • Removing by Index: Use pop() to remove an element by index.
      • 
 
    
-
    
+
    
 
    restaurants.pop(0)
    
 
    
 
    'Pasta Magic'
    
@@ -631,7 +666,7 @@ 
    Nested Lists
    
 
  • Definition: Lists containing other lists or tuples.
    • 
 
  • Accessing: Use nested indexing.
    • 
 
-
    
+
    
 
    restaurant_data = [
     ["Pasta Place", 4.5, 3],
     ["Sushi Bar", 4.2, 1]
@@ -651,7 +686,7 @@ 
    Tuples
    
 
  • Memory Efficiency: Use less memory than lists.
    • 
 
  • Use Cases: Ideal for fixed data (e.g., restaurant location).
    • 
 
-
    
+
    
 
    ratings = (4.5, 3.8, 4.2)
 restaurant_info = ("Pasta Place", "Italian", 2020)
    
 
    
@@ -670,7 +705,7 @@ 
    for Loops
    
 
      
 
    • Example:
      • 
 
    
-
    
+
    
 
    treatments = ["Standard Drug", "New Drug A", "New Drug B"]
 for treatment in treatments:
     print(f"Evaluating efficacy of {treatment}")
    
@@ -691,7 +726,7 @@ 
    Range in for Loops
    
 
      
 
    • Example:
      • 
 
    
-
    
+
    
 
    for phase in range(5):  # 0 to 4
     print(f"Starting Phase {phase + 1}")
    
 
    
@@ -702,7 +737,7 @@ 
    Range in for Loops
    
 Starting Phase 5
    
 
    
 
    
-
    
+
    
 
    for phase in range(1, 5):  # 1 to 4
     print(f"Starting Phase {phase}")
    
 
    
@@ -712,7 +747,7 @@ 
    Range in for Loops
    
 Starting Phase 4
    
 
    
 
    
-
    
+
    
 
    for phase in range(1, 5, 2):  # 1 to 4, step 2
     print(f"Starting Phase {phase}")
    
 
    
@@ -727,7 +762,7 @@ 
    break and continue
    
 
  • break: Exit the loop.
    • 
 
  • continue: Skip the current iteration and continue with the next.
    • 
 
-
    
+
    
 
    efficacy_scores = [45, 60, 75, 85, 90]
 for score in efficacy_scores:
     if score < 50:
@@ -744,7 +779,7 @@ 
    Tuple unpacking
    
 
  • Structure:
    • 
 
  • Example:
    • 
 
-
    
+
    
 
    restaurant_info = ("Pasta Place", "Italian", 2020)
 name, cuisine, year = restaurant_info
 print(name)
@@ -768,7 +803,7 @@ 
    while Loops
    
 
      
 
    • Example:
      • 
 
    
-
    
+
    
 
    phase = 1
 while phase <= 5:
     print(f"Starting Phase {phase}")
diff --git a/general/cheatsheet.pdf b/general/cheatsheet.pdf
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+Frequently Asked Questions – Programming: Everyday Decision-Making Algorithms
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    Frequently Asked Questions
    
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    Answers to common questions
    
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    Unanswered Questions
    
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    If you have a question that is not answered here, please let me know by sending me an e-mail to vlcek@beyondsimulations.com or by creating an issue on GitHub.
    
+
    
+
    
+
    Contribution and Mistakes
    
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    If you have found a mistake in the course material or if you have any suggestion on how to improve the course, please let us know in the following form or by creating an issue on GitHub.
    
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    FAQs
    
+
    
+
    How can I download PDF slides from the lecture?
    
+
      
+
    1. First, open the lecture you want to download the slides from.
      2. 
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    2. Then, click on the RevealJS button in the top right corner.
      3. 
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    3. Now, click on the three stacked bars in the lower left corner.
      4. 
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    4. Then, click on Tools in the upper left corner.
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    5. Now you can select PDF Export Mode and then save the slides as a PDF.
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  06 - Exploration
   
    
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diff --git a/general/faq.pdf b/general/faq.pdf
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diff --git a/general/literature.html b/general/literature.html
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--- a/general/literature.html
+++ b/general/literature.html
@@ -186,6 +186,41 @@
   
  06 - Exploration
   
    
+
+      
+  
+        
  • 
+      
     
+            
+           
+      
    
+      
   
    • 
diff --git a/general/literature.pdf b/general/literature.pdf
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diff --git a/part-01/lecture-optimal-stopping.pdf b/part-01/lecture-optimal-stopping.pdf
index 73fe8b6f8eda84416041353dedebae15efbfcd45..3870c1042c11bf6d060ab9ba4de8d93850a25b74 100644
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zimR%7Q{=UDpN0R2-(Ow^BwNUDH{I{VpF
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+  
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+  
+  Programming: Everyday Decision-Making Algorithms – Lecture I - Optimal Stopping
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+  
    Lecture I - Optimal Stopping
    
+  
    Programming: Everyday Decision-Making Algorithms
    
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+
    
+
    
+
    
+Dr. Tobias Vlćek 
+
    
+        
    
+            Kühne Logistics University Hamburg - Winter 2024
+          
    
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+
    
+
    About this Course
    
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    Teaching Team
    
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    Dr. Tobias Vlcek
    
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    Dr. Nils Roemer
    
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    About me
    
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+
      
+
    • Field: Optimizing and simulating complex systems
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    • Languages: of choice: Julia, Python and Rust
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    • Interest: Modelling, Simulations, Machine Learning
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    • Teaching: OR, Algorithms, and Programming
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    • Contact: vlcek@beyondsimulations.com
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    Tip
    
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    We really appreciate active participation and interaction!
    
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    Course Outline
    
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    • I: Optimal Stopping
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    • II: Explore & Exploit
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    • III: Caching
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    • IV: Scheduling
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    • V: Randomness
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    • VI: Computational Kindness
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    Participation
    
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    Teaching
    
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    • Lecture: Presentation and discussion of algorithms related to everyday decision-making
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    • Tutorial: Step-by-step assignments to be solved and discussed together in groups
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    • Difficulty: Strongly depends on your background and programming experience
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    Tip
    
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    No worries, we will help you out if you have any questions!
    
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    Passing the Course
    
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    • Pass/fail course without exams
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    • 75% attendance required for passing the course
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    • Hand in the assignments of at least two lectures
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    • Short presentation and discussion at the end
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    • You work together in groups of three students
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    Handing in Assignments
    
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    • Each student group submits one solution
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    • Provide us all working notebooks of the lecture
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    • Hand in is due at the beginning of the next lecture
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    • At least 50 % have to be correct to pass
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    • You have to pass at least twice
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    Tip
    
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+
    This is just in order to provide you with working solutions after each deadline.
    
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    Learning Python
    
+
    We will mostly not cover Python during the lectures!
    
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+
    Question: Anybody know why?
    
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+
    
+
      
+
    • In our experience, the best way to learn is by doing!
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    • Here, we will focus on decision-making algorithms
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    • You will learn Python by doing the tutorials
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    Tip
    
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    Don’t worry, we will help you out if you have any questions!
    
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    Difficulty of the Course
    
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    • At first it might be a little bit overwhelming
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    • Programming is similar to learning a new language
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    • First, you have to get used to it and learn words
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    • Later, you’ll be able to apply it and see results
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    • Important: Practice, practice, practice!
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    Goals of the Course
    
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    • Learn the basics of programming
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    • Learn about algorithmic thinking
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    • Be able to apply methods and concepts
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    • Solve practical problems with algorithms
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    Tip
    
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    We are convinced that this course will be quite interesting and teach you more for your daily life than most other courses!
    
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    Why Python?
    
+
      
+
    • Origins: Conceived in late 1980s as a teaching and scripting language
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    • Simple Syntax: Python’s syntax is mostly straightforward and very easy to learn
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    • Versatility: Used in web development, data analysis, artificial intelligence, and more
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    • Community Support: A large community of users worldwide and extensive documentation
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    Help from AI
    
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    • You are allowed to use AI in the course, we use it as well (e.g., Claude, ChatGPT, LLama3 …)
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    • These tools are great for learning Python!
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    • Can help you a lot to get started with programming
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    Warning
    
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    But you should not simply use them to replace your learning.
    
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    How to learn programming
    
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    Our Recommendation
    
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    1. Be present: Attend the lecture and solve the tutorials
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    2. Put in some work: Repeat code and try to understand it
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    3. Do coding: Run code, play around, modify, and solve
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    Tip
    
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    Great resources to start are books and small challenges. You can find a list of book recommendations at the end of the lecture. Small challenges to solve can for example be found on Codewars.
    
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    Don’t give up!
    
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    • Programming is problem solving, don’t get frustrated!
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    • Expect to stretch your comfort zone
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    Setting up Python
    
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    The Setup
    
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    Tip
    
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    IDE = Integrated Development Environment
    
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    Install Python
    
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    Tip
    
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    If the installation does not work, let us know!
    
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    Install VS Code
    
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    • Download and install from the website
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    • Built for Windows, Linux and Mac
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    • Install the Python and Jupyter extension
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    • Now you are ready to go!
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    Tip
    
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    Unsure on how to work with VS Code and notebooks? Take a look at the tutorial from VS Code and/or ask us! We are happy to help you out!
    
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    Python on iPads
    
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    • You can run Python scripts on your iPad
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    • But it is not recommended for the course
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    • However, you could use Juno if you want to
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    • It works locally on your iPad and can run notebooks
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    Caution
    
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    Not all packages available in Python are available here, thus you might need a computer to solve certain problems. For our course, this should not be a problem.
    
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    Your first code
    
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    Hello, World!
    
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    Task: Create a directory for the course and create a new file called hello_world.py with the following code:
    
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    # This is a comment in Python
+print("Hello, World!")
    
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    Hello, World!
    
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    Run it with the green ‘run’ button or by pressing F5!
    
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    Note
    
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    “Hello world” is a classic example to start with. Often used as a test to check if your computer is working properly and that you have installed the necessary software.
    
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    Any questions
    
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    so far?
    
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    Optimal Stopping
    
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    What is Optimal Stopping?
    
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    Question: Anybody know what optimal stopping is?
    
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+
      
+
    • Optimal stopping is the problem of:
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      • choosing the best option
        • 
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      • from a sequence of options
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      • where the options are revealed one by one
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      • 
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    Anybody an
    
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    example of
    
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    optimal stopping?
    
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    Flat Hunting
    
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    Photo by Aditya Ghosh on Unsplash
    
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    Hiring applicants
    
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    Photo by Scott Graham on Unsplash
    
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    Dating
    
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    Photo by Shelby Deeter on Unsplash
    
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    Searching for a parking spot
    
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    Photo by Joseph Pearson on Unsplash
    
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+
    “Secretary Problem”
    
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    The Secretary Problem
    
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+
      
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    • Imagine you’re hiring a secretary
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    • You must interview candidates one by one
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    • Now, you must decide: hire or continue searching
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    • Once you reject a candidate, you cannot go back
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    • How to maximize chance of selecting the best candidate?
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    Note
    
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    The name is a bit misleading, as the problem is not about hiring a secretary, but about finding the best candidate. It comes from the 1960s and thus a little outdated.
    
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    Basic Setup
    
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    • We have n candidates
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    • We interview them one by one
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    • We must decide to hire or continue searching
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    • Ordinal ranking of candidates
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    Question: Anybody know what ordinal ranking is?
    
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    Ways to fail
    
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    Question: Anybody an idea how we can fail?
    
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    1. Reject all candidates and never hire - stopping too late
      2. 
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    2. You hire someone too early - stopping too early
      3. 
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    Ideas?
    
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    Look-and-Leap Strategy
    
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    The optimal strategy is to:
    
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    1. Look at the first 37 % of options
      2. 
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    2. Remember the best one seen so far
      3. 
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    3. Choose the next option that’s better than the best seen
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    4. Chance of selecting the best candidate is 37 %1
      5. 
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    5. Thus, we can fail with 63 %!
      6. 
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    Step-by-step Approximation
    
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    • With each additional candidate, the chance of getting a new best candidate decreases
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      • 1 candidate: 100%
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      • 2 candidates: 50%
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      • 3 candidates: 33%
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      • 4 candidates: 25%
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      • 5 candidates: 20%
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      • 
+
    
+
    
+
    Question: Anybody see a pattern?
    
+
    
+
    
+
    
+
    Why 37%?
    
+
      
+
    • This is based on the geometric distribution
      • 
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    • The optimal stopping point is at n/e1
      • 
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    • e is the base of the natural logarithm (≈ 2.718)
      • 
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    • This comes from maximizing the probability of success
      • 
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+
    
+
    
+
    Computing the number
    
+
    
+
    import math
+
+percentage = 1/math.e
+print(f"Percentage of options to look at: {percentage:.3f}%")
+
+candidates = 20
+lookout_phase = candidates/math.e
+print(f"Look at first {lookout_phase:.3f} candidates")
    
+
    
+
    
+
    
+
    Percentage of options to look at: 0.368%
+Look at first 7.358 candidates
    
+
    
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    Note
    
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    No worries if you don’t understand the code! We are essentialy just using the formula to calculate the percentage of candidates to look at.
    
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    Geometric Distribution
    
+
    Let’s visualize the success of a simulation with 20 candidates:
    
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    Variations
    
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    Rejection
    
+
    Question: Imagine a dating scenario, where the other person can also reject you. Optimal stopping point?
    
+
    
+
      
+
    • The optimal stopping point is now lower
      • 
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    • Because we can now fail more often
      • 
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    • With 50 % chance of rejection, we start leaping at 25 %
      • 
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    • Formula: \(q^{\frac{1}{1-q}}\) with \(q\) being the chance of rejection
      • 
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+
    
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+
    
+
    The role of time
    
+
    What if we don’t have a fixed number of candidates, but rather a fixed amount of time?
    
+
    
+
      
+
    • Imagine we have one year to find a new flat
      • 
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    • We want the best flat, but don’t know what a good flat is
      • 
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+
    Question: How should we behave?
    
+
    
+
    
+
      
+
    • Same, but now we decide when to stop searching!
      • 
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+
    
+
    Other versions
    
+
      
+
    • Selling a house for the best price (“Threshold Rule”)
      • 
+
    • Stealing with a success probability (“Burglar’s Problem”)
      • 
+
    • Finding a parking spot (“Parking Lot Problem”) [^2]
      • 
+
    
+
    
+
    
+
    
+
    
+
    
+
+
    
+
    Note
    
+
    
+
    
+
    Side note for drivers: An increase in occupancy from 90 to 95% doubles the search time for all drivers!
    
+
    
+
    
+
    
+
    
+
    
+
    
+
    
+
    Optimal Solution
    
+
+
    
+
    
+
    The Gambler’s Fallacy
    
+
    Question: Can you imagine a scenario where it would be unwise to use optimal stopping?
    
+
    
+
      
+
    • Imagine a game with a 50 % chance of winning
      • 
+
    • If you win, your payoff is a triple of your bet
      • 
+
    • If you lose, you have to pay your bet
      • 
+
    
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+
    Questions?
    
+
    
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+
    
+
    The End
    
+
    
+
    
+
    
+
    
+
+
    
+
    Note
    
+
    
+
    
+
    That’s it for todays lecture!
    
+We now have covered a brief introduction into optimal stopping and seen how to set up Python. Now we can start with the tutorials!
    
+
    
+
    
+
    
+
    
+
    
+
    
+
    Literature
    
+
+
    
+
    
+
    Interesting literature to start
    
+
      
+
    • Christian, B., & Griffiths, T. (2016). Algorithms to live by: the computer science of human decisions. First international edition. New York, Henry Holt and Company.1
      • 
+
    • Ferguson, T.S. (1989) ‘Who solved the secretary problem?’, Statistical Science, 4(3). doi:10.1214/ss/1177012493.
      • 
+
    
+
    
+
    
+
    Books on Programming
    
+
      
+
    • Downey, A. B. (2024). Think Python: How to think like a computer scientist (Third edition). O’Reilly. Here
      • 
+
    • Elter, S. (2021). Schrödinger programmiert Python: Das etwas andere Fachbuch (1. Auflage). Rheinwerk Verlag.
      • 
+
    
+
    
+
    
+
    
+
    
+
    
+
+
    
+
    Note
    
+
    
+
    
+
    Think Python is a great book to start with. It’s available online for free. Schrödinger Programmiert Python is a great alternative for German students, as it is a very playful introduction to programming with lots of examples.
    
+
    
+
    
+
    
+
    
+
    
+
    
+
    More Literature
    
+
    For more interesting literature, take a look at the literature list of this course.
    
+
+
+
    
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+    
    
+  
    
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+  
+  
+  
+  
+  
+  
+  
+  
+  
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+  
+  
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+  
+    
+    
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+
\ No newline at end of file
diff --git a/part-01/tutorial-01-variables 3.html b/part-01/tutorial-01-variables 3.html
new file mode 100644
index 0000000..c24cdf9
--- /dev/null
+++ b/part-01/tutorial-01-variables 3.html	
@@ -0,0 +1,1051 @@
+
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+
+Tutorial I.I - Variables and Types – Programming: Everyday Decision-Making Algorithms
+
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+  
    
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+  
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+    
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+
    Tutorial I.I - Variables and Types
    
+
    Programming: Everyday Decision-Making Algorithms
    
+
    
+
+
+
+
    
+
+    
+  
+    
+  
    
+  
+
+
+
    
+
+
+
    
+
    Introduction
    
+
    Welcome to this interactive Python tutorial on variables, types, and algorithmic thinking! We’ll explore these concepts through the lens of optimization problems, specifically using the famous “Secretary Problem” as our running example.
    
+
    The Secretary Problem asks: “If you need to hire the best candidate, and you can only interview candidates one at a time (with no going back), when should you stop and make an offer?” This is a perfect example of optimal stopping and will help us understand how variables and data types play crucial roles in algorithmic thinking. To make the problem more interesting, we will use the Secretary Problem to help us make better dating decisions!
    
+
    The question is thus: When should you stop dating and commit to someone?
    
+
    Known academically as the “Optimal Stopping Problem” or “The Marriage Problem”, it asks: If you want to find the best possible partner, and you can only date one person at a time (no going back to previous dates!), when should you stop dating and propose?
    
+
    Let’s learn how to use Python to help us in order to make better dating decisions!
    
+
    
+
    
+
    1 - Variables
    
+
    Just like you keep track of important things in dating (name, phone number, red flags), in Python we use variables to store information:
    
+
    
+
    date_name = "Alexander" # Current date's name
+red_flags = 0 # Count of red flags noticed
+butterflies_felt = True # Do I feel butterflies?
+compatibility_score = 8.5 # On a scale of 1-10, how compatible are we?
+print("We have defined a some variables based on tonight's date.")
    
+
    
+
    We have defined a some variables based on tonight's date.
    
+
    
+
    
+
    
+
    
+
    
+
+
    
+
    
+Tip
+
    
+
    
+
    
+
    Variables in Python are like containers that store information. When we write date_name = "Alexander", we’re:
    
+
      
+
    1. Creating a container called date_name
      2. 
+
    2. Putting the value “Alexander” inside it
      3. 
+
    3. Telling Python this is a text value (string)
      4. 
+
    
+
    
+
    
+
    
+
    
+
    
+
+
    
+
    
+Note
+
    
+
    
+
    
+
    Notice how we use meaningful variable names that describe what they contain:
    
+
      
+
    • date_name is better than just name
      • 
+
    • red_flags is clearer than just flags
      • 
+
    • butterflies_felt clearly indicates a yes/no feeling
      • 
+
    
+
    
+
    
+
    
+
    Exercise 1.1 - First Date Setup
    
+
    Create a variable currently_dating and set it to False (because we’re starting our dating journey).
    
+
    
+
    # YOUR CODE BELOW
    
+
    
+
    
+
    
+Code
+
    # Test your answer
+assert currently_dating == False, "Let's start fresh - set currently_dating to False!"
+print("Ready to start dating! We have defined the variable `currently_dating` as boolean.")
    
+
    
+
    
+
    
+
    
+
    Exercise 1.2 - Date Name
    
+
    Create a variable date_name with your tonight’s date’s name (let’s say "Mika").
    
+
    
+
    # YOUR CODE BELOW
    
+
    
+
    
+
    
+Code
+
    # Test your answer
+assert date_name == "Mika", "Let's use 'Mika' as our tonight's date's name"
+print(f"We have defined a string variable for our tonight's date. Now, we are looking for {date_name}!")
    
+
    
+
    
+
    
+
    
+
    
+
    2 - Types
    
+
    Just like dating involves different types of information, Python has different types for different kinds of data:
    
+
      
+
    • Integers (int): Counting things (number of dates, red flags)
      • 
+
    • Floats (float): Ratings and scores (compatibility score)
      • 
+
    • Booleans (bool): Yes/no information (are they single?)
      • 
+
    • Strings (str): Text (names, favorite food)
      • 
+
    
+
    
+
    
+
    
+
+
    
+
    
+Important
+
    
+
    
+
    
+
    Why do types matter? Because:
    
+
      
+
    • They determine what operations we can perform (you can’t divide names!)
      • 
+
    • They affect how much memory the computer needs
      • 
+
    • They help prevent errors in our code
      • 
+
    
+
    
+
    
+
    
+
    dates_gone_on = 7  # int: keeping count
+chemistry_level = 9.5  # float: rating of the butterflies
+is_single = True  # bool: availability
+favorite_food = "Sushi"  # str: important info!
+print(f"We have gone on {dates_gone_on} dates, a chemistry level of {chemistry_level} in the last date, and we love {favorite_food}!")
    
+
    
+
    We have gone on 7 dates, a chemistry level of 9.5 in the last date, and we love Sushi!
    
+
    
+
    
+
    
+
    
+
    
+
+
    
+
    
+Tip
+
    
+
    
+
    
+
    You can check a variable’s type using the type() function.
    
+
    
+
    
+
    
+
    Exercise 2.1 - Dating Score
    
+
    Create a float variable minimum_rating and set it to 7.0 (our standards are high!). Of course, we don’t objectify people and rate their appearance, thus we rate the compatibility!
    
+
    
+
    # YOUR CODE BELOW
    
+
    
+
    
+
    
+Code
+
    # Test your answer
+assert minimum_rating == 7.0 and isinstance(minimum_rating, float), "Set your standards (minimum_rating) to 7.0!"
+print(f"We won't settle for less than {minimum_rating}/10, where the minimum rating is defined as a float!")
    
+
    
+
    
+
    
+
    
+
    Exercise 2.2 - Dating History
    
+
    Create an integer variable past_relationships and set it to 0.
    
+
    
+
    # YOUR CODE BELOW
    
+
    
+
    
+
    
+Code
+
    # Test your answer
+assert past_relationships == 0 and isinstance(past_relationships, int), "Let's start fresh with 0 past relationships"
+print("Clean slate, although likely not true! We have defined the variable `past_relationships` as an integer and are ready to start dating!")
    
+
    
+
    
+
    
+
    
+
    
+
    3 - Converting Data Types
    
+
    Python provides several functions to convert between different types:
    
+
      
+
    • int(): Converts to integer
+
        
+
      • int("37") → 37
        • 
+
      • int(37.8) → 37 (truncates decimal)
        • 
+
      • 
+
    • float(): Converts to float
+
        
+
      • float("37.5") → 37.5
        • 
+
      • float(37) → 37.0
        • 
+
      • 
+
    • str(): Converts to string
+
        
+
      • str(37) → "37"
        • 
+
      • str(37.5) → "37.5"
        • 
+
      • 
+
    • bool(): Converts to boolean
+
        
+
      • bool(1) → True
        • 
+
      • bool(0) → False
        • 
+
      • bool("") → False
        • 
+
      • bool("hello") → True
        • 
+
      • 
+
    
+
    In optimal stopping for dating, the math says you should date and reject the first 37% of your dating pool, then commit to the next person who’s better than everyone you’ve met before! Let’s track this:
    
+
    
+
    dating_pool = 100 # The number of people we will date
+exploration_phase = int(dating_pool * 0.37)  # The 37% rule
+print(f"Date (and reject) the first {exploration_phase} people")
    
+
    
+
    Date (and reject) the first 37 people
    
+
    
+
    
+
    
+
    Exercise 3.1 - Decision Point
    
+
    Convert the string "37" into an integer variable named stopping_point.
    
+
    
+
    stopping_point = "37"
+# YOUR CODE BELOW
    
+
    
+
    
+
    
+Code
+
    # Test your answer
+assert isinstance(stopping_point, int) and stopping_point == 37, "Convert '37' to an integer"
+print(f"After person {stopping_point}, we'll get serious about finding the best possible partner.")
    
+
    
+
    
+
    
+
    
+
    
+
+
    
+
    
+Tip
+
    
+
    
+
    
+
    When converting strings to numbers:
    
+
      
+
    • Make sure the string contains only numeric characters
      • 
+
    • Use int() for whole numbers
      • 
+
    • Use float() if you need decimal points
      • 
+
    
+
    
+
    
+
    
+
    
+
    
+
    4 - String Formatting
    
+
    String formatting is a powerful tool in Python that allows you to insert variables into strings. We do so by using curly braces {} around the variable names and with the f prefix before the string. For example:
    
+
    
+
    name = "Casey"
+print(f"Hello, {name}! Nice to meet you.")
    
+
    
+
    Hello, Casey! Nice to meet you.
    
+
    
+
    
+
    Here, {name} will insert the value of name into the string if the variable name is defined.
    
+
    Let’s create a nice dating profile using string formatting:
    
+
    
+
    name = "Casey"
+age = 25 # Age of Casey
+bio = f"{name}, {age} - Looking for someone special!" # Insert the variables into the string
+print(bio) # Print the string which is stored in bio
    
+
    
+
    Casey, 25 - Looking for someone special!
    
+
    
+
    
+
    
+
    Exercise 4.1 - Profile Message
    
+
    We have already defined the variables name and minimum_rating. Now we want to use them in the context of a formatted string. Create a formatted string profile_message using the variables name and minimum_rating that says “Hello, {name}! Nice to meet you. I hope you are at least {minimum_rating}/10 compatible with me!”.
    
+
    
+
    # YOUR CODE BELOW
    
+
    
+
    
+
    
+Code
+
    # Test your answer
+assert profile_message == "Hello, Casey! Nice to meet you. I hope you are at least 7.0/10 compatible with me!", "Format your first message to Casey correctly!"
+print("Your message is send - good luck!")
    
+
    
+
    
+
    
+
    
+
    
+
    Conclusion
    
+
    Congratulations! You’ve learned about Python variables and types through the lens of dating optimization!
    
+
    Remember:
    
+
      
+
    • Variables help track your dating journey
      • 
+
    • Different types handle different kinds of dating data
      • 
+
    • The 37% rule suggests when to get serious
      • 
+
    • String formatting helps create the perfect dating profile
      • 
+
    
+
    Dating tip: While this mathematical approach is a good starting point, remember that love isn’t always logical! We haven’t considered the emotional aspects of dating yet or the fact that we might not be the best partner for each other.
    
+
    
+
    
+
    
+
    Solutions
    
+
    You will likely find solutions to most exercises online. However, we strongly encourage you to work on these exercises independently without searching explicitly for the exact answers to the exercises. Understanding someone else’s solution is very different from developing your own. Use the lecture notes and try to solve the exercises on your own. This approach will significantly enhance your learning and problem-solving skills.
    
+
    Remember, the goal is not just to complete the exercises, but to understand the concepts and improve your programming abilities. If you encounter difficulties, review the lecture materials, experiment with different approaches, and don’t hesitate to ask for clarification during class discussions.
    
+
    Later, you will find the solutions to these exercises online in the associated GitHub repository, but we will also quickly go over them next week. To access the solutions, click on the Github button on the lower right and search for the folder with today’s lecture and tutorial. Alternatively, you can ask ChatGPT or Claude to explain them to you. But please remember, the goal is not just to complete the exercises, but to understand the concepts and improve your programming abilities.
    
+
    
+
    Continue to the next tutorial to learn about comparisons and conditionals in the context of the optimal stopping problem!
    
+
+
+
    
+
+
     
+
+
     
+
+
+
+
+
+
\ No newline at end of file
diff --git a/part-01/tutorial-01-variables 3.ipynb b/part-01/tutorial-01-variables 3.ipynb
new file mode 100644
index 0000000..f3b4487
--- /dev/null
+++ b/part-01/tutorial-01-variables 3.ipynb	
@@ -0,0 +1,534 @@
+{
+  "cells": [
+    {
+      "cell_type": "markdown",
+      "metadata": {},
+      "source": [
+        "# Tutorial I.I - Variables and Types\n",
+        "\n",
+        "Programming: Everyday Decision-Making Algorithms\n",
+        "\n",
+        "# Introduction\n",
+        "\n",
+        "Welcome to this interactive Python tutorial on variables, types, and\n",
+        "algorithmic thinking! We’ll explore these concepts through the lens of\n",
+        "optimization problems, specifically using the famous “Secretary Problem”\n",
+        "as our running example.\n",
+        "\n",
+        "The Secretary Problem asks: “If you need to hire the best candidate, and\n",
+        "you can only interview candidates one at a time (with no going back),\n",
+        "when should you stop and make an offer?” This is a perfect example of\n",
+        "optimal stopping and will help us understand how variables and data\n",
+        "types play crucial roles in algorithmic thinking. To make the problem\n",
+        "more interesting, we will use the Secretary Problem to help us make\n",
+        "better dating decisions!\n",
+        "\n",
+        "The question is thus: **When should you stop dating and commit to\n",
+        "someone?**\n",
+        "\n",
+        "Known academically as the “Optimal Stopping Problem” or “The Marriage\n",
+        "Problem”, it asks: If you want to find the best possible partner, and\n",
+        "you can only date one person at a time (no going back to previous\n",
+        "dates!), when should you stop dating and propose?\n",
+        "\n",
+        "Let’s learn how to use Python to help us in order to make better dating\n",
+        "decisions!\n",
+        "\n",
+        "# 1 - Variables\n",
+        "\n",
+        "Just like you keep track of important things in dating (name, phone\n",
+        "number, red flags), in Python we use variables to store information:"
+      ],
+      "id": "3b598f62-546e-4ab1-980a-a90cdb6cb933"
+    },
+    {
+      "cell_type": "code",
+      "execution_count": 1,
+      "metadata": {},
+      "outputs": [
+        {
+          "output_type": "stream",
+          "name": "stdout",
+          "text": [
+            "We have defined a some variables based on tonight's date."
+          ]
+        }
+      ],
+      "source": [
+        "date_name = \"Alexander\" # Current date's name\n",
+        "red_flags = 0 # Count of red flags noticed\n",
+        "butterflies_felt = True # Do I feel butterflies?\n",
+        "compatibility_score = 8.5 # On a scale of 1-10, how compatible are we?\n",
+        "print(\"We have defined a some variables based on tonight's date.\")"
+      ],
+      "id": "da75f77d"
+    },
+    {
+      "cell_type": "markdown",
+      "metadata": {},
+      "source": [
+        "> **Tip**\n",
+        ">\n",
+        "> Variables in Python are like containers that store information. When\n",
+        "> we write `date_name = \"Alexander\"`, we’re:\n",
+        ">\n",
+        "> 1.  Creating a container called `date_name`\n",
+        "> 2.  Putting the value “Alexander” inside it\n",
+        "> 3.  Telling Python this is a text value (string)\n",
+        "\n",
+        "> **Note**\n",
+        ">\n",
+        "> Notice how we use meaningful variable names that describe what they\n",
+        "> contain:\n",
+        ">\n",
+        "> -   `date_name` is better than just `name`\n",
+        "> -   `red_flags` is clearer than just `flags`\n",
+        "> -   `butterflies_felt` clearly indicates a yes/no feeling\n",
+        "\n",
+        "## Exercise 1.1 - First Date Setup\n",
+        "\n",
+        "Create a variable `currently_dating` and set it to `False` (because\n",
+        "we’re starting our dating journey)."
+      ],
+      "id": "f4db1170-773a-40e6-aefd-a1bbd8f8ddbb"
+    },
+    {
+      "cell_type": "code",
+      "execution_count": 2,
+      "metadata": {},
+      "outputs": [],
+      "source": [
+        "# YOUR CODE BELOW"
+      ],
+      "id": "9a6bf51a"
+    },
+    {
+      "cell_type": "code",
+      "execution_count": 3,
+      "metadata": {},
+      "outputs": [],
+      "source": [
+        "# Test your answer\n",
+        "assert currently_dating == False, \"Let's start fresh - set currently_dating to False!\"\n",
+        "print(\"Ready to start dating! We have defined the variable `currently_dating` as boolean.\")"
+      ],
+      "id": "c29e457c"
+    },
+    {
+      "cell_type": "markdown",
+      "metadata": {},
+      "source": [
+        "## Exercise 1.2 - Date Name\n",
+        "\n",
+        "Create a variable `date_name` with your tonight’s date’s name (let’s say\n",
+        "`\"Mika\"`)."
+      ],
+      "id": "0076d6c8-92c2-48fa-9d6d-c3637302fded"
+    },
+    {
+      "cell_type": "code",
+      "execution_count": 4,
+      "metadata": {},
+      "outputs": [],
+      "source": [
+        "# YOUR CODE BELOW"
+      ],
+      "id": "10ded840"
+    },
+    {
+      "cell_type": "code",
+      "execution_count": 5,
+      "metadata": {},
+      "outputs": [],
+      "source": [
+        "# Test your answer\n",
+        "assert date_name == \"Mika\", \"Let's use 'Mika' as our tonight's date's name\"\n",
+        "print(f\"We have defined a string variable for our tonight's date. Now, we are looking for {date_name}!\")"
+      ],
+      "id": "8ebbdf41"
+    },
+    {
+      "cell_type": "markdown",
+      "metadata": {},
+      "source": [
+        "# 2 - Types\n",
+        "\n",
+        "Just like dating involves different types of information, Python has\n",
+        "different types for different kinds of data:\n",
+        "\n",
+        "-   Integers (`int`): Counting things (number of dates, red flags)\n",
+        "-   Floats (`float`): Ratings and scores (compatibility score)\n",
+        "-   Booleans (`bool`): Yes/no information (are they single?)\n",
+        "-   Strings (`str`): Text (names, favorite food)\n",
+        "\n",
+        "> **Important**\n",
+        ">\n",
+        "> Why do types matter? Because:\n",
+        ">\n",
+        "> -   They determine what operations we can perform (you can’t divide\n",
+        ">     names!)\n",
+        "> -   They affect how much memory the computer needs\n",
+        "> -   They help prevent errors in our code"
+      ],
+      "id": "0ba8ce20-7a62-478a-b24a-86ddc0f83160"
+    },
+    {
+      "cell_type": "code",
+      "execution_count": 6,
+      "metadata": {},
+      "outputs": [
+        {
+          "output_type": "stream",
+          "name": "stdout",
+          "text": [
+            "We have gone on 7 dates, a chemistry level of 9.5 in the last date, and we love Sushi!"
+          ]
+        }
+      ],
+      "source": [
+        "dates_gone_on = 7  # int: keeping count\n",
+        "chemistry_level = 9.5  # float: rating of the butterflies\n",
+        "is_single = True  # bool: availability\n",
+        "favorite_food = \"Sushi\"  # str: important info!\n",
+        "print(f\"We have gone on {dates_gone_on} dates, a chemistry level of {chemistry_level} in the last date, and we love {favorite_food}!\")"
+      ],
+      "id": "7d7567f4"
+    },
+    {
+      "cell_type": "markdown",
+      "metadata": {},
+      "source": [
+        "> **Tip**\n",
+        ">\n",
+        "> You can check a variable’s type using the `type()` function.\n",
+        "\n",
+        "## Exercise 2.1 - Dating Score\n",
+        "\n",
+        "Create a float variable `minimum_rating` and set it to `7.0` (our\n",
+        "standards are high!). Of course, we don’t objectify people and rate\n",
+        "their appearance, thus we rate the compatibility!"
+      ],
+      "id": "fad5a12f-0f46-4c52-af2d-b3496c67d338"
+    },
+    {
+      "cell_type": "code",
+      "execution_count": 7,
+      "metadata": {},
+      "outputs": [],
+      "source": [
+        "# YOUR CODE BELOW"
+      ],
+      "id": "f6af502d"
+    },
+    {
+      "cell_type": "code",
+      "execution_count": 8,
+      "metadata": {},
+      "outputs": [],
+      "source": [
+        "# Test your answer\n",
+        "assert minimum_rating == 7.0 and isinstance(minimum_rating, float), \"Set your standards (minimum_rating) to 7.0!\"\n",
+        "print(f\"We won't settle for less than {minimum_rating}/10, where the minimum rating is defined as a float!\")"
+      ],
+      "id": "2b0a3180"
+    },
+    {
+      "cell_type": "markdown",
+      "metadata": {},
+      "source": [
+        "## Exercise 2.2 - Dating History\n",
+        "\n",
+        "Create an integer variable `past_relationships` and set it to `0`."
+      ],
+      "id": "f8ec1d5e-d6ed-4972-9428-fc82a6318b26"
+    },
+    {
+      "cell_type": "code",
+      "execution_count": 9,
+      "metadata": {},
+      "outputs": [],
+      "source": [
+        "# YOUR CODE BELOW"
+      ],
+      "id": "9040bd37"
+    },
+    {
+      "cell_type": "code",
+      "execution_count": 10,
+      "metadata": {},
+      "outputs": [],
+      "source": [
+        "# Test your answer\n",
+        "assert past_relationships == 0 and isinstance(past_relationships, int), \"Let's start fresh with 0 past relationships\"\n",
+        "print(\"Clean slate, although likely not true! We have defined the variable `past_relationships` as an integer and are ready to start dating!\")"
+      ],
+      "id": "6855f2fc"
+    },
+    {
+      "cell_type": "markdown",
+      "metadata": {},
+      "source": [
+        "# 3 - Converting Data Types\n",
+        "\n",
+        "Python provides several functions to convert between different types:\n",
+        "\n",
+        "-   `int()`: Converts to integer\n",
+        "    -   `int(\"37\")` → `37`\n",
+        "    -   `int(37.8)` → `37` (truncates decimal)\n",
+        "-   `float()`: Converts to float\n",
+        "    -   `float(\"37.5\")` → `37.5`\n",
+        "    -   `float(37)` → `37.0`\n",
+        "-   `str()`: Converts to string\n",
+        "    -   `str(37)` → `\"37\"`\n",
+        "    -   `str(37.5)` → `\"37.5\"`\n",
+        "-   `bool()`: Converts to boolean\n",
+        "    -   `bool(1)` → `True`\n",
+        "    -   `bool(0)` → `False`\n",
+        "    -   `bool(\"\")` → `False`\n",
+        "    -   `bool(\"hello\")` → `True`\n",
+        "\n",
+        "In optimal stopping for dating, the math says you should date and reject\n",
+        "the first 37% of your dating pool, then commit to the next person who’s\n",
+        "better than everyone you’ve met before! Let’s track this:"
+      ],
+      "id": "8d5d1728-8526-42d6-9c9d-e588575c8352"
+    },
+    {
+      "cell_type": "code",
+      "execution_count": 11,
+      "metadata": {},
+      "outputs": [
+        {
+          "output_type": "stream",
+          "name": "stdout",
+          "text": [
+            "Date (and reject) the first 37 people"
+          ]
+        }
+      ],
+      "source": [
+        "dating_pool = 100 # The number of people we will date\n",
+        "exploration_phase = int(dating_pool * 0.37)  # The 37% rule\n",
+        "print(f\"Date (and reject) the first {exploration_phase} people\")"
+      ],
+      "id": "e771b243"
+    },
+    {
+      "cell_type": "markdown",
+      "metadata": {},
+      "source": [
+        "## Exercise 3.1 - Decision Point\n",
+        "\n",
+        "Convert the string `\"37\"` into an integer variable named\n",
+        "`stopping_point`."
+      ],
+      "id": "9bb7a482-9150-434f-bbc2-1d26da91177b"
+    },
+    {
+      "cell_type": "code",
+      "execution_count": 12,
+      "metadata": {},
+      "outputs": [],
+      "source": [
+        "stopping_point = \"37\"\n",
+        "# YOUR CODE BELOW\n"
+      ],
+      "id": "66e19008"
+    },
+    {
+      "cell_type": "code",
+      "execution_count": 13,
+      "metadata": {},
+      "outputs": [],
+      "source": [
+        "# Test your answer\n",
+        "assert isinstance(stopping_point, int) and stopping_point == 37, \"Convert '37' to an integer\"\n",
+        "print(f\"After person {stopping_point}, we'll get serious about finding the best possible partner.\")"
+      ],
+      "id": "bab05f88"
+    },
+    {
+      "cell_type": "markdown",
+      "metadata": {},
+      "source": [
+        "> **Tip**\n",
+        ">\n",
+        "> When converting strings to numbers:\n",
+        ">\n",
+        "> -   Make sure the string contains only numeric characters\n",
+        "> -   Use `int()` for whole numbers\n",
+        "> -   Use `float()` if you need decimal points\n",
+        "\n",
+        "# 4 - String Formatting\n",
+        "\n",
+        "String formatting is a powerful tool in Python that allows you to insert\n",
+        "variables into strings. We do so by using curly braces `{}` around the\n",
+        "variable names and with the `f` prefix before the string. For example:"
+      ],
+      "id": "2c16e6b5-db1e-45eb-ae5d-b280726a5fae"
+    },
+    {
+      "cell_type": "code",
+      "execution_count": 14,
+      "metadata": {},
+      "outputs": [
+        {
+          "output_type": "stream",
+          "name": "stdout",
+          "text": [
+            "Hello, Casey! Nice to meet you."
+          ]
+        }
+      ],
+      "source": [
+        "name = \"Casey\"\n",
+        "print(f\"Hello, {name}! Nice to meet you.\")"
+      ],
+      "id": "84028990"
+    },
+    {
+      "cell_type": "markdown",
+      "metadata": {},
+      "source": [
+        "Here, `{name}` will insert the value of `name` into the string if the\n",
+        "variable `name` is defined.\n",
+        "\n",
+        "Let’s create a nice dating profile using string formatting:"
+      ],
+      "id": "8992331b-ef71-4ace-9125-0084825df505"
+    },
+    {
+      "cell_type": "code",
+      "execution_count": 15,
+      "metadata": {},
+      "outputs": [
+        {
+          "output_type": "stream",
+          "name": "stdout",
+          "text": [
+            "Casey, 25 - Looking for someone special!"
+          ]
+        }
+      ],
+      "source": [
+        "name = \"Casey\"\n",
+        "age = 25 # Age of Casey\n",
+        "bio = f\"{name}, {age} - Looking for someone special!\" # Insert the variables into the string\n",
+        "print(bio) # Print the string which is stored in bio"
+      ],
+      "id": "de9e70ac"
+    },
+    {
+      "cell_type": "markdown",
+      "metadata": {},
+      "source": [
+        "## Exercise 4.1 - Profile Message\n",
+        "\n",
+        "We have already defined the variables `name` and `minimum_rating`. Now\n",
+        "we want to use them in the context of a formatted string. Create a\n",
+        "formatted string `profile_message` using the variables `name` and\n",
+        "`minimum_rating` that says “Hello, {name}! Nice to meet you. I hope you\n",
+        "are at least {minimum_rating}/10 compatible with me!”."
+      ],
+      "id": "e434960a-3ff7-4343-967b-d5da1c9dbfb9"
+    },
+    {
+      "cell_type": "code",
+      "execution_count": 16,
+      "metadata": {},
+      "outputs": [],
+      "source": [
+        "# YOUR CODE BELOW"
+      ],
+      "id": "bf4428cd"
+    },
+    {
+      "cell_type": "code",
+      "execution_count": 17,
+      "metadata": {},
+      "outputs": [],
+      "source": [
+        "# Test your answer\n",
+        "assert profile_message == \"Hello, Casey! Nice to meet you. I hope you are at least 7.0/10 compatible with me!\", \"Format your first message to Casey correctly!\"\n",
+        "print(\"Your message is send - good luck!\")"
+      ],
+      "id": "24827a18"
+    },
+    {
+      "cell_type": "markdown",
+      "metadata": {},
+      "source": [
+        "# Conclusion\n",
+        "\n",
+        "Congratulations! You’ve learned about Python variables and types through\n",
+        "the lens of dating optimization!\n",
+        "\n",
+        "Remember:\n",
+        "\n",
+        "-   Variables help track your dating journey\n",
+        "-   Different types handle different kinds of dating data\n",
+        "-   The 37% rule suggests when to get serious\n",
+        "-   String formatting helps create the perfect dating profile\n",
+        "\n",
+        "Dating tip: While this mathematical approach is a good starting point,\n",
+        "remember that love isn’t always logical! We haven’t considered the\n",
+        "emotional aspects of dating yet or the fact that we might not be the\n",
+        "best partner for each other.\n",
+        "\n",
+        "------------------------------------------------------------------------\n",
+        "\n",
+        "# Solutions\n",
+        "\n",
+        "You will likely find solutions to most exercises online. However, we\n",
+        "strongly encourage you to work on these exercises independently without\n",
+        "searching explicitly for the exact answers to the exercises.\n",
+        "Understanding someone else’s solution is very different from developing\n",
+        "your own. Use the lecture notes and try to solve the exercises on your\n",
+        "own. This approach will significantly enhance your learning and\n",
+        "problem-solving skills.\n",
+        "\n",
+        "Remember, the goal is not just to complete the exercises, but to\n",
+        "understand the concepts and improve your programming abilities. If you\n",
+        "encounter difficulties, review the lecture materials, experiment with\n",
+        "different approaches, and don’t hesitate to ask for clarification during\n",
+        "class discussions.\n",
+        "\n",
+        "Later, you will find the solutions to these exercises online in the\n",
+        "associated GitHub repository, but we will also quickly go over them next\n",
+        "week. To access the solutions, click on the Github button on the lower\n",
+        "right and search for the folder with today’s lecture and tutorial.\n",
+        "Alternatively, you can ask ChatGPT or Claude to explain them to you. But\n",
+        "please remember, the goal is not just to complete the exercises, but to\n",
+        "understand the concepts and improve your programming abilities.\n",
+        "\n",
+        "------------------------------------------------------------------------\n",
+        "\n",
+        "*Continue to the next tutorial to learn about comparisons and\n",
+        "conditionals in the context of the optimal stopping problem!*"
+      ],
+      "id": "61276c4f-df3e-4caf-85ce-20c6a477ad19"
+    }
+  ],
+  "nbformat": 4,
+  "nbformat_minor": 5,
+  "metadata": {
+    "kernelspec": {
+      "name": "python3",
+      "display_name": "Python 3 (ipykernel)",
+      "language": "python",
+      "path": "/Users/tvlcek/miniconda3/share/jupyter/kernels/python3"
+    },
+    "language_info": {
+      "name": "python",
+      "codemirror_mode": {
+        "name": "ipython",
+        "version": "3"
+      },
+      "file_extension": ".py",
+      "mimetype": "text/x-python",
+      "nbconvert_exporter": "python",
+      "pygments_lexer": "ipython3",
+      "version": "3.12.7"
+    }
+  }
+}
\ No newline at end of file
diff --git a/part-01/tutorial-01-variables 3.pdf b/part-01/tutorial-01-variables 3.pdf
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diff --git a/part-01/tutorial-01-variables.html b/part-01/tutorial-01-variables.html
index e575840..1499881 100644
--- a/part-01/tutorial-01-variables.html
+++ b/part-01/tutorial-01-variables.html
@@ -220,6 +220,41 @@
   
  06 - Exploration
   
    
+
+      
+  
+        
  • 
+      
     
+            
+           
+      
    
+      
   
    • 
@@ -312,7 +347,7 @@ 
    Introduction
    
 
    
 
    1 - Variables
    
 
    Just like you keep track of important things in dating (name, phone number, red flags), in Python we use variables to store information:
    
-
    
+
    
 
    date_name = "Alexander" # Current date's name
 red_flags = 0 # Count of red flags noticed
 butterflies_felt = True # Do I feel butterflies?
@@ -361,10 +396,10 @@ 
    1 - Variables
    
 
    
 
    Exercise 1.1 - First Date Setup
    
 
    Create a variable currently_dating and set it to False (because we’re starting our dating journey).
    
-
    
+
    
 
    # YOUR CODE BELOW
    
 
    
-
    
+
    
 
    
 Code
 
    # Test your answer
@@ -376,10 +411,10 @@ 
    Exercise 1
 
    
 
    Exercise 1.2 - Date Name
    
 
    Create a variable date_name with your tonight’s date’s name (let’s say "Mika").
    
-
    
+
    
 
    # YOUR CODE BELOW
    
 
    
-
    
+
    
 
    
 Code
 
    # Test your answer
@@ -416,7 +451,7 @@ 
    2 - Types
    
 
 
    
 
    
-
    
+
    
 
    dates_gone_on = 7  # int: keeping count
 chemistry_level = 9.5  # float: rating of the butterflies
 is_single = True  # bool: availability
@@ -442,10 +477,10 @@ 
    2 - Types
    
 
    
 
    Exercise 2.1 - Dating Score
    
 
    Create a float variable minimum_rating and set it to 7.0 (our standards are high!). Of course, we don’t objectify people and rate their appearance, thus we rate the compatibility!
    
-
    
+
    
 
    # YOUR CODE BELOW
    
 
    
-
    
+
    
 
    
 Code
 
    # Test your answer
@@ -457,10 +492,10 @@ 
    Exercise 2.1 -
 
    
 
    Exercise 2.2 - Dating History
    
 
    Create an integer variable past_relationships and set it to 0.
    
-
    
+
    
 
    # YOUR CODE BELOW
    
 
    
-
    
+
    
 
    
 Code
 
    # Test your answer
@@ -498,7 +533,7 @@ 
    3 - Converting Data Types
    
 
 
 
    In optimal stopping for dating, the math says you should date and reject the first 37% of your dating pool, then commit to the next person who’s better than everyone you’ve met before! Let’s track this:
    
-
    
+
    
 
    dating_pool = 100 # The number of people we will date
 exploration_phase = int(dating_pool * 0.37)  # The 37% rule
 print(f"Date (and reject) the first {exploration_phase} people")
    
@@ -509,11 +544,11 @@ 
    3 - Converting Data Types
    
 
    
 
    Exercise 3.1 - Decision Point
    
 
    Convert the string "37" into an integer variable named stopping_point.
    
-
    
+
    
 
    stopping_point = "37"
 # YOUR CODE BELOW
    
 
    
-
    
+
    
 
    
 Code
 
    # Test your answer
@@ -544,7 +579,7 @@ 
    Exercise 3.1
 
    
 
    4 - String Formatting
    
 
    String formatting is a powerful tool in Python that allows you to insert variables into strings. We do so by using curly braces {} around the variable names and with the f prefix before the string. For example:
    
-
    
+
    
 
    name = "Casey"
 print(f"Hello, {name}! Nice to meet you.")
    
 
    
@@ -553,7 +588,7 @@ 
    4 - String Formatting
    
 
    
 
    Here, {name} will insert the value of name into the string if the variable name is defined.
    
 
    Let’s create a nice dating profile using string formatting:
    
-
    
+
    
 
    name = "Casey"
 age = 25 # Age of Casey
 bio = f"{name}, {age} - Looking for someone special!" # Insert the variables into the string
@@ -565,10 +600,10 @@ 
    4 - String Formatting
    
 
    
 
    Exercise 4.1 - Profile Message
    
 
    We have already defined the variables name and minimum_rating. Now we want to use them in the context of a formatted string. Create a formatted string profile_message using the variables name and minimum_rating that says “Hello, {name}! Nice to meet you. I hope you are at least {minimum_rating}/10 compatible with me!”.
    
-
    
+
    
 
    # YOUR CODE BELOW
    
 
    
-
    
+
    
 
    
 Code
 
    # Test your answer
diff --git a/part-01/tutorial-01-variables.ipynb b/part-01/tutorial-01-variables.ipynb
index a66c9f9..eb19b36 100644
--- a/part-01/tutorial-01-variables.ipynb
+++ b/part-01/tutorial-01-variables.ipynb
@@ -39,7 +39,7 @@
         "Just like you keep track of important things in dating (name, phone\n",
         "number, red flags), in Python we use variables to store information:"
       ],
-      "id": "7e1737a9-e201-4dbc-8e7c-6abb117b0e17"
+      "id": "2d3e07a8-0710-4f84-b696-ecf38bd39d9d"
     },
     {
       "cell_type": "code",
@@ -61,7 +61,7 @@
         "compatibility_score = 8.5 # On a scale of 1-10, how compatible are we?\n",
         "print(\"We have defined a some variables based on tonight's date.\")"
       ],
-      "id": "e397fd93"
+      "id": "9caee9be"
     },
     {
       "cell_type": "markdown",
@@ -90,7 +90,7 @@
         "Create a variable `currently_dating` and set it to `False` (because\n",
         "we’re starting our dating journey)."
       ],
-      "id": "a3b67db5-ad0c-4e23-99c9-2d6515c2ce59"
+      "id": "c87c6f95-a3a8-43f7-96d5-c92144f0431b"
     },
     {
       "cell_type": "code",
@@ -100,7 +100,7 @@
       "source": [
         "# YOUR CODE BELOW"
       ],
-      "id": "5a3e4d9f"
+      "id": "6ba61a37"
     },
     {
       "cell_type": "code",
@@ -112,7 +112,7 @@
         "assert currently_dating == False, \"Let's start fresh - set currently_dating to False!\"\n",
         "print(\"Ready to start dating! We have defined the variable `currently_dating` as boolean.\")"
       ],
-      "id": "3dbadfb5"
+      "id": "cb683d7d"
     },
     {
       "cell_type": "markdown",
@@ -123,7 +123,7 @@
         "Create a variable `date_name` with your tonight’s date’s name (let’s say\n",
         "`\"Mika\"`)."
       ],
-      "id": "ff24fae7-8e4b-4a45-b6d3-f59953d4185d"
+      "id": "628863ed-c250-428b-86d0-1288b76becf0"
     },
     {
       "cell_type": "code",
@@ -133,7 +133,7 @@
       "source": [
         "# YOUR CODE BELOW"
       ],
-      "id": "0ca319ff"
+      "id": "c44d1ee2"
     },
     {
       "cell_type": "code",
@@ -145,7 +145,7 @@
         "assert date_name == \"Mika\", \"Let's use 'Mika' as our tonight's date's name\"\n",
         "print(f\"We have defined a string variable for our tonight's date. Now, we are looking for {date_name}!\")"
       ],
-      "id": "d7bb0373"
+      "id": "9fc188f3"
     },
     {
       "cell_type": "markdown",
@@ -170,7 +170,7 @@
         "> -   They affect how much memory the computer needs\n",
         "> -   They help prevent errors in our code"
       ],
-      "id": "a27f530c-7911-4084-92c3-680940195185"
+      "id": "a20332cf-dee6-4c58-ac44-7d32ee3bda9a"
     },
     {
       "cell_type": "code",
@@ -192,7 +192,7 @@
         "favorite_food = \"Sushi\"  # str: important info!\n",
         "print(f\"We have gone on {dates_gone_on} dates, a chemistry level of {chemistry_level} in the last date, and we love {favorite_food}!\")"
       ],
-      "id": "094f08d9"
+      "id": "5b49f6b3"
     },
     {
       "cell_type": "markdown",
@@ -208,7 +208,7 @@
         "standards are high!). Of course, we don’t objectify people and rate\n",
         "their appearance, thus we rate the compatibility!"
       ],
-      "id": "fb5cfa01-7dfd-4394-b148-03db7fb3892e"
+      "id": "31f95453-7413-4f6b-859c-434ddf843be8"
     },
     {
       "cell_type": "code",
@@ -218,7 +218,7 @@
       "source": [
         "# YOUR CODE BELOW"
       ],
-      "id": "1cfe947b"
+      "id": "11c10068"
     },
     {
       "cell_type": "code",
@@ -230,7 +230,7 @@
         "assert minimum_rating == 7.0 and isinstance(minimum_rating, float), \"Set your standards (minimum_rating) to 7.0!\"\n",
         "print(f\"We won't settle for less than {minimum_rating}/10, where the minimum rating is defined as a float!\")"
       ],
-      "id": "24be6d49"
+      "id": "9a82c5f8"
     },
     {
       "cell_type": "markdown",
@@ -240,7 +240,7 @@
         "\n",
         "Create an integer variable `past_relationships` and set it to `0`."
       ],
-      "id": "6cad7a60-0175-41ba-bea6-96bbc33521ec"
+      "id": "7e921630-c9b1-4bf1-b99c-c7da2212102f"
     },
     {
       "cell_type": "code",
@@ -250,7 +250,7 @@
       "source": [
         "# YOUR CODE BELOW"
       ],
-      "id": "c9b2b735"
+      "id": "468de7b2"
     },
     {
       "cell_type": "code",
@@ -262,7 +262,7 @@
         "assert past_relationships == 0 and isinstance(past_relationships, int), \"Let's start fresh with 0 past relationships\"\n",
         "print(\"Clean slate, although likely not true! We have defined the variable `past_relationships` as an integer and are ready to start dating!\")"
       ],
-      "id": "28033a26"
+      "id": "3720cf1f"
     },
     {
       "cell_type": "markdown",
@@ -291,7 +291,7 @@
         "the first 37% of your dating pool, then commit to the next person who’s\n",
         "better than everyone you’ve met before! Let’s track this:"
       ],
-      "id": "f5810c5c-ad5e-4344-bc76-a88ebf99c175"
+      "id": "db17aa62-59b7-4bbb-ac77-6ece8d3c6219"
     },
     {
       "cell_type": "code",
@@ -311,7 +311,7 @@
         "exploration_phase = int(dating_pool * 0.37)  # The 37% rule\n",
         "print(f\"Date (and reject) the first {exploration_phase} people\")"
       ],
-      "id": "c201e8cc"
+      "id": "174518e3"
     },
     {
       "cell_type": "markdown",
@@ -322,7 +322,7 @@
         "Convert the string `\"37\"` into an integer variable named\n",
         "`stopping_point`."
       ],
-      "id": "d11da715-68a5-499e-81c2-584b99c800f6"
+      "id": "4722be46-6a6c-4a1c-9337-83a43ff4f02e"
     },
     {
       "cell_type": "code",
@@ -333,7 +333,7 @@
         "stopping_point = \"37\"\n",
         "# YOUR CODE BELOW\n"
       ],
-      "id": "54b41b9d"
+      "id": "3458e7b2"
     },
     {
       "cell_type": "code",
@@ -345,7 +345,7 @@
         "assert isinstance(stopping_point, int) and stopping_point == 37, \"Convert '37' to an integer\"\n",
         "print(f\"After person {stopping_point}, we'll get serious about finding the best possible partner.\")"
       ],
-      "id": "066fdac4"
+      "id": "c2acb8d7"
     },
     {
       "cell_type": "markdown",
@@ -365,7 +365,7 @@
         "variables into strings. We do so by using curly braces `{}` around the\n",
         "variable names and with the `f` prefix before the string. For example:"
       ],
-      "id": "8667f791-ccdc-4685-b0ee-32b5f26867a0"
+      "id": "09974b75-413d-45a5-a7ec-ea54a2ffbb54"
     },
     {
       "cell_type": "code",
@@ -384,7 +384,7 @@
         "name = \"Casey\"\n",
         "print(f\"Hello, {name}! Nice to meet you.\")"
       ],
-      "id": "5f568165"
+      "id": "00e9c643"
     },
     {
       "cell_type": "markdown",
@@ -395,7 +395,7 @@
         "\n",
         "Let’s create a nice dating profile using string formatting:"
       ],
-      "id": "10ed2941-c558-4d3d-bf62-958adc716c18"
+      "id": "021219db-7840-4b09-8628-f18f622f9cdd"
     },
     {
       "cell_type": "code",
@@ -416,7 +416,7 @@
         "bio = f\"{name}, {age} - Looking for someone special!\" # Insert the variables into the string\n",
         "print(bio) # Print the string which is stored in bio"
       ],
-      "id": "31ab1618"
+      "id": "997b8bff"
     },
     {
       "cell_type": "markdown",
@@ -430,7 +430,7 @@
         "`minimum_rating` that says “Hello, {name}! Nice to meet you. I hope you\n",
         "are at least {minimum_rating}/10 compatible with me!”."
       ],
-      "id": "c9c6e7df-2442-46cb-89d2-49cec0c0fb2c"
+      "id": "34ea4495-b39b-4b52-baed-fb7259e4e454"
     },
     {
       "cell_type": "code",
@@ -440,7 +440,7 @@
       "source": [
         "# YOUR CODE BELOW"
       ],
-      "id": "765b016e"
+      "id": "2a66130c"
     },
     {
       "cell_type": "code",
@@ -452,7 +452,7 @@
         "assert profile_message == \"Hello, Casey! Nice to meet you. I hope you are at least 7.0/10 compatible with me!\", \"Format your first message to Casey correctly!\"\n",
         "print(\"Your message is send - good luck!\")"
       ],
-      "id": "1c0f2617"
+      "id": "d0420600"
     },
     {
       "cell_type": "markdown",
@@ -506,7 +506,7 @@
         "*Continue to the next tutorial to learn about comparisons and\n",
         "conditionals in the context of the optimal stopping problem!*"
       ],
-      "id": "72024e75-3b4a-49e6-ba42-3d16a4148835"
+      "id": "c637708d-09f3-463f-9d2a-5a718bf12de4"
     }
   ],
   "nbformat": 4,
diff --git a/part-01/tutorial-01-variables.pdf b/part-01/tutorial-01-variables.pdf
index 036f3823e7ce93136902267321c636d57110cfbc..6600eed79b1b284badccf7b333e64d689df18497 100644
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diff --git a/part-01/tutorial-02-comparisons 3.html b/part-01/tutorial-02-comparisons 3.html
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+Tutorial I.II - Comparison Operators – Programming: Everyday Decision-Making Algorithms
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    Tutorial I.II - Comparison Operators
    
+
    Programming: Everyday Decision-Making Algorithms
    
+
    
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+
    
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+    
+  
+    
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+
    Introduction
    
+
    You’re teaching a computer to make decisions. Just like we compare things in everyday life (“Is it raining?”, “Do I have enough money?”), computers need ways to compare values and make choices. Let’s look at this in the context of hiring decisions to help us how to make decisions in the context of optimal stopping problems.
    
+
    Imagine you’re helping a company make hiring decisions. You need to look at different candidates and decide if they meet certain requirements. To make these decisions with Python, we need to learn how to make comparisons!
    
+
    
+
    
+
    1 - Basic Comparisons
    
+
    When looking at job candidates, we often ask questions like:
    
+
      
+
    • Does the candidate have enough experience?
      • 
+
    • Is their salary request within our budget?
      • 
+
    • Did they score well on the test?
      • 
+
    
+
    These questions all require yes/no (True/False) answers, which is exactly what comparison operators give us in Python. Each comparison will result in either True or False.
    
+
    In Python, we use special symbols to make these comparisons:
    
+
    
+
    # Let's look at the current candidate compared to the best we've seen so far
+current_candidate_score = 85
+best_score_so_far = 82
+
+# Is this the best candidate yet?
+is_best_so_far = (current_candidate_score > best_score_so_far)
+print(f"Is this our best candidate so far? {is_best_so_far}")
+
+# Have we interviewed enough candidates?
+candidates_seen = 15
+total_candidates = 30
+passed_threshold = (candidates_seen >= total_candidates * 0.37)
+print(f"Have we passed our optimal stopping threshold? {passed_threshold}")
    
+
    
+
    Is this our best candidate so far? True
+Have we passed our optimal stopping threshold? True
    
+
    
+
    
+
    
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+
    
+Tip
+
    
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+
    
+
    When you make a comparison in Python, the result is always a boolean value (True or False). This is why we can store the result in variables like is_best_so_far - these variables will contain either True or False.
    
+
    
+
    
+
    Here are all the comparison operators we can use:
    
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    SymbolMeaningExample
    ==Equal toscore == 100
    !=Not equal todegree != "Computer Science"
    <Less thansalary < 80000
    >Greater thanexperience > 5
    <=Less than or equal toage <= 65
    >=Greater than or equal totest_score >= 80
    
+
    
+
    Exercise 1.1 - Compare Test Scores
    
+
    A candidate scored 95 on their test. The previous highest score was 88. Create a comparison to check if the new score is better and store the result in compare_scores.
    
+
    
+
    # Creates the variables
+new_score = 95
+previous_best = 88
+# YOUR CODE BELOW
    
+
    
+
    
+
    
+Code
+
    # Test your answer
+assert compare_scores == True, "The new score should be greater than the previous best"
+print(f"Is new score better? {compare_scores}")
    
+
    
+
    
+
    
+
    
+
    Exercise 1.2 - Compare Skills
    
+
    Check if a candidate’s skill matches what we need. Compare if the following two variables are different and store the result in compare_skills.
    
+
    
+
    candidate_skill = "Finance"
+required_skill = "Python"
+# YOUR CODE BELOW
    
+
    
+
    
+
    
+Code
+
    # Test your answer
+assert compare_skills == False, "The candidate's skill should not match the required skill"
+print("Good job! You correctly identified that the skills are different")
    
+
    
+
    
+
    
+
    
+
    Exercise 1.3 - Compare Candidates
    
+
    In the secretary problem, we need to compare candidates to the best we’ve seen. Check if the current candidate is better than our best so far and store the result in is_better.
    
+
    
+
    current_rating = 92
+best_so_far = 88
+# YOUR CODE BELOW
    
+
    
+
    
+
    
+Code
+
    # Test your answer
+assert is_better == True, "The current candidate should be better than the best so far"
+print("Good job! You correctly identified that the current candidate is better than the best so far")
    
+
    
+
    
+
    
+
    
+
    
+
    2 - Combining Comparisons with Logical Operators
    
+
    Often, we need to check multiple things at once. For example, a good candidate should:
    
+
      
+
    • Have enough experience
      • 
+
    • Be within our budget
      • 
+
    • Pass the test
      • 
+
    
+
    Python gives us three ways to combine comparisons:
    
+
      
+
    • and: Both conditions must be true
      • 
+
    • or: At least one condition must be true
      • 
+
    • not: Makes true become false and false become true
      • 
+
    
+
    Let’s see some examples:
    
+
    
+
    # Candidate information
+experience = 5
+test_score = 90
+salary_ask = 75000
+
+# Check multiple requirements at once
+meets_experience = (experience >= 3)
+good_test_score = (test_score >= 85)
+affordable = (salary_ask <= 80000)
+
+# All requirements must be met (using AND)
+is_good_candidate = (meets_experience and good_test_score and affordable)
+print(f"Should we hire this candidate? {is_good_candidate}")
+
+# Alternative qualifications (using OR)
+has_degree = True
+has_certification = False
+is_qualified = (has_degree or has_certification)
+print(f"Is candidate qualified? {is_qualified}")
    
+
    
+
    Should we hire this candidate? True
+Is candidate qualified? True
    
+
    
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+
    
+Important
+
    
+
    
+
    
+
    Common Mistakes to Avoid:
    
+
      
+
    1. Don’t confuse = (assignment) with == (comparison)
      2. 
+
    2. Remember that and requires ALL conditions to be True
      3. 
+
    3. When combining multiple comparisons, use parentheses to make your logic clear Example: (experience >= 3) and (test_score >= 85)
      4. 
+
    
+
    
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+
    
+
    Exercise 2.1 - Check Multiple Requirements
    
+
    We have a candidate with:
    
+
      
+
    • 4 years of experience
      • 
+
    • Test score of 90
      • 
+
    
+
    Check if they meet BOTH requirements:
    
+
      
+
    • More than 3 years experience
      • 
+
    • Test score above 85
      • 
+
    
+
    Store the result in meets_requirements.
    
+
    
+
    years = 4
+score = 90
+# YOUR CODE BELOW
    
+
    
+
    
+
    
+Code
+
    # Test your answer
+assert meets_requirements == True, "The candidate should meet both requirements"
+print("Good job! You correctly identified that the candidate meets both requirements")
    
+
    
+
    
+
    
+
    
+
    Exercise 2.2 - Alternative Requirements
    
+
    A candidate is acceptable if they EITHER:
    
+
      
+
    • Have a PhD
      • 
+
    • OR have a high test score (above 95)
      • 
+
    
+
    Store the result in is_qualified
    
+
    
+
    has_phd = True
+test_score = 92
+# YOUR CODE BELOW
    
+
    
+
    
+
    
+Code
+
    # Test your answer
+assert is_qualified == True, "The candidate should be qualified"
+print("Good job! You correctly identified that the candidate is qualified")
    
+
    
+
    
+
    
+
    
+
    
+
    3 - Putting It All Together
    
+
    Let’s look at a real candidate and check all their qualifications:
    
+
    
+
    # Secretary Problem Scenario
+candidate_name = "Mika"
+candidates_seen = 25
+total_candidates = 50
+current_score = 88
+best_score_so_far = 85
+
+# Our decision criteria
+threshold_ratio = 0.37
+passed_threshold = (candidates_seen >= total_candidates * threshold_ratio)
+is_best_so_far = (current_score > best_score_so_far)
+
+# Final decision - must pass threshold AND be best so far
+should_hire = (passed_threshold and is_best_so_far)
+
+print(f"Candidate: {candidate_name}")
+print(f"Passed observation threshold: {passed_threshold}")
+print(f"Best candidate so far: {is_best_so_far}")
+print(f"Final decision - Should hire: {should_hire}")
    
+
    
+
    Candidate: Mika
+Passed observation threshold: True
+Best candidate so far: True
+Final decision - Should hire: True
    
+
    
+
    
+
    
+
    Exercise 3.1 - Make a Hiring Decision
    
+
    Look at the following candidate’s information and decide if we should hire them:
    
+
    Requirements:
    
+
      
+
    • At least 5 years experience
      • 
+
    • Test score above 85
      • 
+
    • Salary request at most 90000
      • 
+
    • Must have a degree
      • 
+
    
+
    Create a single boolean expression that checks ALL requirements and store the result in final_decision.
    
+
    
+
    # Candidate information
+candidate_experience = 7
+candidate_score = 89
+candidate_salary = 92000
+candidate_has_degree = True
+# YOUR CODE BELOW
    
+
    
+
    
+
    
+Code
+
    # Test your answer
+assert final_decision == False, "The candidate should not meet all requirements"
+print("Good job! You correctly identified that the candidate does not meet all requirements as his salary expectation is too high.")
    
+
    
+
    
+
    
+
    
+
    Exercise 2.3 - Optimal Stopping Decision
    
+
    We have:
    
+
      
+
    • Seen 18 out of 40 candidates
      • 
+
    • Current candidate score: 90
      • 
+
    • Best score so far: 85
      • 
+
    
+
    Check if we should hire this candidate (we should hire if we’ve seen at least 37% of candidates AND this candidate is better than the best so far).
    
+
    Store the result in make_offer.
    
+
    
+
    # Candidate information
+candidates_seen = 18
+total_candidates = 40
+current_score = 90
+best_score_so_far = 85
+# YOUR CODE BELOW
    
+
    
+
    
+
    
+Code
+
    # Test your answer
+assert make_offer == True, "We should hire this candidate"
+print("Good job! You correctly identified that we should hire this candidate")
    
+
    
+
    
+
    
+
    
+
    
+
    Conclusion
    
+
    Great job! You now know how to:
    
+
      
+
    • Compare values using Python’s comparison operators
      • 
+
    • Combine comparisons using logical operators
      • 
+
    • Make decisions based on multiple criteria
      • 
+
    
+
    These skills are useful not just for hiring decisions, but for any situation where you need to make choices based on multiple conditions, especially in the context of optimal stopping problems!
    
+
    
+
    
+
    
+
    Solutions
    
+
    You will likely find solutions to most exercises online. However, we strongly encourage you to work on these exercises independently without searching explicitly for the exact answers to the exercises. Understanding someone else’s solution is very different from developing your own. Use the lecture notes and try to solve the exercises on your own. This approach will significantly enhance your learning and problem-solving skills.
    
+
    Remember, the goal is not just to complete the exercises, but to understand the concepts and improve your programming abilities. If you encounter difficulties, review the lecture materials, experiment with different approaches, and don’t hesitate to ask for clarification during class discussions.
    
+
    Later, you will find the solutions to these exercises online in the associated GitHub repository, but we will also quickly go over them next week. To access the solutions, click on the Github button on the lower right and search for the folder with today’s lecture and tutorial. Alternatively, you can ask ChatGPT or Claude to explain them to you. But please remember, the goal is not just to complete the exercises, but to understand the concepts and improve your programming abilities.
    
+
    Continue to the next tutorial to learn how to apply these skills to the optimal stopping problem!
    
+
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+
    
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\ No newline at end of file
diff --git a/part-01/tutorial-02-comparisons 3.ipynb b/part-01/tutorial-02-comparisons 3.ipynb
new file mode 100644
index 0000000..99ffb8e
--- /dev/null
+++ b/part-01/tutorial-02-comparisons 3.ipynb	
@@ -0,0 +1,564 @@
+{
+  "cells": [
+    {
+      "cell_type": "markdown",
+      "metadata": {},
+      "source": [
+        "# Tutorial I.II - Comparison Operators\n",
+        "\n",
+        "Programming: Everyday Decision-Making Algorithms\n",
+        "\n",
+        "# Introduction\n",
+        "\n",
+        "You’re teaching a computer to make decisions. Just like we compare\n",
+        "things in everyday life (“Is it raining?”, “Do I have enough money?”),\n",
+        "computers need ways to compare values and make choices. Let’s look at\n",
+        "this in the context of hiring decisions to help us how to make decisions\n",
+        "in the context of optimal stopping problems.\n",
+        "\n",
+        "Imagine you’re helping a company make hiring decisions. You need to look\n",
+        "at different candidates and decide if they meet certain requirements. To\n",
+        "make these decisions with Python, we need to learn how to make\n",
+        "comparisons!\n",
+        "\n",
+        "# 1 - Basic Comparisons\n",
+        "\n",
+        "When looking at job candidates, we often ask questions like:\n",
+        "\n",
+        "-   Does the candidate have enough experience?\n",
+        "-   Is their salary request within our budget?\n",
+        "-   Did they score well on the test?\n",
+        "\n",
+        "These questions all require yes/no (`True/False`) answers, which is\n",
+        "exactly what comparison operators give us in Python. Each comparison\n",
+        "will result in either `True` or `False`.\n",
+        "\n",
+        "In Python, we use special symbols to make these comparisons:"
+      ],
+      "id": "a9cb3435-539d-40de-89e5-19db6c813d00"
+    },
+    {
+      "cell_type": "code",
+      "execution_count": 1,
+      "metadata": {},
+      "outputs": [
+        {
+          "output_type": "stream",
+          "name": "stdout",
+          "text": [
+            "Is this our best candidate so far? True\n",
+            "Have we passed our optimal stopping threshold? True"
+          ]
+        }
+      ],
+      "source": [
+        "# Let's look at the current candidate compared to the best we've seen so far\n",
+        "current_candidate_score = 85\n",
+        "best_score_so_far = 82\n",
+        "\n",
+        "# Is this the best candidate yet?\n",
+        "is_best_so_far = (current_candidate_score > best_score_so_far)\n",
+        "print(f\"Is this our best candidate so far? {is_best_so_far}\")\n",
+        "\n",
+        "# Have we interviewed enough candidates?\n",
+        "candidates_seen = 15\n",
+        "total_candidates = 30\n",
+        "passed_threshold = (candidates_seen >= total_candidates * 0.37)\n",
+        "print(f\"Have we passed our optimal stopping threshold? {passed_threshold}\")"
+      ],
+      "id": "8b1b3457"
+    },
+    {
+      "cell_type": "markdown",
+      "metadata": {},
+      "source": [
+        "> **Tip**\n",
+        ">\n",
+        "> When you make a comparison in Python, the result is always a boolean\n",
+        "> value (`True` or `False`). This is why we can store the result in\n",
+        "> variables like `is_best_so_far` - these variables will contain either\n",
+        "> `True` or `False`.\n",
+        "\n",
+        "Here are all the comparison operators we can use:\n",
+        "\n",
+        "| Symbol | Meaning                  | Example                        |\n",
+        "|--------|--------------------------|--------------------------------|\n",
+        "| `==`   | Equal to                 | `score == 100`                 |\n",
+        "| `!=`   | Not equal to             | `degree != \"Computer Science\"` |\n",
+        "| `<`    | Less than                | `salary < 80000`               |\n",
+        "| `>`    | Greater than             | `experience > 5`               |\n",
+        "| `<=`   | Less than or equal to    | `age <= 65`                    |\n",
+        "| `>=`   | Greater than or equal to | `test_score >= 80`             |\n",
+        "\n",
+        "## Exercise 1.1 - Compare Test Scores\n",
+        "\n",
+        "A candidate scored 95 on their test. The previous highest score was 88.\n",
+        "Create a comparison to check if the new score is better and store the\n",
+        "result in `compare_scores`."
+      ],
+      "id": "8588140c-fd3e-41b4-b1d3-203ee12412f8"
+    },
+    {
+      "cell_type": "code",
+      "execution_count": 2,
+      "metadata": {},
+      "outputs": [],
+      "source": [
+        "# Creates the variables\n",
+        "new_score = 95\n",
+        "previous_best = 88\n",
+        "# YOUR CODE BELOW"
+      ],
+      "id": "1d8d811f"
+    },
+    {
+      "cell_type": "code",
+      "execution_count": 3,
+      "metadata": {},
+      "outputs": [],
+      "source": [
+        "# Test your answer\n",
+        "assert compare_scores == True, \"The new score should be greater than the previous best\"\n",
+        "print(f\"Is new score better? {compare_scores}\")"
+      ],
+      "id": "1ee2bf9f"
+    },
+    {
+      "cell_type": "markdown",
+      "metadata": {},
+      "source": [
+        "## Exercise 1.2 - Compare Skills\n",
+        "\n",
+        "Check if a candidate’s skill matches what we need. Compare if the\n",
+        "following two variables are different and store the result in\n",
+        "`compare_skills`."
+      ],
+      "id": "787c4eeb-6fa9-437c-a889-cad80edb64d4"
+    },
+    {
+      "cell_type": "code",
+      "execution_count": 4,
+      "metadata": {},
+      "outputs": [],
+      "source": [
+        "candidate_skill = \"Finance\"\n",
+        "required_skill = \"Python\"\n",
+        "# YOUR CODE BELOW"
+      ],
+      "id": "eb6d8742"
+    },
+    {
+      "cell_type": "code",
+      "execution_count": 5,
+      "metadata": {},
+      "outputs": [],
+      "source": [
+        "# Test your answer\n",
+        "assert compare_skills == False, \"The candidate's skill should not match the required skill\"\n",
+        "print(\"Good job! You correctly identified that the skills are different\")"
+      ],
+      "id": "ec0f0201"
+    },
+    {
+      "cell_type": "markdown",
+      "metadata": {},
+      "source": [
+        "## Exercise 1.3 - Compare Candidates\n",
+        "\n",
+        "In the secretary problem, we need to compare candidates to the best\n",
+        "we’ve seen. Check if the current candidate is better than our best so\n",
+        "far and store the result in `is_better`."
+      ],
+      "id": "09c2b9d3-da9f-4cf5-b3d4-261e523c1920"
+    },
+    {
+      "cell_type": "code",
+      "execution_count": 6,
+      "metadata": {},
+      "outputs": [],
+      "source": [
+        "current_rating = 92\n",
+        "best_so_far = 88\n",
+        "# YOUR CODE BELOW"
+      ],
+      "id": "04e9d25c"
+    },
+    {
+      "cell_type": "code",
+      "execution_count": 7,
+      "metadata": {},
+      "outputs": [],
+      "source": [
+        "# Test your answer\n",
+        "assert is_better == True, \"The current candidate should be better than the best so far\"\n",
+        "print(\"Good job! You correctly identified that the current candidate is better than the best so far\")"
+      ],
+      "id": "7f751cb4"
+    },
+    {
+      "cell_type": "markdown",
+      "metadata": {},
+      "source": [
+        "# 2 - Combining Comparisons with Logical Operators\n",
+        "\n",
+        "Often, we need to check multiple things at once. For example, a good\n",
+        "candidate should:\n",
+        "\n",
+        "-   Have enough experience\n",
+        "-   Be within our budget\n",
+        "-   Pass the test\n",
+        "\n",
+        "Python gives us three ways to combine comparisons:\n",
+        "\n",
+        "-   `and`: Both conditions must be true\n",
+        "-   `or`: At least one condition must be true\n",
+        "-   `not`: Makes true become false and false become true\n",
+        "\n",
+        "Let’s see some examples:"
+      ],
+      "id": "5da4ab8b-3117-4103-a4ab-a29bcf890eb6"
+    },
+    {
+      "cell_type": "code",
+      "execution_count": 8,
+      "metadata": {},
+      "outputs": [
+        {
+          "output_type": "stream",
+          "name": "stdout",
+          "text": [
+            "Should we hire this candidate? True\n",
+            "Is candidate qualified? True"
+          ]
+        }
+      ],
+      "source": [
+        "# Candidate information\n",
+        "experience = 5\n",
+        "test_score = 90\n",
+        "salary_ask = 75000\n",
+        "\n",
+        "# Check multiple requirements at once\n",
+        "meets_experience = (experience >= 3)\n",
+        "good_test_score = (test_score >= 85)\n",
+        "affordable = (salary_ask <= 80000)\n",
+        "\n",
+        "# All requirements must be met (using AND)\n",
+        "is_good_candidate = (meets_experience and good_test_score and affordable)\n",
+        "print(f\"Should we hire this candidate? {is_good_candidate}\")\n",
+        "\n",
+        "# Alternative qualifications (using OR)\n",
+        "has_degree = True\n",
+        "has_certification = False\n",
+        "is_qualified = (has_degree or has_certification)\n",
+        "print(f\"Is candidate qualified? {is_qualified}\")"
+      ],
+      "id": "c39cbfdb"
+    },
+    {
+      "cell_type": "markdown",
+      "metadata": {},
+      "source": [
+        "> **Important**\n",
+        ">\n",
+        "> Common Mistakes to Avoid:\n",
+        ">\n",
+        "> 1.  Don’t confuse `=` (assignment) with `==` (comparison)\n",
+        "> 2.  Remember that `and` requires ALL conditions to be True\n",
+        "> 3.  When combining multiple comparisons, use parentheses to make your\n",
+        ">     logic clear Example: `(experience >= 3) and (test_score >= 85)`\n",
+        "\n",
+        "## Exercise 2.1 - Check Multiple Requirements\n",
+        "\n",
+        "We have a candidate with:\n",
+        "\n",
+        "-   4 years of experience\n",
+        "-   Test score of 90\n",
+        "\n",
+        "Check if they meet BOTH requirements:\n",
+        "\n",
+        "-   More than 3 years experience\n",
+        "-   Test score above 85\n",
+        "\n",
+        "Store the result in `meets_requirements`."
+      ],
+      "id": "697094ca-1a60-43c7-a109-e572e8138191"
+    },
+    {
+      "cell_type": "code",
+      "execution_count": 9,
+      "metadata": {},
+      "outputs": [],
+      "source": [
+        "years = 4\n",
+        "score = 90\n",
+        "# YOUR CODE BELOW"
+      ],
+      "id": "a25c57b1"
+    },
+    {
+      "cell_type": "code",
+      "execution_count": 10,
+      "metadata": {},
+      "outputs": [],
+      "source": [
+        "# Test your answer\n",
+        "assert meets_requirements == True, \"The candidate should meet both requirements\"\n",
+        "print(\"Good job! You correctly identified that the candidate meets both requirements\")"
+      ],
+      "id": "8359c09d"
+    },
+    {
+      "cell_type": "markdown",
+      "metadata": {},
+      "source": [
+        "## Exercise 2.2 - Alternative Requirements\n",
+        "\n",
+        "A candidate is acceptable if they EITHER:\n",
+        "\n",
+        "-   Have a PhD\n",
+        "-   OR have a high test score (above 95)\n",
+        "\n",
+        "Store the result in `is_qualified`"
+      ],
+      "id": "991b62ae-be2c-4236-ac6c-802794a3a7f4"
+    },
+    {
+      "cell_type": "code",
+      "execution_count": 11,
+      "metadata": {},
+      "outputs": [],
+      "source": [
+        "has_phd = True\n",
+        "test_score = 92\n",
+        "# YOUR CODE BELOW"
+      ],
+      "id": "d73aeeae"
+    },
+    {
+      "cell_type": "code",
+      "execution_count": 12,
+      "metadata": {},
+      "outputs": [],
+      "source": [
+        "# Test your answer\n",
+        "assert is_qualified == True, \"The candidate should be qualified\"\n",
+        "print(\"Good job! You correctly identified that the candidate is qualified\")"
+      ],
+      "id": "8bead000"
+    },
+    {
+      "cell_type": "markdown",
+      "metadata": {},
+      "source": [
+        "# 3 - Putting It All Together\n",
+        "\n",
+        "Let’s look at a real candidate and check all their qualifications:"
+      ],
+      "id": "64c12cde-fedf-4839-87c6-93aa1cf9fc8b"
+    },
+    {
+      "cell_type": "code",
+      "execution_count": 13,
+      "metadata": {},
+      "outputs": [
+        {
+          "output_type": "stream",
+          "name": "stdout",
+          "text": [
+            "Candidate: Mika\n",
+            "Passed observation threshold: True\n",
+            "Best candidate so far: True\n",
+            "Final decision - Should hire: True"
+          ]
+        }
+      ],
+      "source": [
+        "# Secretary Problem Scenario\n",
+        "candidate_name = \"Mika\"\n",
+        "candidates_seen = 25\n",
+        "total_candidates = 50\n",
+        "current_score = 88\n",
+        "best_score_so_far = 85\n",
+        "\n",
+        "# Our decision criteria\n",
+        "threshold_ratio = 0.37\n",
+        "passed_threshold = (candidates_seen >= total_candidates * threshold_ratio)\n",
+        "is_best_so_far = (current_score > best_score_so_far)\n",
+        "\n",
+        "# Final decision - must pass threshold AND be best so far\n",
+        "should_hire = (passed_threshold and is_best_so_far)\n",
+        "\n",
+        "print(f\"Candidate: {candidate_name}\")\n",
+        "print(f\"Passed observation threshold: {passed_threshold}\")\n",
+        "print(f\"Best candidate so far: {is_best_so_far}\")\n",
+        "print(f\"Final decision - Should hire: {should_hire}\")"
+      ],
+      "id": "50e261fd"
+    },
+    {
+      "cell_type": "markdown",
+      "metadata": {},
+      "source": [
+        "## Exercise 3.1 - Make a Hiring Decision\n",
+        "\n",
+        "Look at the following candidate’s information and decide if we should\n",
+        "hire them:\n",
+        "\n",
+        "Requirements:\n",
+        "\n",
+        "-   At least 5 years experience\n",
+        "-   Test score above 85\n",
+        "-   Salary request at most 90000\n",
+        "-   Must have a degree\n",
+        "\n",
+        "Create a single boolean expression that checks ALL requirements and\n",
+        "store the result in `final_decision`."
+      ],
+      "id": "362bb3ff-2550-42f8-8425-ae049094450d"
+    },
+    {
+      "cell_type": "code",
+      "execution_count": 14,
+      "metadata": {},
+      "outputs": [],
+      "source": [
+        "# Candidate information\n",
+        "candidate_experience = 7\n",
+        "candidate_score = 89\n",
+        "candidate_salary = 92000\n",
+        "candidate_has_degree = True\n",
+        "# YOUR CODE BELOW"
+      ],
+      "id": "56309c4e"
+    },
+    {
+      "cell_type": "code",
+      "execution_count": 15,
+      "metadata": {},
+      "outputs": [],
+      "source": [
+        "# Test your answer\n",
+        "assert final_decision == False, \"The candidate should not meet all requirements\"\n",
+        "print(\"Good job! You correctly identified that the candidate does not meet all requirements as his salary expectation is too high.\")"
+      ],
+      "id": "0ea4ae6f"
+    },
+    {
+      "cell_type": "markdown",
+      "metadata": {},
+      "source": [
+        "## Exercise 2.3 - Optimal Stopping Decision\n",
+        "\n",
+        "We have:\n",
+        "\n",
+        "-   Seen 18 out of 40 candidates\n",
+        "-   Current candidate score: 90\n",
+        "-   Best score so far: 85\n",
+        "\n",
+        "Check if we should hire this candidate (we should hire if we’ve seen at\n",
+        "least 37% of candidates AND this candidate is better than the best so\n",
+        "far).\n",
+        "\n",
+        "Store the result in `make_offer`."
+      ],
+      "id": "8b845382-73bb-4ee5-bb26-ca13aa3908e7"
+    },
+    {
+      "cell_type": "code",
+      "execution_count": 16,
+      "metadata": {},
+      "outputs": [],
+      "source": [
+        "# Candidate information\n",
+        "candidates_seen = 18\n",
+        "total_candidates = 40\n",
+        "current_score = 90\n",
+        "best_score_so_far = 85\n",
+        "# YOUR CODE BELOW"
+      ],
+      "id": "e7d37b1c"
+    },
+    {
+      "cell_type": "code",
+      "execution_count": 17,
+      "metadata": {},
+      "outputs": [],
+      "source": [
+        "# Test your answer\n",
+        "assert make_offer == True, \"We should hire this candidate\"\n",
+        "print(\"Good job! You correctly identified that we should hire this candidate\")"
+      ],
+      "id": "4309d734"
+    },
+    {
+      "cell_type": "markdown",
+      "metadata": {},
+      "source": [
+        "# Conclusion\n",
+        "\n",
+        "Great job! You now know how to:\n",
+        "\n",
+        "-   Compare values using Python’s comparison operators\n",
+        "-   Combine comparisons using logical operators\n",
+        "-   Make decisions based on multiple criteria\n",
+        "\n",
+        "These skills are useful not just for hiring decisions, but for any\n",
+        "situation where you need to make choices based on multiple conditions,\n",
+        "especially in the context of optimal stopping problems!\n",
+        "\n",
+        "------------------------------------------------------------------------\n",
+        "\n",
+        "# Solutions\n",
+        "\n",
+        "You will likely find solutions to most exercises online. However, we\n",
+        "strongly encourage you to work on these exercises independently without\n",
+        "searching explicitly for the exact answers to the exercises.\n",
+        "Understanding someone else’s solution is very different from developing\n",
+        "your own. Use the lecture notes and try to solve the exercises on your\n",
+        "own. This approach will significantly enhance your learning and\n",
+        "problem-solving skills.\n",
+        "\n",
+        "Remember, the goal is not just to complete the exercises, but to\n",
+        "understand the concepts and improve your programming abilities. If you\n",
+        "encounter difficulties, review the lecture materials, experiment with\n",
+        "different approaches, and don’t hesitate to ask for clarification during\n",
+        "class discussions.\n",
+        "\n",
+        "Later, you will find the solutions to these exercises online in the\n",
+        "associated GitHub repository, but we will also quickly go over them next\n",
+        "week. To access the solutions, click on the Github button on the lower\n",
+        "right and search for the folder with today’s lecture and tutorial.\n",
+        "Alternatively, you can ask ChatGPT or Claude to explain them to you. But\n",
+        "please remember, the goal is not just to complete the exercises, but to\n",
+        "understand the concepts and improve your programming abilities.\n",
+        "\n",
+        "*Continue to the next tutorial to learn how to apply these skills to the\n",
+        "optimal stopping problem!*"
+      ],
+      "id": "e31cb665-7614-46e0-a22c-03896b568bf8"
+    }
+  ],
+  "nbformat": 4,
+  "nbformat_minor": 5,
+  "metadata": {
+    "kernelspec": {
+      "name": "python3",
+      "display_name": "Python 3 (ipykernel)",
+      "language": "python",
+      "path": "/Users/tvlcek/miniconda3/share/jupyter/kernels/python3"
+    },
+    "language_info": {
+      "name": "python",
+      "codemirror_mode": {
+        "name": "ipython",
+        "version": "3"
+      },
+      "file_extension": ".py",
+      "mimetype": "text/x-python",
+      "nbconvert_exporter": "python",
+      "pygments_lexer": "ipython3",
+      "version": "3.12.7"
+    }
+  }
+}
\ No newline at end of file
diff --git a/part-01/tutorial-02-comparisons 3.pdf b/part-01/tutorial-02-comparisons 3.pdf
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zgG4a-S@K@M)j?Ui=;2Ww@LmMlMFlIcICnB9I*k
  06 - Exploration
   
    
+
+      
+  
+        
  • 
+      
     
+            
+           
+      
    
+      
   
    • 
@@ -314,7 +349,7 @@ 
    1 - Basic Comparisons
    
 
 
    These questions all require yes/no (True/False) answers, which is exactly what comparison operators give us in Python. Each comparison will result in either True or False.
    
 
    In Python, we use special symbols to make these comparisons:
    
-
    
+
    
 
    # Let's look at the current candidate compared to the best we've seen so far
 current_candidate_score = 85
 best_score_so_far = 82
@@ -391,13 +426,13 @@ 
    1 - Basic Comparisons
    
 
    
 
    Exercise 1.1 - Compare Test Scores
    
 
    A candidate scored 95 on their test. The previous highest score was 88. Create a comparison to check if the new score is better and store the result in compare_scores.
    
-
    
+
    
 
    # Creates the variables
 new_score = 95
 previous_best = 88
 # YOUR CODE BELOW
    
 
    
-
    
+
    
 
    
 Code
 
    # Test your answer
@@ -409,12 +444,12 @@ 
    Exercis
 
    
 
    Exercise 1.2 - Compare Skills
    
 
    Check if a candidate’s skill matches what we need. Compare if the following two variables are different and store the result in compare_skills.
    
-
    
+
    
 
    candidate_skill = "Finance"
 required_skill = "Python"
 # YOUR CODE BELOW
    
 
    
-
    
+
    
 
    
 Code
 
    # Test your answer
@@ -426,12 +461,12 @@ 
    Exercise 1.2
 
    
 
    Exercise 1.3 - Compare Candidates
    
 
    In the secretary problem, we need to compare candidates to the best we’ve seen. Check if the current candidate is better than our best so far and store the result in is_better.
    
-
    
+
    
 
    current_rating = 92
 best_so_far = 88
 # YOUR CODE BELOW
    
 
    
-
    
+
    
 
    
 Code
 
    # Test your answer
@@ -456,7 +491,7 @@ 
    2 - Combining Comparisons with Logical Operators
    
 
  • not: Makes true become false and false become true
    • 
 
 
    Let’s see some examples:
    
-
    
+
    
 
    # Candidate information
 experience = 5
 test_score = 90
@@ -512,12 +547,12 @@ 
    Test score above 85
 
 
    Store the result in meets_requirements.
    
-
    
+
    
 
    years = 4
 score = 90
 # YOUR CODE BELOW
    
 
    
-
    
+
    
 
    
 Code
 
    # Test your answer
@@ -534,12 +569,12 @@ 
    Ex
 
  • OR have a high test score (above 95)
    • 
 
 
    Store the result in is_qualified
    
-
    
+
    
 
    has_phd = True
 test_score = 92
 # YOUR CODE BELOW
    
 
    
-
    
+
    
 
    
 Code
 
    # Test your answer
@@ -552,7 +587,7 @@ 
    Ex
 
    
 
    3 - Putting It All Together
    
 
    Let’s look at a real candidate and check all their qualifications:
    
-
    
+
    
 
    # Secretary Problem Scenario
 candidate_name = "Mika"
 candidates_seen = 25
@@ -590,7 +625,7 @@ 
    Exer
 
  • Must have a degree
    • 
 
 
    Create a single boolean expression that checks ALL requirements and store the result in final_decision.
    
-
    
+
    
 
    # Candidate information
 candidate_experience = 7
 candidate_score = 89
@@ -598,7 +633,7 @@ 
    Exer
 candidate_has_degree = True
 # YOUR CODE BELOW
    
 
    
-
    
+
    
 
    
 Code
 
    # Test your answer
@@ -617,7 +652,7 @@ 
    E
 
 
    Check if we should hire this candidate (we should hire if we’ve seen at least 37% of candidates AND this candidate is better than the best so far).
    
 
    Store the result in make_offer.
    
-
    
+
    
 
    # Candidate information
 candidates_seen = 18
 total_candidates = 40
@@ -625,7 +660,7 @@ 
    E
 best_score_so_far = 85
 # YOUR CODE BELOW
    
 
    
-
    
+
    
 
    
 Code
 
    # Test your answer
diff --git a/part-01/tutorial-02-comparisons.ipynb b/part-01/tutorial-02-comparisons.ipynb
index 96d7b53..fed30ab 100644
--- a/part-01/tutorial-02-comparisons.ipynb
+++ b/part-01/tutorial-02-comparisons.ipynb
@@ -35,7 +35,7 @@
         "\n",
         "In Python, we use special symbols to make these comparisons:"
       ],
-      "id": "e5ee62c1-08b9-4cf2-97db-acdb63690ea6"
+      "id": "04649bc1-523a-4f4c-a0a4-bc4fd3ccae6d"
     },
     {
       "cell_type": "code",
@@ -66,7 +66,7 @@
         "passed_threshold = (candidates_seen >= total_candidates * 0.37)\n",
         "print(f\"Have we passed our optimal stopping threshold? {passed_threshold}\")"
       ],
-      "id": "b1771d02"
+      "id": "dd9abbf1"
     },
     {
       "cell_type": "markdown",
@@ -96,7 +96,7 @@
         "Create a comparison to check if the new score is better and store the\n",
         "result in `compare_scores`."
       ],
-      "id": "ee1ae40d-c3af-4ca6-a8f6-b531c511e7ab"
+      "id": "2df47eeb-adf5-410f-a474-84b2c1c5b618"
     },
     {
       "cell_type": "code",
@@ -109,7 +109,7 @@
         "previous_best = 88\n",
         "# YOUR CODE BELOW"
       ],
-      "id": "d1f1f2fd"
+      "id": "1fd8bf01"
     },
     {
       "cell_type": "code",
@@ -121,7 +121,7 @@
         "assert compare_scores == True, \"The new score should be greater than the previous best\"\n",
         "print(f\"Is new score better? {compare_scores}\")"
       ],
-      "id": "8fbe9ee5"
+      "id": "bf29702d"
     },
     {
       "cell_type": "markdown",
@@ -133,7 +133,7 @@
         "following two variables are different and store the result in\n",
         "`compare_skills`."
       ],
-      "id": "50928248-022f-4afc-904c-b13900bf8b38"
+      "id": "09a7b8e0-81ab-48db-9036-c95dbb63b9bb"
     },
     {
       "cell_type": "code",
@@ -145,7 +145,7 @@
         "required_skill = \"Python\"\n",
         "# YOUR CODE BELOW"
       ],
-      "id": "5513160a"
+      "id": "9ee91a02"
     },
     {
       "cell_type": "code",
@@ -157,7 +157,7 @@
         "assert compare_skills == False, \"The candidate's skill should not match the required skill\"\n",
         "print(\"Good job! You correctly identified that the skills are different\")"
       ],
-      "id": "e3c03ff4"
+      "id": "6dacbaa1"
     },
     {
       "cell_type": "markdown",
@@ -169,7 +169,7 @@
         "we’ve seen. Check if the current candidate is better than our best so\n",
         "far and store the result in `is_better`."
       ],
-      "id": "60261e0b-97c2-4159-8f36-d0408d0d0b8d"
+      "id": "3a1b7c2f-82aa-4562-b5a4-18f2dca32b2a"
     },
     {
       "cell_type": "code",
@@ -181,7 +181,7 @@
         "best_so_far = 88\n",
         "# YOUR CODE BELOW"
       ],
-      "id": "20cb8087"
+      "id": "0086fc04"
     },
     {
       "cell_type": "code",
@@ -193,7 +193,7 @@
         "assert is_better == True, \"The current candidate should be better than the best so far\"\n",
         "print(\"Good job! You correctly identified that the current candidate is better than the best so far\")"
       ],
-      "id": "33d69ba0"
+      "id": "37d036a8"
     },
     {
       "cell_type": "markdown",
@@ -216,7 +216,7 @@
         "\n",
         "Let’s see some examples:"
       ],
-      "id": "d53a859d-c7d7-4522-b9f4-65ec30043ea2"
+      "id": "253320ad-02bb-4da8-a710-5a0d670319cb"
     },
     {
       "cell_type": "code",
@@ -253,7 +253,7 @@
         "is_qualified = (has_degree or has_certification)\n",
         "print(f\"Is candidate qualified? {is_qualified}\")"
       ],
-      "id": "b12f717f"
+      "id": "69325af3"
     },
     {
       "cell_type": "markdown",
@@ -282,7 +282,7 @@
         "\n",
         "Store the result in `meets_requirements`."
       ],
-      "id": "837357db-34db-4bc3-94a0-b4c49656c0fb"
+      "id": "cac50fe2-289b-4c9d-bdea-6359c748b5dd"
     },
     {
       "cell_type": "code",
@@ -294,7 +294,7 @@
         "score = 90\n",
         "# YOUR CODE BELOW"
       ],
-      "id": "b18e6cd3"
+      "id": "d11bdf32"
     },
     {
       "cell_type": "code",
@@ -306,7 +306,7 @@
         "assert meets_requirements == True, \"The candidate should meet both requirements\"\n",
         "print(\"Good job! You correctly identified that the candidate meets both requirements\")"
       ],
-      "id": "75af109d"
+      "id": "6716cf66"
     },
     {
       "cell_type": "markdown",
@@ -321,7 +321,7 @@
         "\n",
         "Store the result in `is_qualified`"
       ],
-      "id": "2037d6e2-600e-48c6-8970-c074cbdbca01"
+      "id": "0302b602-8090-4e04-b4fb-6a7490fa2429"
     },
     {
       "cell_type": "code",
@@ -333,7 +333,7 @@
         "test_score = 92\n",
         "# YOUR CODE BELOW"
       ],
-      "id": "5172a968"
+      "id": "7b43da2e"
     },
     {
       "cell_type": "code",
@@ -345,7 +345,7 @@
         "assert is_qualified == True, \"The candidate should be qualified\"\n",
         "print(\"Good job! You correctly identified that the candidate is qualified\")"
       ],
-      "id": "9088716b"
+      "id": "3c82e17a"
     },
     {
       "cell_type": "markdown",
@@ -355,7 +355,7 @@
         "\n",
         "Let’s look at a real candidate and check all their qualifications:"
       ],
-      "id": "7c21d6b1-ced1-4081-bf41-d968c955fe30"
+      "id": "9c370776-8779-4cdf-91f7-7421b760ae2f"
     },
     {
       "cell_type": "code",
@@ -394,7 +394,7 @@
         "print(f\"Best candidate so far: {is_best_so_far}\")\n",
         "print(f\"Final decision - Should hire: {should_hire}\")"
       ],
-      "id": "c4504a16"
+      "id": "f0f25a9b"
     },
     {
       "cell_type": "markdown",
@@ -415,7 +415,7 @@
         "Create a single boolean expression that checks ALL requirements and\n",
         "store the result in `final_decision`."
       ],
-      "id": "5148a399-161a-481c-8de3-13248628b81d"
+      "id": "b464b79b-18db-4e7c-b582-81d57158490e"
     },
     {
       "cell_type": "code",
@@ -430,7 +430,7 @@
         "candidate_has_degree = True\n",
         "# YOUR CODE BELOW"
       ],
-      "id": "8aab1588"
+      "id": "3ccc16e8"
     },
     {
       "cell_type": "code",
@@ -442,7 +442,7 @@
         "assert final_decision == False, \"The candidate should not meet all requirements\"\n",
         "print(\"Good job! You correctly identified that the candidate does not meet all requirements as his salary expectation is too high.\")"
       ],
-      "id": "bda0f075"
+      "id": "e646b5a6"
     },
     {
       "cell_type": "markdown",
@@ -462,7 +462,7 @@
         "\n",
         "Store the result in `make_offer`."
       ],
-      "id": "ff0a43a0-e1fa-4d5a-8075-95da2edd3eb6"
+      "id": "6e1219dc-3a9b-4b28-8577-8ade8a056cda"
     },
     {
       "cell_type": "code",
@@ -477,7 +477,7 @@
         "best_score_so_far = 85\n",
         "# YOUR CODE BELOW"
       ],
-      "id": "914dc2ea"
+      "id": "3cc6052a"
     },
     {
       "cell_type": "code",
@@ -489,7 +489,7 @@
         "assert make_offer == True, \"We should hire this candidate\"\n",
         "print(\"Good job! You correctly identified that we should hire this candidate\")"
       ],
-      "id": "2b362699"
+      "id": "c869a422"
     },
     {
       "cell_type": "markdown",
@@ -536,7 +536,7 @@
         "*Continue to the next tutorial to learn how to apply these skills to the\n",
         "optimal stopping problem!*"
       ],
-      "id": "db09074e-47e8-4f0f-8bb9-9742cc62558d"
+      "id": "a065221a-371b-4aa4-ad44-6a3b402f8b6c"
     }
   ],
   "nbformat": 4,
diff --git a/part-01/tutorial-02-comparisons.pdf b/part-01/tutorial-02-comparisons.pdf
index 00303a5a028b4f00120737b6294ec05f1a08a3b7..a68bd79b6b6b7bfcddda7cf3e6431b4721dc91ef 100644
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v)Vp_dE#{;>5!Oq0fah~ki$))dGASKi-=#T=wZrlT=+Fc(n3
+
+
+
+
+
+
+
+
+Tutorial I.III - Making Decisions – Programming: Everyday Decision-Making Algorithms
+
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+
    
+  
    
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+    
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+
    
+
    Tutorial I.III - Making Decisions
    
+
    Programming: Everyday Decision-Making Algorithms
    
+
    
+
+
+
+
    
+
+    
+  
+    
+  
    
+  
+
+
+
    
+
+
+
    
+
    Introduction
    
+
    Imagine you’re searching for a new apartment. You view a flat - should you take it or keep looking for something better? This is another classic optimal stopping problem! Just like in dating or hiring, you need to decide when to stop searching.
    
+
    In this tutorial, we’ll learn how computers make decisions using if and else statements. These are like the “if this, then that” decisions we make every day!
    
+
    
+
    
+
    1 - Understanding If Statements
    
+
    An if statement is like asking a yes/no question and doing something based on the answer. For example:
    
+
    
+
    flat_rating = 8  # Rate the flat from 0-10
+
+if flat_rating >= 7:
+    print("This is a good apartment!")
    
+
    
+
    This is a good apartment!
    
+
    
+
    
+
    The structure is:
    
+
      
+
    1. The word if
      2. 
+
    2. A condition that’s either True or False
      3. 
+
    3. A colon :
      4. 
+
    4. Indented code that runs if the condition is True
      5. 
+
    
+
    
+
    
+
    
+
+
    
+
    
+Tip
+
    
+
    
+
    
+
    Think of if statements like everyday decisions:
    
+
      
+
    • IF it’s within budget, view it
      • 
+
    • IF the flat is good, apply for it
      • 
+
    • IF it has enough rooms, add it to the shortlist
      • 
+
    
+
    Computer if statements work exactly the same way! They check a condition and then do something based on that check.
    
+
    
+
    
+
    
+
    
+
    
+
+
    
+
    
+Important
+
    
+
    
+
    
+
    Common Mistakes with If Statements:
    
+
      
+
    1. Forgetting the colon : after the condition
      2. 
+
    2. Incorrect indentation of the code block
      3. 
+
    3. Using = (assignment) instead of == (comparison)
      4. 
+
    4. Forgetting that the condition must result in True or False
      5. 
+
    
+
    
+
    
+
    
+
    Exercise 1.1 - Your First Decision
    
+
    Create an if statement that prints “Perfect flat!” if the flat_rating is 10.
    
+
    
+
    flat_rating = 10
+# YOUR CODE BELOW
+
+# Test your answer yourself - the cell should print "Perfect flat!" if executed correctly
    
+
    
+
    
+
    
+
    
+
    2 - Adding Else Statements
    
+
    But what if we want to do something different when the condition is False? That’s where else comes in:
    
+
    
+
    flat_rating = 4  # Not a great flat!
+
+if flat_rating >= 7:
+    print("Apply for this flat!")
+else:
+    print("Keep searching!")
    
+
    
+
    Keep searching!
    
+
    
+
    
+
    The structure is:
    
+
      
+
    1. An if statement with its condition
      2. 
+
    2. Code to run if True
      3. 
+
    3. The word else and a colon :
      4. 
+
    4. Indented code to run if False
      5. 
+
    
+
    
+
    
+
    
+
+
    
+
    
+Tip
+
    
+
    
+
    
+
    Think of if-else like complete either/or decisions:
    
+
      
+
    • IF it’s within budget, schedule viewing, ELSE skip it
      • 
+
    • IF the location is good, consider it, ELSE keep searching
      • 
+
    • IF all criteria are met, apply now, ELSE continue looking
      • 
+
    
+
    The else statement is our backup plan!
    
+
    
+
    
+
    
+
    Exercise 2.1 - Complete Decision
    
+
    Write an if-else statement that sets decision to “Apply now” if flat_rating is at least 7, and “Keep searching” otherwise.
    
+
    
+
    flat_rating = 6
+decision = ""
+# YOUR CODE BELOW
    
+
    
+
    
+
    
+Code
+
    # Test your answer
+assert decision == "Keep searching", "The decision should be 'Keep searching' as the flat rating is less than 7"
+print(f"Decision: {decision} as the flat rating is {flat_rating}")
    
+
    
+
    
+
    
+
    
+
    
+
+
    
+
    
+Tip
+
    
+
    
+
    
+
    Writing Better If-Else Statements:
    
+
      
+
    1. Keep your conditions simple and readable
      2. 
+
    2. Use meaningful variable names
      3. 
+
    3. Consider what should happen in both cases
      4. 
+
    4. Test both paths to make sure they work
      5. 
+
    
+
    
+
    
+
    
+
    
+
    
+
    3 - Adding Elif (Else If)
    
+
    Sometimes we need more than two options. That’s where elif comes in:
    
+
    
+
    flat_rating = 8
+
+if flat_rating >= 9:
+    print("Amazing flat - apply immediately!")
+elif flat_rating >= 7:
+    print("Good flat - consider applying")
+elif flat_rating >= 5:
+    print("Mediocre flat - keep it as backup")
+else:
+    print("Poor flat - definitely keep looking")
    
+
    
+
    Good flat - consider applying
    
+
    
+
    
+
    The structure adds:
    
+
      
+
    • Multiple elif conditions between if and else
      • 
+
    • Each condition is checked in order
      • 
+
    • The first True condition runs its code
      • 
+
    
+
    
+
    
+
    
+
+
    
+
    
+Tip
+
    
+
    
+
    
+
    Think of elif like multiple-choice decisions:
    
+
      
+
    • IF it’s perfect → apply immediately
      • 
+
    • ELIF it’s good → schedule second viewing
      • 
+
    • ELIF it’s okay → keep as backup
      • 
+
    • ELSE → continue searching
      • 
+
    
+
    It’s like a flowchart where only one path can be taken!
    
+
    
+
    
+
    
+
    
+
    
+
+
    
+
    
+Warning
+
    
+
    
+
    
+
    Important Elif Rules:
    
+
      
+
    1. Order matters! Put more specific conditions first
      2. 
+
    2. Only one block will execute
      3. 
+
    3. elif must come after if and before else
      4. 
+
    4. You can have as many elif blocks as you need
      5. 
+
    
+
    
+
    
+
    
+
    Exercise 3.1 - Apartment Categories
    
+
    Create a variable flat_category that is:
    
+
      
+
    • “Luxury” if rating is 9 or 10
      • 
+
    • “Premium” if rating is 7 or 8
      • 
+
    • “Standard” if rating is 5 or 6
      • 
+
    • “Basic” for anything lower
      • 
+
    
+
    
+
    flat_rating = 8
+flat_category = ""
+# YOUR CODE BELOW
    
+
    
+
    
+
    
+Code
+
    # Test your answer
+assert flat_category == "Premium", "The flat category should be 'Premium' as the flat rating is 8"
+print(f"Flat Category: {flat_category} as the flat rating is {flat_rating}")
    
+
    
+
    
+
    
+
    
+
    
+
    4 - Complex Decisions
    
+
    In real life, we often need to check multiple conditions at once. We can combine conditions using and and or:
    
+
    
+
    flat_rating = 8
+weeks_searching = 3
+max_search_time = 4
+
+if (flat_rating >= 7) and (weeks_searching < max_search_time):
+    print("Take this flat - it's good enough and we still have time!")
+elif (flat_rating >= 9) or (weeks_searching >= max_search_time):
+    print("Take this flat - either it's perfect or we're out of time!")
+else:
+    print("Keep looking!")
    
+
    
+
    Take this flat - it's good enough and we still have time!
    
+
    
+
    
+
    
+
    
+
    
+
+
    
+
    
+Tip
+
    
+
    
+
    
+
    Tips for Complex Conditions:
    
+
      
+
    • Use parentheses to make your logic clear
      • 
+
    • Break very complex conditions into smaller parts
      • 
+
    • Test edge cases to make sure your logic works
      • 
+
    
+
    
+
    
+
    
+
    Exercise 4.1 - Real World Flat Hunting
    
+
    Create a variable should_apply that is True if:
    
+
      
+
    • The flat rating is at least 8, OR
      • 
+
    • The flat rating is at least 6 AND we’ve been searching for 3 weeks or more
      • 
+
    
+
    
+
    flat_rating = 6
+weeks_searching = 4
+should_apply = False
+# YOUR CODE BELOW
    
+
    
+
    
+
    
+Code
+
    # Test your answer
+assert should_apply == True, "The flat rating is 6 and we've been searching for 4 weeks, so we should apply"
+print(f"Should we apply? {should_apply} as the flat rating is {flat_rating} and we've been searching for {weeks_searching} weeks")
    
+
    
+
    
+
    
+
    
+
    
+
    5 - The 37% Rule with Decisions
    
+
    Remember the optimal stopping rule? Let’s apply it to apartment hunting:
    
+
    
+
    flats_seen = 6
+total_viewings = 15
+current_rating = 8
+best_rating_so_far = 7
+
+# Calculate if we've passed 37% of viewings
+threshold_passed = flats_seen >= (total_viewings * 0.37)
+
+if not threshold_passed:
+    print("Keep looking - still in observation phase")
+elif current_rating > best_rating_so_far:
+    print("Apply for this flat!")
+else:
+    print("Keep looking - waiting for better than our best")
    
+
    
+
    Apply for this flat!
    
+
    
+
    
+
    
+
    Exercise 5.1 - Implement the Rule
    
+
    Adjust the code below to change the variable make_application to True if:
    
+
      
+
    • We’ve seen at least 37% of available flats (use 15 total flats), AND
      • 
+
    • The current flat is better than the best we’ve seen so far
      • 
+
    
+
    
+
    flats_seen = 6  # We've seen 6 flats
+total_viewings = 15  # We plan to view 15 flats in total
+current_rating = 9
+best_rating_so_far = 8
+make_application = False
+# YOUR CODE BELOW
    
+
    
+
    
+
    
+Code
+
    # Test your answer
+assert make_application == True, "The flat rating is 9 and we've been searching for 4 weeks, so we should apply"
+print(f"Should we apply for this flat? {make_application}")
    
+
    
+
    
+
    
+
    
+
    
+
    Conclusion
    
+
    Great work! You’ve learned how to make decisions in Python using:
    
+
      
+
    • Simple if statements
      • 
+
    • if-else statements
      • 
+
    • elif for multiple conditions
      • 
+
    • Complex decisions with and/or
      • 
+
    • Applying these to real-world stopping problems
      • 
+
    
+
    Remember, just like in apartment hunting, these tools help us make better decisions in any situation where we need to decide whether to take what we have or keep looking for something better!
    
+
    
+
    
+
    
+
    Solutions
    
+
    You will likely find solutions to most exercises online. However, we strongly encourage you to work on these exercises independently without searching explicitly for the exact answers to the exercises. Understanding someone else’s solution is very different from developing your own. Use the lecture notes and try to solve the exercises on your own. This approach will significantly enhance your learning and problem-solving skills.
    
+
    Remember, the goal is not just to complete the exercises, but to understand the concepts and improve your programming abilities. If you encounter difficulties, review the lecture materials, experiment with different approaches, and don’t hesitate to ask for clarification during class discussions.
    
+
    Later, you will find the solutions to these exercises online in the associated GitHub repository, but we will also quickly go over them next week. To access the solutions, click on the Github button on the lower right and search for the folder with today’s lecture and tutorial. Alternatively, you can ask ChatGPT or Claude to explain them to you. But please remember, the goal is not just to complete the exercises, but to understand the concepts and improve your programming abilities.
    
+
    That’s it for part I! Next week, we’ll apply these skills exploration and exploitation!
    
+
+
+
    
+
+
     
+
+
     
+
+
+
+
+
+
\ No newline at end of file
diff --git a/part-01/tutorial-03-stopping 3.ipynb b/part-01/tutorial-03-stopping 3.ipynb
new file mode 100644
index 0000000..e7cce1b
--- /dev/null
+++ b/part-01/tutorial-03-stopping 3.ipynb	
@@ -0,0 +1,537 @@
+{
+  "cells": [
+    {
+      "cell_type": "markdown",
+      "metadata": {},
+      "source": [
+        "# Tutorial I.III - Making Decisions\n",
+        "\n",
+        "Programming: Everyday Decision-Making Algorithms\n",
+        "\n",
+        "# Introduction\n",
+        "\n",
+        "Imagine you’re searching for a new apartment. You view a flat - should\n",
+        "you take it or keep looking for something better? This is another\n",
+        "classic optimal stopping problem! Just like in dating or hiring, you\n",
+        "need to decide when to stop searching.\n",
+        "\n",
+        "In this tutorial, we’ll learn how computers make decisions using `if`\n",
+        "and `else` statements. These are like the “if this, then that” decisions\n",
+        "we make every day!\n",
+        "\n",
+        "# 1 - Understanding If Statements\n",
+        "\n",
+        "An `if` statement is like asking a yes/no question and doing something\n",
+        "based on the answer. For example:"
+      ],
+      "id": "4ee67a5e-8eee-423d-959c-5c54c27d5a38"
+    },
+    {
+      "cell_type": "code",
+      "execution_count": 1,
+      "metadata": {},
+      "outputs": [
+        {
+          "output_type": "stream",
+          "name": "stdout",
+          "text": [
+            "This is a good apartment!"
+          ]
+        }
+      ],
+      "source": [
+        "flat_rating = 8  # Rate the flat from 0-10\n",
+        "\n",
+        "if flat_rating >= 7:\n",
+        "    print(\"This is a good apartment!\")"
+      ],
+      "id": "46b2e117"
+    },
+    {
+      "cell_type": "markdown",
+      "metadata": {},
+      "source": [
+        "The structure is:\n",
+        "\n",
+        "1.  The word `if`\n",
+        "2.  A condition that’s either True or False\n",
+        "3.  A colon `:`\n",
+        "4.  **Indented** code that runs if the condition is True\n",
+        "\n",
+        "> **Tip**\n",
+        ">\n",
+        "> Think of `if` statements like everyday decisions:\n",
+        ">\n",
+        "> -   IF it’s within budget, view it\n",
+        "> -   IF the flat is good, apply for it\n",
+        "> -   IF it has enough rooms, add it to the shortlist\n",
+        ">\n",
+        "> Computer `if` statements work exactly the same way! They check a\n",
+        "> condition and then do something based on that check.\n",
+        "\n",
+        "> **Important**\n",
+        ">\n",
+        "> Common Mistakes with If Statements:\n",
+        ">\n",
+        "> 1.  Forgetting the colon `:` after the condition\n",
+        "> 2.  **Incorrect indentation** of the code block\n",
+        "> 3.  Using `=` (assignment) instead of `==` (comparison)\n",
+        "> 4.  Forgetting that the condition must result in `True` or `False`\n",
+        "\n",
+        "## Exercise 1.1 - Your First Decision\n",
+        "\n",
+        "Create an `if` statement that prints “Perfect flat!” if the\n",
+        "`flat_rating` is 10."
+      ],
+      "id": "b516b593-72c3-46ad-b433-f781ab3a05d1"
+    },
+    {
+      "cell_type": "code",
+      "execution_count": 2,
+      "metadata": {},
+      "outputs": [],
+      "source": [
+        "flat_rating = 10\n",
+        "# YOUR CODE BELOW\n",
+        "\n",
+        "# Test your answer yourself - the cell should print \"Perfect flat!\" if executed correctly"
+      ],
+      "id": "1fe49c70"
+    },
+    {
+      "cell_type": "markdown",
+      "metadata": {},
+      "source": [
+        "# 2 - Adding Else Statements\n",
+        "\n",
+        "But what if we want to do something different when the condition is\n",
+        "False? That’s where `else` comes in:"
+      ],
+      "id": "7a15a7db-f550-4858-8614-bdc98f9fe7b0"
+    },
+    {
+      "cell_type": "code",
+      "execution_count": 3,
+      "metadata": {},
+      "outputs": [
+        {
+          "output_type": "stream",
+          "name": "stdout",
+          "text": [
+            "Keep searching!"
+          ]
+        }
+      ],
+      "source": [
+        "flat_rating = 4  # Not a great flat!\n",
+        "\n",
+        "if flat_rating >= 7:\n",
+        "    print(\"Apply for this flat!\")\n",
+        "else:\n",
+        "    print(\"Keep searching!\")"
+      ],
+      "id": "877ec39e"
+    },
+    {
+      "cell_type": "markdown",
+      "metadata": {},
+      "source": [
+        "The structure is:\n",
+        "\n",
+        "1.  An `if` statement with its condition\n",
+        "2.  Code to run if True\n",
+        "3.  The word `else` and a colon `:`\n",
+        "4.  Indented code to run if False\n",
+        "\n",
+        "> **Tip**\n",
+        ">\n",
+        "> Think of `if-else` like complete either/or decisions:\n",
+        ">\n",
+        "> -   IF it’s within budget, schedule viewing, ELSE skip it\n",
+        "> -   IF the location is good, consider it, ELSE keep searching\n",
+        "> -   IF all criteria are met, apply now, ELSE continue looking\n",
+        ">\n",
+        "> The `else` statement is our backup plan!\n",
+        "\n",
+        "## Exercise 2.1 - Complete Decision\n",
+        "\n",
+        "Write an if-else statement that sets `decision` to “Apply now” if\n",
+        "`flat_rating` is at least 7, and “Keep searching” otherwise."
+      ],
+      "id": "cdb9ca1b-f25c-458d-ba46-7b83b92df1b8"
+    },
+    {
+      "cell_type": "code",
+      "execution_count": 4,
+      "metadata": {},
+      "outputs": [],
+      "source": [
+        "flat_rating = 6\n",
+        "decision = \"\"\n",
+        "# YOUR CODE BELOW"
+      ],
+      "id": "c466a4c6"
+    },
+    {
+      "cell_type": "code",
+      "execution_count": 5,
+      "metadata": {},
+      "outputs": [],
+      "source": [
+        "# Test your answer\n",
+        "assert decision == \"Keep searching\", \"The decision should be 'Keep searching' as the flat rating is less than 7\"\n",
+        "print(f\"Decision: {decision} as the flat rating is {flat_rating}\")"
+      ],
+      "id": "3d6e8b5b"
+    },
+    {
+      "cell_type": "markdown",
+      "metadata": {},
+      "source": [
+        "> **Tip**\n",
+        ">\n",
+        "> Writing Better If-Else Statements:\n",
+        ">\n",
+        "> 1.  Keep your conditions simple and readable\n",
+        "> 2.  Use meaningful variable names\n",
+        "> 3.  Consider what should happen in both cases\n",
+        "> 4.  Test both paths to make sure they work\n",
+        "\n",
+        "# 3 - Adding Elif (Else If)\n",
+        "\n",
+        "Sometimes we need more than two options. That’s where `elif` comes in:"
+      ],
+      "id": "91c06d4e-b4fb-4c04-8f10-9cd7a2a5cca6"
+    },
+    {
+      "cell_type": "code",
+      "execution_count": 6,
+      "metadata": {},
+      "outputs": [
+        {
+          "output_type": "stream",
+          "name": "stdout",
+          "text": [
+            "Good flat - consider applying"
+          ]
+        }
+      ],
+      "source": [
+        "flat_rating = 8\n",
+        "\n",
+        "if flat_rating >= 9:\n",
+        "    print(\"Amazing flat - apply immediately!\")\n",
+        "elif flat_rating >= 7:\n",
+        "    print(\"Good flat - consider applying\")\n",
+        "elif flat_rating >= 5:\n",
+        "    print(\"Mediocre flat - keep it as backup\")\n",
+        "else:\n",
+        "    print(\"Poor flat - definitely keep looking\")"
+      ],
+      "id": "0f322fb0"
+    },
+    {
+      "cell_type": "markdown",
+      "metadata": {},
+      "source": [
+        "The structure adds:\n",
+        "\n",
+        "-   Multiple `elif` conditions between `if` and `else`\n",
+        "-   Each condition is checked in order\n",
+        "-   The first True condition runs its code\n",
+        "\n",
+        "> **Tip**\n",
+        ">\n",
+        "> Think of `elif` like multiple-choice decisions:\n",
+        ">\n",
+        "> -   IF it’s perfect → apply immediately\n",
+        "> -   ELIF it’s good → schedule second viewing\n",
+        "> -   ELIF it’s okay → keep as backup\n",
+        "> -   ELSE → continue searching\n",
+        ">\n",
+        "> It’s like a flowchart where only one path can be taken!\n",
+        "\n",
+        "> **Warning**\n",
+        ">\n",
+        "> Important Elif Rules:\n",
+        ">\n",
+        "> 1.  Order matters! Put more specific conditions first\n",
+        "> 2.  Only one block will execute\n",
+        "> 3.  `elif` must come after `if` and before `else`\n",
+        "> 4.  You can have as many `elif` blocks as you need\n",
+        "\n",
+        "## Exercise 3.1 - Apartment Categories\n",
+        "\n",
+        "Create a variable `flat_category` that is:\n",
+        "\n",
+        "-   “Luxury” if rating is 9 or 10\n",
+        "-   “Premium” if rating is 7 or 8\n",
+        "-   “Standard” if rating is 5 or 6\n",
+        "-   “Basic” for anything lower"
+      ],
+      "id": "dcff8196-55f2-49c4-9bde-d08dc944d2b3"
+    },
+    {
+      "cell_type": "code",
+      "execution_count": 7,
+      "metadata": {},
+      "outputs": [],
+      "source": [
+        "flat_rating = 8\n",
+        "flat_category = \"\"\n",
+        "# YOUR CODE BELOW"
+      ],
+      "id": "d4ec91e6"
+    },
+    {
+      "cell_type": "code",
+      "execution_count": 8,
+      "metadata": {},
+      "outputs": [],
+      "source": [
+        "# Test your answer\n",
+        "assert flat_category == \"Premium\", \"The flat category should be 'Premium' as the flat rating is 8\"\n",
+        "print(f\"Flat Category: {flat_category} as the flat rating is {flat_rating}\")"
+      ],
+      "id": "979ce306"
+    },
+    {
+      "cell_type": "markdown",
+      "metadata": {},
+      "source": [
+        "# 4 - Complex Decisions\n",
+        "\n",
+        "In real life, we often need to check multiple conditions at once. We can\n",
+        "combine conditions using `and` and `or`:"
+      ],
+      "id": "709875ea-06ba-4190-89f5-e200bb9f5a22"
+    },
+    {
+      "cell_type": "code",
+      "execution_count": 9,
+      "metadata": {},
+      "outputs": [
+        {
+          "output_type": "stream",
+          "name": "stdout",
+          "text": [
+            "Take this flat - it's good enough and we still have time!"
+          ]
+        }
+      ],
+      "source": [
+        "flat_rating = 8\n",
+        "weeks_searching = 3\n",
+        "max_search_time = 4\n",
+        "\n",
+        "if (flat_rating >= 7) and (weeks_searching < max_search_time):\n",
+        "    print(\"Take this flat - it's good enough and we still have time!\")\n",
+        "elif (flat_rating >= 9) or (weeks_searching >= max_search_time):\n",
+        "    print(\"Take this flat - either it's perfect or we're out of time!\")\n",
+        "else:\n",
+        "    print(\"Keep looking!\")"
+      ],
+      "id": "810f74c4"
+    },
+    {
+      "cell_type": "markdown",
+      "metadata": {},
+      "source": [
+        "> **Tip**\n",
+        ">\n",
+        "> Tips for Complex Conditions:\n",
+        ">\n",
+        "> -   Use parentheses to make your logic clear\n",
+        "> -   Break very complex conditions into smaller parts\n",
+        "> -   Test edge cases to make sure your logic works\n",
+        "\n",
+        "## Exercise 4.1 - Real World Flat Hunting\n",
+        "\n",
+        "Create a variable `should_apply` that is True if:\n",
+        "\n",
+        "-   The flat rating is at least 8, OR\n",
+        "-   The flat rating is at least 6 AND we’ve been searching for 3 weeks\n",
+        "    or more"
+      ],
+      "id": "20ca2323-5129-46b7-8a67-b89220348baa"
+    },
+    {
+      "cell_type": "code",
+      "execution_count": 10,
+      "metadata": {},
+      "outputs": [],
+      "source": [
+        "flat_rating = 6\n",
+        "weeks_searching = 4\n",
+        "should_apply = False\n",
+        "# YOUR CODE BELOW"
+      ],
+      "id": "eec12ccc"
+    },
+    {
+      "cell_type": "code",
+      "execution_count": 11,
+      "metadata": {},
+      "outputs": [],
+      "source": [
+        "# Test your answer\n",
+        "assert should_apply == True, \"The flat rating is 6 and we've been searching for 4 weeks, so we should apply\"\n",
+        "print(f\"Should we apply? {should_apply} as the flat rating is {flat_rating} and we've been searching for {weeks_searching} weeks\")"
+      ],
+      "id": "f96e403d"
+    },
+    {
+      "cell_type": "markdown",
+      "metadata": {},
+      "source": [
+        "# 5 - The 37% Rule with Decisions\n",
+        "\n",
+        "Remember the optimal stopping rule? Let’s apply it to apartment hunting:"
+      ],
+      "id": "4841b456-2a0e-4840-a228-605bc5d51532"
+    },
+    {
+      "cell_type": "code",
+      "execution_count": 12,
+      "metadata": {},
+      "outputs": [
+        {
+          "output_type": "stream",
+          "name": "stdout",
+          "text": [
+            "Apply for this flat!"
+          ]
+        }
+      ],
+      "source": [
+        "flats_seen = 6\n",
+        "total_viewings = 15\n",
+        "current_rating = 8\n",
+        "best_rating_so_far = 7\n",
+        "\n",
+        "# Calculate if we've passed 37% of viewings\n",
+        "threshold_passed = flats_seen >= (total_viewings * 0.37)\n",
+        "\n",
+        "if not threshold_passed:\n",
+        "    print(\"Keep looking - still in observation phase\")\n",
+        "elif current_rating > best_rating_so_far:\n",
+        "    print(\"Apply for this flat!\")\n",
+        "else:\n",
+        "    print(\"Keep looking - waiting for better than our best\")"
+      ],
+      "id": "f524e080"
+    },
+    {
+      "cell_type": "markdown",
+      "metadata": {},
+      "source": [
+        "## Exercise 5.1 - Implement the Rule\n",
+        "\n",
+        "Adjust the code below to change the variable `make_application` to True\n",
+        "if:\n",
+        "\n",
+        "-   We’ve seen at least 37% of available flats (use 15 total flats), AND\n",
+        "-   The current flat is better than the best we’ve seen so far"
+      ],
+      "id": "52a5d792-fa19-465a-bedf-2e7a919af0a9"
+    },
+    {
+      "cell_type": "code",
+      "execution_count": 13,
+      "metadata": {},
+      "outputs": [],
+      "source": [
+        "flats_seen = 6  # We've seen 6 flats\n",
+        "total_viewings = 15  # We plan to view 15 flats in total\n",
+        "current_rating = 9\n",
+        "best_rating_so_far = 8\n",
+        "make_application = False\n",
+        "# YOUR CODE BELOW"
+      ],
+      "id": "36a255d8"
+    },
+    {
+      "cell_type": "code",
+      "execution_count": 14,
+      "metadata": {},
+      "outputs": [],
+      "source": [
+        "# Test your answer\n",
+        "assert make_application == True, \"The flat rating is 9 and we've been searching for 4 weeks, so we should apply\"\n",
+        "print(f\"Should we apply for this flat? {make_application}\")"
+      ],
+      "id": "557eac74"
+    },
+    {
+      "cell_type": "markdown",
+      "metadata": {},
+      "source": [
+        "# Conclusion\n",
+        "\n",
+        "Great work! You’ve learned how to make decisions in Python using:\n",
+        "\n",
+        "-   Simple if statements\n",
+        "-   if-else statements\n",
+        "-   elif for multiple conditions\n",
+        "-   Complex decisions with and/or\n",
+        "-   Applying these to real-world stopping problems\n",
+        "\n",
+        "Remember, just like in apartment hunting, these tools help us make\n",
+        "better decisions in any situation where we need to decide whether to\n",
+        "take what we have or keep looking for something better!\n",
+        "\n",
+        "------------------------------------------------------------------------\n",
+        "\n",
+        "# Solutions\n",
+        "\n",
+        "You will likely find solutions to most exercises online. However, we\n",
+        "strongly encourage you to work on these exercises independently without\n",
+        "searching explicitly for the exact answers to the exercises.\n",
+        "Understanding someone else’s solution is very different from developing\n",
+        "your own. Use the lecture notes and try to solve the exercises on your\n",
+        "own. This approach will significantly enhance your learning and\n",
+        "problem-solving skills.\n",
+        "\n",
+        "Remember, the goal is not just to complete the exercises, but to\n",
+        "understand the concepts and improve your programming abilities. If you\n",
+        "encounter difficulties, review the lecture materials, experiment with\n",
+        "different approaches, and don’t hesitate to ask for clarification during\n",
+        "class discussions.\n",
+        "\n",
+        "Later, you will find the solutions to these exercises online in the\n",
+        "associated GitHub repository, but we will also quickly go over them next\n",
+        "week. To access the solutions, click on the Github button on the lower\n",
+        "right and search for the folder with today’s lecture and tutorial.\n",
+        "Alternatively, you can ask ChatGPT or Claude to explain them to you. But\n",
+        "please remember, the goal is not just to complete the exercises, but to\n",
+        "understand the concepts and improve your programming abilities.\n",
+        "\n",
+        "*That’s it for part I! Next week, we’ll apply these skills exploration\n",
+        "and exploitation!*"
+      ],
+      "id": "7b1318d3-480a-4492-b3a1-233dae20aa9c"
+    }
+  ],
+  "nbformat": 4,
+  "nbformat_minor": 5,
+  "metadata": {
+    "kernelspec": {
+      "name": "python3",
+      "display_name": "Python 3 (ipykernel)",
+      "language": "python",
+      "path": "/Users/tvlcek/miniconda3/share/jupyter/kernels/python3"
+    },
+    "language_info": {
+      "name": "python",
+      "codemirror_mode": {
+        "name": "ipython",
+        "version": "3"
+      },
+      "file_extension": ".py",
+      "mimetype": "text/x-python",
+      "nbconvert_exporter": "python",
+      "pygments_lexer": "ipython3",
+      "version": "3.12.7"
+    }
+  }
+}
\ No newline at end of file
diff --git a/part-01/tutorial-03-stopping 3.pdf b/part-01/tutorial-03-stopping 3.pdf
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diff --git a/part-01/tutorial-03-stopping.html b/part-01/tutorial-03-stopping.html
index e2a577d..fd76859 100644
--- a/part-01/tutorial-03-stopping.html
+++ b/part-01/tutorial-03-stopping.html
@@ -220,6 +220,41 @@
   
  06 - Exploration
   
    
+
+      
+  
+        
  • 
+      
     
+            
+           
+      
    
+      
   
    • 
@@ -311,7 +346,7 @@ 
    Introduction
    
 
    
 
    1 - Understanding If Statements
    
 
    An if statement is like asking a yes/no question and doing something based on the answer. For example:
    
-
    
+
    
 
    flat_rating = 8  # Rate the flat from 0-10
 
 if flat_rating >= 7:
@@ -368,7 +403,7 @@ 
    1 - Understanding If Statements
    
 
    
 
    Exercise 1.1 - Your First Decision
    
 
    Create an if statement that prints “Perfect flat!” if the flat_rating is 10.
    
-
    
+
    
 
    flat_rating = 10
 # YOUR CODE BELOW
 
@@ -379,7 +414,7 @@ 
    Exercis
 
    
 
    2 - Adding Else Statements
    
 
    But what if we want to do something different when the condition is False? That’s where else comes in:
    
-
    
+
    
 
    flat_rating = 4  # Not a great flat!
 
 if flat_rating >= 7:
@@ -419,12 +454,12 @@ 
    2 - Adding Else Statements
    
 
    
 
    Exercise 2.1 - Complete Decision
    
 
    Write an if-else statement that sets decision to “Apply now” if flat_rating is at least 7, and “Keep searching” otherwise.
    
-
    
+
    
 
    flat_rating = 6
 decision = ""
 # YOUR CODE BELOW
    
 
    
-
    
+
    
 
    
 Code
 
    # Test your answer
@@ -456,7 +491,7 @@ 
    Exercise
 
    
 
    3 - Adding Elif (Else If)
    
 
    Sometimes we need more than two options. That’s where elif comes in:
    
-
    
+
    
 
    flat_rating = 8
 
 if flat_rating >= 9:
@@ -525,12 +560,12 @@ 
    Exerci
 
  • “Standard” if rating is 5 or 6
    • 
 
  • “Basic” for anything lower
    • 
 
-
    
+
    
 
    flat_rating = 8
 flat_category = ""
 # YOUR CODE BELOW
    
 
    
-
    
+
    
 
    
 Code
 
    # Test your answer
@@ -543,7 +578,7 @@ 
    Exerci
 
    
 
    4 - Complex Decisions
    
 
    In real life, we often need to check multiple conditions at once. We can combine conditions using and and or:
    
-
    
+
    
 
    flat_rating = 8
 weeks_searching = 3
 max_search_time = 4
@@ -583,13 +618,13 @@ 
    Exe
 
  • The flat rating is at least 8, OR
    • 
 
  • The flat rating is at least 6 AND we’ve been searching for 3 weeks or more
    • 
 
-
    
+
    
 
    flat_rating = 6
 weeks_searching = 4
 should_apply = False
 # YOUR CODE BELOW
    
 
    
-
    
+
    
 
    
 Code
 
    # Test your answer
@@ -602,7 +637,7 @@ 
    Exe
 
    
 
    5 - The 37% Rule with Decisions
    
 
    Remember the optimal stopping rule? Let’s apply it to apartment hunting:
    
-
    
+
    
 
    flats_seen = 6
 total_viewings = 15
 current_rating = 8
@@ -628,7 +663,7 @@ 
    Exercise
 
  • We’ve seen at least 37% of available flats (use 15 total flats), AND
    • 
 
  • The current flat is better than the best we’ve seen so far
    • 
 
-
    
+
    
 
    flats_seen = 6  # We've seen 6 flats
 total_viewings = 15  # We plan to view 15 flats in total
 current_rating = 9
@@ -636,7 +671,7 @@ 
    Exercise
 make_application = False
 # YOUR CODE BELOW
    
 
    
-
    
+
    
 
    
 Code
 
    # Test your answer
diff --git a/part-01/tutorial-03-stopping.ipynb b/part-01/tutorial-03-stopping.ipynb
index b793175..cf1c66a 100644
--- a/part-01/tutorial-03-stopping.ipynb
+++ b/part-01/tutorial-03-stopping.ipynb
@@ -24,7 +24,7 @@
         "An `if` statement is like asking a yes/no question and doing something\n",
         "based on the answer. For example:"
       ],
-      "id": "92569ebe-e96b-44ba-be37-1eb37251b847"
+      "id": "20793639-375f-40ce-9ff4-5fba7c780b19"
     },
     {
       "cell_type": "code",
@@ -45,7 +45,7 @@
         "if flat_rating >= 7:\n",
         "    print(\"This is a good apartment!\")"
       ],
-      "id": "589d51f9"
+      "id": "00461a12"
     },
     {
       "cell_type": "markdown",
@@ -83,7 +83,7 @@
         "Create an `if` statement that prints “Perfect flat!” if the\n",
         "`flat_rating` is 10."
       ],
-      "id": "d07fef3c-f4b5-4001-986c-984f86ea3a90"
+      "id": "7952e1a3-b27e-43a2-aa22-e2374d71ad3c"
     },
     {
       "cell_type": "code",
@@ -96,7 +96,7 @@
         "\n",
         "# Test your answer yourself - the cell should print \"Perfect flat!\" if executed correctly"
       ],
-      "id": "398203b5"
+      "id": "89a92f8e"
     },
     {
       "cell_type": "markdown",
@@ -107,7 +107,7 @@
         "But what if we want to do something different when the condition is\n",
         "False? That’s where `else` comes in:"
       ],
-      "id": "603ab501-83b9-45bb-b443-2381b5997adf"
+      "id": "9742caba-6bdd-4aa7-94f7-e5597d0ca5db"
     },
     {
       "cell_type": "code",
@@ -130,7 +130,7 @@
         "else:\n",
         "    print(\"Keep searching!\")"
       ],
-      "id": "17393550"
+      "id": "05ecb088"
     },
     {
       "cell_type": "markdown",
@@ -158,7 +158,7 @@
         "Write an if-else statement that sets `decision` to “Apply now” if\n",
         "`flat_rating` is at least 7, and “Keep searching” otherwise."
       ],
-      "id": "b23eddeb-726b-4429-83bb-f8f98c294980"
+      "id": "b7295e1e-a3f7-4840-b61c-824d3e3e2bf6"
     },
     {
       "cell_type": "code",
@@ -170,7 +170,7 @@
         "decision = \"\"\n",
         "# YOUR CODE BELOW"
       ],
-      "id": "bbaf80b0"
+      "id": "f7d37a15"
     },
     {
       "cell_type": "code",
@@ -182,7 +182,7 @@
         "assert decision == \"Keep searching\", \"The decision should be 'Keep searching' as the flat rating is less than 7\"\n",
         "print(f\"Decision: {decision} as the flat rating is {flat_rating}\")"
       ],
-      "id": "a2387beb"
+      "id": "ec8c3cc0"
     },
     {
       "cell_type": "markdown",
@@ -201,7 +201,7 @@
         "\n",
         "Sometimes we need more than two options. That’s where `elif` comes in:"
       ],
-      "id": "51dd818f-8ed4-402d-9984-ef9c0162b8b1"
+      "id": "e74b8a60-48b6-4136-8ccd-ad971edb1df0"
     },
     {
       "cell_type": "code",
@@ -228,7 +228,7 @@
         "else:\n",
         "    print(\"Poor flat - definitely keep looking\")"
       ],
-      "id": "c63e67bc"
+      "id": "3ca03921"
     },
     {
       "cell_type": "markdown",
@@ -269,7 +269,7 @@
         "-   “Standard” if rating is 5 or 6\n",
         "-   “Basic” for anything lower"
       ],
-      "id": "3d5ddd84-c166-4c16-82a0-58a8ba6d2aff"
+      "id": "32995be9-629a-4942-86bf-c5142eb1a5b5"
     },
     {
       "cell_type": "code",
@@ -281,7 +281,7 @@
         "flat_category = \"\"\n",
         "# YOUR CODE BELOW"
       ],
-      "id": "e718c73c"
+      "id": "8de89d30"
     },
     {
       "cell_type": "code",
@@ -293,7 +293,7 @@
         "assert flat_category == \"Premium\", \"The flat category should be 'Premium' as the flat rating is 8\"\n",
         "print(f\"Flat Category: {flat_category} as the flat rating is {flat_rating}\")"
       ],
-      "id": "f798a759"
+      "id": "17c1e44c"
     },
     {
       "cell_type": "markdown",
@@ -304,7 +304,7 @@
         "In real life, we often need to check multiple conditions at once. We can\n",
         "combine conditions using `and` and `or`:"
       ],
-      "id": "59cb5d46-1e4e-4745-aff7-dd4ed8820b96"
+      "id": "796de522-a660-4dd5-a5ee-245439222ad3"
     },
     {
       "cell_type": "code",
@@ -331,7 +331,7 @@
         "else:\n",
         "    print(\"Keep looking!\")"
       ],
-      "id": "b404c951"
+      "id": "142c8a5c"
     },
     {
       "cell_type": "markdown",
@@ -353,7 +353,7 @@
         "-   The flat rating is at least 6 AND we’ve been searching for 3 weeks\n",
         "    or more"
       ],
-      "id": "2eca55b4-9600-415c-8769-8a9e97922d72"
+      "id": "cf95f530-ce95-4857-92f0-2973075a5d49"
     },
     {
       "cell_type": "code",
@@ -366,7 +366,7 @@
         "should_apply = False\n",
         "# YOUR CODE BELOW"
       ],
-      "id": "dbc68b3e"
+      "id": "494ca453"
     },
     {
       "cell_type": "code",
@@ -378,7 +378,7 @@
         "assert should_apply == True, \"The flat rating is 6 and we've been searching for 4 weeks, so we should apply\"\n",
         "print(f\"Should we apply? {should_apply} as the flat rating is {flat_rating} and we've been searching for {weeks_searching} weeks\")"
       ],
-      "id": "0140b4f1"
+      "id": "ec8568c5"
     },
     {
       "cell_type": "markdown",
@@ -388,7 +388,7 @@
         "\n",
         "Remember the optimal stopping rule? Let’s apply it to apartment hunting:"
       ],
-      "id": "ee605a1d-66f8-4c79-bf33-b167b77e1694"
+      "id": "35c413c1-c692-4302-a0ef-852327611667"
     },
     {
       "cell_type": "code",
@@ -419,7 +419,7 @@
         "else:\n",
         "    print(\"Keep looking - waiting for better than our best\")"
       ],
-      "id": "ac7b2b3c"
+      "id": "91afa07a"
     },
     {
       "cell_type": "markdown",
@@ -433,7 +433,7 @@
         "-   We’ve seen at least 37% of available flats (use 15 total flats), AND\n",
         "-   The current flat is better than the best we’ve seen so far"
       ],
-      "id": "9a8dd93d-8265-4a13-bf83-6b55be8a1fc4"
+      "id": "393ef287-3b20-4e70-b714-34805678949e"
     },
     {
       "cell_type": "code",
@@ -448,7 +448,7 @@
         "make_application = False\n",
         "# YOUR CODE BELOW"
       ],
-      "id": "de7f15d2"
+      "id": "e1c2f973"
     },
     {
       "cell_type": "code",
@@ -460,7 +460,7 @@
         "assert make_application == True, \"The flat rating is 9 and we've been searching for 4 weeks, so we should apply\"\n",
         "print(f\"Should we apply for this flat? {make_application}\")"
       ],
-      "id": "392e2850"
+      "id": "195d7fe9"
     },
     {
       "cell_type": "markdown",
@@ -509,7 +509,7 @@
         "*That’s it for part I! Next week, we’ll apply these skills exploration\n",
         "and exploitation!*"
       ],
-      "id": "dfba8b05-1b23-4828-ab74-d2169329a568"
+      "id": "9a67642c-6034-4e2a-983a-608b28227a0a"
     }
   ],
   "nbformat": 4,
diff --git a/part-01/tutorial-03-stopping.pdf b/part-01/tutorial-03-stopping.pdf
index 698492ffcc7e942af11c8d66afa278389792a958..334ed59d304cfe3fa9f3c6eae6304f7e66d3f08f 100644
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+Lecture II - Explore Vs. Exploit – Programming: Everyday Decision-Making Algorithms
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    Lecture II - Explore Vs. Exploit
    
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    Programming: Everyday Decision-Making Algorithms
    
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    Author
    
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    Affiliation
    
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    Dr. Nils Roemer 
    
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+            Kühne Logistics University Hamburg - Winter 2024
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    Explore Vs. Exploit
    
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    Some definitions…
    
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    1. Question: What does “explore” mean?
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    2. Question: What does “exploit” mean?
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    3. Question: what is the relationship between ‘explore’ and ‘exploit’ ?
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    4. Explore is the gathering of new information.
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    5. Exploit is the utilization of already known information to obtain a known result.
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    6. Explore and exploit are opposing alternatives in a trade-off.
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    Some examples…
    
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    • Clinical trials
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    • A/B testing
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    • Restaurant choice
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    • Dating
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    • Social interactions
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    Everyday decision-making
    
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    • Explore: Do we try new things?
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    • Exploit: Do we stick to our favorite ones?
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    • Life is a trade-off, a balance:
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      • between novelty and tradition.
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      • between the latest and the greatest.
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      • between explore and exploit.
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    • Question: What is the optimal balance?
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    • Scientists have been working on this for over 50 years.
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    Question: What is the problem with exploitation?
    
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    • Exploitation is not always the best strategy.
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    • Especially when you have very limited information.
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    • When you stop exploring, you might miss out on better options.
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    • Imagine you were no longer able to gather any new information and could only choose between known alternatives.
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    Question: What is the problem with exploration?
    
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    • Exploration is not always the best strategy.
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    • Especially when you are limited in using the newly gathered information.
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    • When you constantly explore, you might never enjoy the fruits of your exploration.
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    • Imagine you could eat each meal only once, hear each song only once, talk to each person only once…
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    The Multi-Armed Bandit Problem
    
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    To provide decision support, computer scientists formulated the explore-exploit trade-off as the multi-armed bandit problem.
    
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    Question: What is a one-armed bandit?
    
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    One Armed Bandit
    
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    Photo by Kabir M on Unsplash
    
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    The multi-armed bandit problem I
    
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    • A gambler is faced with a room of slot machines (one-armed bandits).
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    • Each slot machine has a different probability of winning.
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    • Question: What does the scenario have to do with explore vs exploit?
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    The multi-armed bandit problem II
    
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    • By playing a slot machine, the gambler can gather information about the probability of winning.
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    • But each pull of a lever comes with a certain cost.
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    • It’s the aim of the gambler to maximize his winnings.
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    The multi-armed bandit problem III
    
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    • Consider the following scenario:
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      • You already pulled the lever of two machines.
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      • Machine A: 15 pulls, 9 wins.
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      • Machine B: 2 pulls, 1 win.
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    • Question: Which machine should you play next?
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    Expected value as a decision criterion
    
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    • The expected value of a slot machine is the average number of wins per pull.
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    • Expected value of machine A = E(A) = 9/15 = 0.6
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    • Expected value of machine B = E(B) = 1/2 = 0.5
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    • Machine A has the higher expected value.
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    • But 2 and even 15 pulls are not a large number (considering standard deviation).
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    The multi-armed bandit problem IV
    
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    • The multi-armed bandit problem represents a lot of different real-world decisions.
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    • It shows us, that there might be a difference between the optimal long-term average performance and the optimal immediate performance.
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    • Which lever to pull next depends completely on something we haven’t discussed yet:
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    The multi-armed bandit problem V
    
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    • How long you plan to be in the casino?
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    • Question: Why is this important?
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    • Question: How does this influence our decision on taking machine A or machine B?
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    . . .
    
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    “I’m more likely to try a new restaurant when I move to a city than when I’m leaving it” (Chris Stucchio)
    
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    The influence of the interval
    
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    • Let’s call the time you plan to be in the casino “the interval”.
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    • The longer the interval, the more (in general) you should explore, since you will have more opportunities to exploit the gathered information.
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    • The shorter the interval, the more you should exploit your current knowledge.
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    • The optimal strategy depends on the length of the interval.
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    Interval and Exploration
    
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    • Explore when you have the time to use the resulting knowledge.
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    . . .
    
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    “I moved to Pune, India, and I just […] eat everywhere that didn’t look like it was gonna kill me” (Chris Stucchio)
    
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    Interval and Exploitation
    
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    • Exploit when you are ready to cash in.
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    . . .
    
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    “And as I was leaving the city I went back to all my old favorites, rather than trying out new stuff […]. Even if I find a slightly better place, I’m only going to go there once or twice, so why take the risk?” (Chris Stucchio)
    
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    Exploration and Exploitation
    
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    Exploration
    
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    Photo by Colin Maynard on Unsplash
    
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    Exploitation
    
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    Photo by Cristina Gottardi on Unsplash
    
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    Reverse Engineering
    
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    • Derivation of the interval by observing the strategy
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    • Among the the ten highest-grossing movies, how many were sequels?
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      • 1981: 2
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      • 1991: 3
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      • 2001: 5
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      • 2011: 8
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    • Question: Do you have an explanation for the trend?
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    Sequels…
    
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    Photo by Universal Pictures on Wikipedia
    
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    Reverse Engineering: A possible explanation
    
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    • Making a brand new movie is risky but has the potential to create a new fan base. (explore)
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    • From a Studio’s perspective, a sequel is a movie with a guaranteed fan base, a cash cow, a sure thing, an exploit.
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    • One possible explanation for the numbers is that the studios think they are approaching the end of their interval.
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    • They are pulling the arms of the best machines they’ve got before the casino turns them out.
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    The multi-armed bandit problem VI
    
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    • While the so far provided anecdotes are helping us to understand the explore-exploit trade-off, they are far away from beeing a satisfying “optimal” solution.
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    • Actually, finding an algorithm that tells us exactly how to to handle the trade-off is a very hard problem.
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    • On the way there were many interesting approaches…
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    Win-Stay Lose-Shift
    
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    Win-Stay Lose-Shift1
    
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    • Question: What do you think, what the win-stay lose-shift strategy does?
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    • The win-stay lose-shift strategy is a simple strategy that is often used in multi-armed bandit problems.
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    • It is based on the idea that if you have won, you should stay with the same machine.
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    • If you have lost, you should switch to a different machine.
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    • This strategy is not always the best strategy, but it is simple and proven better than choose an arm at random.
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    Win-Stay is a no brainer
    
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    • Question: What do you think about win-stay?
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    • If you decide to pull an arm and you win, you should pull the same arm again.
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    • Nothing changes, except the attractiveness of the arm you just pulled is higher.
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    Lose-Shift is another story
    
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    • Question: What do you think about lose-shift?
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    • Changing arms each time you lose might be a prety rush move.
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    • Imagine you’re eating at your favorite restaurant for the tenth time in a row.
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    • You have always been very satisfied (win), but today you are disappointed (loose).
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    • Should you turn your back on the restaurant?
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    Like most of the time, easy answers comes with problems
    
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    • The win-stay lose-shift strategy penalizes losses too much.
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    • The strategy does not take into account the interval.
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    • But the strategy was good start to develop better approaches.
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    The Bellman Approach
    
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    The Bellman approach I
    
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    • Few years later, Richard Bellman, found an exact solution to the problem for all cases with finite and known intervals.
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    • Bellman found that under the given assumptions, exploit vs explore can be formulated as an optimal stopping problem.
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    • Where the question is, when to stop exploring and start exploiting.
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    • The solution is based on dynamic programming and backward calculation starting from the final pull (analogous to the secretary problem with full information).
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    The Bellman approach II
    
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    • Bellman found that the following equation provides the optimal strategy (when the assumptions hold):
      • 
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    \[\mathbb{E}[B] = \frac{w + 1}{w + l + 2}\]
    
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    • where w is the number of wins and l is the number of loses.
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    Question time
    
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    \[\mathbb{E}[B] = \frac{w + 1}{w + l + 2}\]
    
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    • Question: What is E[B]?
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    • Question: What is E[A]?
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    • Question: What machine shall we play according to the Bellman approach?
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    The Bellman approach III
    
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    The following table shows the expected value for different win-lose scenarios.
    
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    Loses/Wins12345678910
    10.500.600.670.710.750.780.800.820.830.85
    20.400.500.570.630.670.700.730.750.770.79
    30.330.430.500.560.600.640.670.690.710.73
    40.290.380.440.500.550.580.620.640.670.69
    50.250.330.400.450.500.540.570.600.630.65
    60.220.300.360.420.460.500.530.560.590.61
    70.200.270.330.380.430.470.500.530.560.58
    80.180.250.310.360.400.440.470.500.530.55
    90.170.230.290.330.380.410.440.470.500.52
    100.150.210.270.310.350.390.420.450.480.50
    
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    The Bellman approach IV
    
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+
      
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    • The calculation of the optimal strategy is very extensive when there are many arms and a long interval.
      • 
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    • And yet the approach does not help us in many scenarios because we do not know the exact length of the interval (time in the casino).
      • 
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    • At this point, it looked like the multi-armed bandit problem would remain a problem without a solution.
      • 
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    The Gittins Index
    
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    The Gittins Index I2
    
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    • In the 1970s Unilever asked a young mathematician, John Gittins, to help optimize their drug trials.
      • 
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    • Given different compounds, what is the quickest way to determine which is likely to be effective?
      • 
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    • Gittins found an optimal strategy and abstracted the problem to a general level.
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    • He found the solution to the multi-armed bandit problem.
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    The Gittins Index II
    
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    • A major problem with the multi-armed banded problem is that previous solutions made very critical assumptions about the underlying interval.
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    • For example, that the length of the interval is known at the beginning of the analysis.
      • 
+
    • Gittins developed a charming solution to this problem. In his approach, future wins (e.g., cash flows) are discounted so that any interval length (including infinity) can be considered.
      • 
+
    
+
    
+
    
+
    
+
    Reality check: Discounting I
    
+
    
+
      
+
    • Does discounting future wins make sense?
      • 
+
    • Question: Does discounting money wins make sense?
      • 
+
    • Regarding monetary wins, it does. For example, due to interest rates and opportunity costs.
      • 
+
    
+
    
+
    
+
    
+
    Reality check: Discounting II
    
+
    
+
      
+
    • Does discounting future wins make sense?
      • 
+
    • Question: Does discounting non-monetary wins make sense?
      • 
+
    • Regarding non-monetary wins, it is more difficult to justify.
      • 
+
    • But its not counterintuitive.
      • 
+
    • What is more important to you today, tonight’s dinner, or ceteris paribus the dinner in a week’s time?
      • 
+
    
+
    
+
    
+
    
+
    The Gittins Index III
    
+
    
+
      
+
    • The Gittins index can be used for any problems of the form of the multi-armed bandit problem.
      • 
+
    • That means it solves the explore-exploit trade-off.
      • 
+
    • Let’s consider our machine A and B example one last time.
+
        
+
      • Machine A: 15 pulls, 9 wins, 6 loses.
        • 
+
      • Machine B: 2 pulls, 1 win, 1 lose.
        • 
+
      • 
+
    
+
    
+
    
+
    
+
    The Gittins Index IV
    
+
    
+
+
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    Loses/Wins0123456789
    0.7029.8001.8452.8723.8905.9039.9141.9221.9287.9342
    1.5001.6346.7072.7539.7869.8115.8307.8461.8588.8695
    2.3796.5163.6010.6579.6996.7318.7573.7782.7956.8103
    3.3021.4342.5184.5809.6276.6642.6940.7187.7396.7573
    4.2488.3720.4561.5179.5676.6071.6395.6666.6899.7101
    5.2103.3245.4058.4677.5168.5581.5923.6212.6461.6677
    6.1815.2871.3647.4257.4748.5156.5510.5811.6071.6300
    7.1591.2569.3308.3900.4387.4795.5144.5454.5723.5960
    8.1413.2323.3025.3595.4073.4479.4828.5134.5409.5652
    9.1269.2116.2784.3332.3799.4200.4548.4853.5125.5373
    
+
    
+
    
+
    
+
    Question: Choose machine A or B according to the Gittins index?
    
+
    
+
      
+
    • The index for machine B (0.6346) is higher than for machine A (0.6300).
      • 
+
    • The index shows a clear win-stay pattern.
      • 
+
    • There is a relaxed lose-shift pattern.
      • 
+
    • At the (0,0) point we see the exploration bonus (premium).
      • 
+
    • The index converges to 1/2 for a 50/50 chance game.
      • 
+
    
+
    
+
    
+
    
+
    The Gittins Index V
    
+
    
+
      
+
    • The problem with the Gittins index is that it is very difficult to calculate.
      • 
+
    • See the following equation: \[G_i(s_i, f_i) := \sup_{\tau \geq 1} \frac{\mathbb{E}\left[\sum_{t=0}^{\tau-1} \beta^t \cdot r_i^t \middle| s_i, f_i\right]}{\mathbb{E}\left[\sum_{t=0}^{\tau-1} \beta^t\right]}\]
      • 
+
    • Where \(G_i(s_i, f_i)\) is the Gittins index for machine \(i\), \(s_i\) is the number of wins, \(f_i\) is the number of losses, \(\beta\) is the discount factor, and \(r_i^t\) is the reward for machine \(i\) at time \(t\).
      • 
+
    
+
    
+
    
+
    
+
    
+
    Explore vs Exploit: Summary
    
+
    
+
    Explore vs Exploit: Summary
    
+
    
+
      
+
    • Consider an explore vs exploit decision situation.
      • 
+
    • As you learned exploiting comes with a known (expected) outcome for example E(A) = 0.6
      • 
+
    • Exploring comes with an unknown outcome E(B) = ?
      • 
+
    • What should you do according to decision science?
      • 
+
    
+
    
+
    
+
    
+
    Explore vs Exploit: Anecdotally
    
+
    
+
      
+
    • If you have a long interval, you should explore, choose B untill you are sure about E(B).
      • 
+
    • If you have a short interval, you should exploit, choose A.
      • 
+
    
+
    
+
    
+
    
+
    Explore vs Exploit: Mathematically
    
+
    
+
      
+
    • If E(A) and E(B) are known, choose higher expected value.
      • 
+
    • If E(B) is unknown, but you know the length of the interval, the Bellman-approach provides the optimal strategy.
      • 
+
    • If E(B) is unknown, and you do not know the length of the interval, the Gittins index provides the optimal strategy.
      • 
+
    
+
    
+
    
+
    
+
    Explore vs Exploit: Key Takeaways
    
+
    
+
    “The grass is always greener on the other side of the fence.”
    
+
    
+
    
+
      
+
    • The math tells us why:
      • 
+
    • Exploration in it self has a value, since trying new things increases our chance of finding the best.
      • 
+
    • Your todays takeaway from the lecture should be: Be sensitive to how much time you have left in the casino and explore, explore, explore…
      • 
+
    
+
    
+
    
+
    
+
    
+
    Literature
    
+
    
+
    Interesting literature to start
    
+
      
+
    • Christian, B., & Griffiths, T. (2016). Algorithms to live by: the computer science of human decisions. First international edition. New York, Henry Holt and Company.3
      • 
+
    • Ferguson, T.S. (1989) ‘Who solved the secretary problem?’, Statistical Science, 4(3). doi:10.1214/ss/1177012493.
      • 
+
    
+
    
+
    
+
    Books on Programming
    
+
      
+
    • Downey, A. B. (2024). Think Python: How to think like a computer scientist (Third edition). O’Reilly. Here
      • 
+
    • Elter, S. (2021). Schrödinger programmiert Python: Das etwas andere Fachbuch (1. Auflage). Rheinwerk Verlag.
      • 
+
    
+
    . . .
    
+
    
+
    
+
    
+
+
    
+
    
+Note
+
    
+
    
+
    
+
    Think Python is a great book to start with. It’s available online for free. Schrödinger Programmiert Python is a great alternative for German students, as it is a very playful introduction to programming with lots of examples.
    
+
    
+
    
+
    
+
    
+
    More Literature
    
+
    For more interesting literature, take a look at the literature list of this course.
    
+
+
+
    
+
    
+
+
+
    Footnotes
    
+
+
      
+
    1. For more details see Robbins, H. (1952) ‘Some aspects of the sequential design of experiments’, Bulletin of the American Mathematical Society, 58.↩︎
      2. 
+
    2. Gittins, J. (1979) ‘Bandit Processes and Dynamic Allocation Indices’, Journal of the Royal Statistical Society. Series B (Methodological).↩︎
      3. 
+
    3. The main inspiration for this lecture. Nils and I have read it and discussed it in depth, always wanting to translate it into a course.↩︎
      4. 
+
    
+
     
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+
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  06 - Exploration
   
    
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+      
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+        
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+      
     
+            
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+      
   
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+  
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+  
+  Programming: Everyday Decision-Making Algorithms – Lecture II - Explore Vs. Exploit
+  
+  
+  
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+    
    
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+  
    Lecture II - Explore Vs. Exploit
    
+  
    Programming: Everyday Decision-Making Algorithms
    
+
+
    
+
    
+
    
+Dr. Nils Roemer 
+
    
+        
    
+            Kühne Logistics University Hamburg - Winter 2024
+          
    
+    
    
+
    
+
+
    
+
    
+
    
+
    Explore Vs. Exploit
    
+
+
    
+
    
+
    Some definitions…
    
+
    
+
      
+
    1. Question: What does “explore” mean?
      2. 
+
    2. Question: What does “exploit” mean?
      3. 
+
    3. Question: what is the relationship between ‘explore’ and ‘exploit’ ?
      4. 
+
    4. Explore is the gathering of new information.
      5. 
+
    5. Exploit is the utilization of already known information to obtain a known result.
      6. 
+
    6. Explore and exploit are opposing alternatives in a trade-off.
      7. 
+
    
+
    
+
    
+
    
+
    Some examples…
    
+
    
+
      
+
    • Clinical trials
      • 
+
    • A/B testing
      • 
+
    • Restaurant choice
      • 
+
    • Dating
      • 
+
    • Social interactions
      • 
+
    
+
    
+
    
+
    
+
    Everyday decision-making
    
+
    
+
      
+
    • Explore: Do we try new things?
      • 
+
    • Exploit: Do we stick to our favorite ones?
      • 
+
    • Life is a trade-off, a balance:
+
        
+
      • between novelty and tradition.
        • 
+
      • between the latest and the greatest.
        • 
+
      • between explore and exploit.
        • 
+
      • 
+
    • Question: What is the optimal balance?
      • 
+
    • Scientists have been working on this for over 50 years.
      • 
+
    
+
    
+
    
+
    
+
    Question: What is the problem with exploitation?
    
+
    
+
      
+
    • Exploitation is not always the best strategy.
      • 
+
    • Especially when you have very limited information.
      • 
+
    • When you stop exploring, you might miss out on better options.
      • 
+
    • Imagine you were no longer able to gather any new information and could only choose between known alternatives.
      • 
+
    
+
    
+
    
+
    
+
    Question: What is the problem with exploration?
    
+
    
+
      
+
    • Exploration is not always the best strategy.
      • 
+
    • Especially when you are limited in using the newly gathered information.
      • 
+
    • When you constantly explore, you might never enjoy the fruits of your exploration.
      • 
+
    • Imagine you could eat each meal only once, hear each song only once, talk to each person only once…
      • 
+
    
+
    
+
    
+
    
+
    
+
    The Multi-Armed Bandit Problem
    
+
+
    
+
    
+
    To provide decision support, computer scientists formulated the explore-exploit trade-off as the multi-armed bandit problem.
    
+
    Question: What is a one-armed bandit?
    
+
    
+
    
+
    One Armed Bandit
    
+
    
+
    Photo by Kabir M on Unsplash
    
+
    
+
    
+
    
+
    The multi-armed bandit problem I
    
+
    
+
      
+
    • A gambler is faced with a room of slot machines (one-armed bandits).
      • 
+
    • Each slot machine has a different probability of winning.
      • 
+
    • Question: What does the scenario have to do with explore vs exploit?
      • 
+
    
+
    
+
    
+
    
+
    The multi-armed bandit problem II
    
+
    
+
      
+
    • By playing a slot machine, the gambler can gather information about the probability of winning.
      • 
+
    • But each pull of a lever comes with a certain cost.
      • 
+
    • It’s the aim of the gambler to maximize his winnings.
      • 
+
    
+
    
+
    
+
    
+
    The multi-armed bandit problem III
    
+
    
+
      
+
    • Consider the following scenario:
+
        
+
      • You already pulled the lever of two machines.
        • 
+
      • Machine A: 15 pulls, 9 wins.
        • 
+
      • Machine B: 2 pulls, 1 win.
        • 
+
      • 
+
    • Question: Which machine should you play next?
      • 
+
    
+
    
+
    
+
    
+
    Expected value as a decision criterion
    
+
    
+
      
+
    • The expected value of a slot machine is the average number of wins per pull.
      • 
+
    • Expected value of machine A = E(A) = 9/15 = 0.6
      • 
+
    • Expected value of machine B = E(B) = 1/2 = 0.5
      • 
+
    • Machine A has the higher expected value.
      • 
+
    • But 2 and even 15 pulls are not a large number (considering standard deviation).
      • 
+
    
+
    
+
    
+
    
+
    The multi-armed bandit problem IV
    
+
    
+
      
+
    • The multi-armed bandit problem represents a lot of different real-world decisions.
      • 
+
    • It shows us, that there might be a difference between the optimal long-term average performance and the optimal immediate performance.
      • 
+
    • Which lever to pull next depends completely on something we haven’t discussed yet:
      • 
+
    
+
    
+
    
+
    
+
    The multi-armed bandit problem V
    
+
    
+
      
+
    • How long you plan to be in the casino?
      • 
+
    • Question: Why is this important?
      • 
+
    • Question: How does this influence our decision on taking machine A or machine B?
      • 
+
    
+
    
+
    
+
    
+
    “I’m more likely to try a new restaurant when I move to a city than when I’m leaving it” (Chris Stucchio)
    
+
    
+
    
+
    
+
    
+
    The influence of the interval
    
+
    
+
      
+
    • Let’s call the time you plan to be in the casino “the interval”.
      • 
+
    • The longer the interval, the more (in general) you should explore, since you will have more opportunities to exploit the gathered information.
      • 
+
    • The shorter the interval, the more you should exploit your current knowledge.
      • 
+
    • The optimal strategy depends on the length of the interval.
      • 
+
    
+
    
+
    
+
    
+
    Interval and Exploration
    
+
      
+
    • Explore when you have the time to use the resulting knowledge.
      • 
+
    
+
    
+
    
+
    “I moved to Pune, India, and I just […] eat everywhere that didn’t look like it was gonna kill me” (Chris Stucchio)
    
+
    
+
    
+
    
+
    
+
    Interval and Exploitation
    
+
      
+
    • Exploit when you are ready to cash in.
      • 
+
    
+
    
+
    
+
    “And as I was leaving the city I went back to all my old favorites, rather than trying out new stuff […]. Even if I find a slightly better place, I’m only going to go there once or twice, so why take the risk?” (Chris Stucchio)
    
+
    
+
    
+
    
+
    
+
    
+
    Exploration and Exploitation
    
+
+
    
+
    
+
    Exploration
    
+
    
+
    Photo by Colin Maynard on Unsplash
    
+
    
+
    
+
    
+
    Exploitation
    
+
    
+
    Photo by Cristina Gottardi on Unsplash
    
+
    
+
    
+
    
+
    Reverse Engineering
    
+
    
+
      
+
    • Derivation of the interval by observing the strategy
      • 
+
    • Among the the ten highest-grossing movies, how many were sequels?
+
        
+
      • 1981: 2
        • 
+
      • 1991: 3
        • 
+
      • 2001: 5
        • 
+
      • 2011: 8
        • 
+
      • 
+
    • Question: Do you have an explanation for the trend?
      • 
+
    
+
    
+
    
+
    
+
    Sequels…
    
+
    
+
    Photo by Universal Pictures on Wikipedia
    
+
    
+
    
+
    
+
    Reverse Engineering: A possible explanation
    
+
    
+
      
+
    • Making a brand new movie is risky but has the potential to create a new fan base. (explore)
      • 
+
    • From a Studio’s perspective, a sequel is a movie with a guaranteed fan base, a cash cow, a sure thing, an exploit.
      • 
+
    • One possible explanation for the numbers is that the studios think they are approaching the end of their interval.
      • 
+
    • They are pulling the arms of the best machines they’ve got before the casino turns them out.
      • 
+
    
+
    
+
    
+
    
+
    The multi-armed bandit problem VI
    
+
    
+
      
+
    • While the so far provided anecdotes are helping us to understand the explore-exploit trade-off, they are far away from beeing a satisfying “optimal” solution.
      • 
+
    • Actually, finding an algorithm that tells us exactly how to to handle the trade-off is a very hard problem.
      • 
+
    • On the way there were many interesting approaches…
      • 
+
    
+
    
+
    
+
    
+
    
+
    Win-Stay Lose-Shift
    
+
+
    
+
    
+
    Win-Stay Lose-Shift1
    
+
    
+
      
+
    • The win-stay lose-shift strategy is a simple strategy that is often used in multi-armed bandit problems.
      • 
+
    • It is based on the idea that if you have won, you should stay with the same machine.
      • 
+
    • If you have lost, you should switch to a different machine.
      • 
+
    • This strategy is not always the best strategy, but it is simple and proven better than choose an arm at random.
      • 
+
    
+
    
+
    
+
    
+
    Win-Stay is a no brainer
    
+
    
+
      
+
    • If you decide to pull an arm and you win, you should pull the same arm again.
      • 
+
    • Nothing changes, except the attractiveness of the arm you just pulled is higher.
      • 
+
    
+
    
+
    
+
    
+
    Lose-Shift is another story
    
+
    
+
      
+
    • Changing arms each time you lose might be a prety rush move.
      • 
+
    • Imagine you’re eating at your favorite restaurant for the tenth time in a row.
      • 
+
    • You have always been very satisfied (win), but today you are disappointed (loose).
      • 
+
    • Should you turn your back on the restaurant?
      • 
+
    
+
    
+
    
+
    
+
    Like most of the time, easy answers comes with problems
    
+
    
+
      
+
    • The win-stay lose-shift strategy penalizes losses too much.
      • 
+
    • The strategy does not take into account the interval.
      • 
+
    • But the strategy laid the foundation for better approaches
      • 
+
    
+
    
+
    
+
    
+
    
+
    The Bellman Approach
    
+
+
    
+
    
+
    The Bellman approach I
    
+
    
+
      
+
    • Few years later, Richard Bellman, found an exact solution to the problem for all cases with finite and known intervals.
      • 
+
    • Bellman found that under the given assumptions, exploit vs explore can be formulated as an optimal stopping problem.
      • 
+
    • Where the question is, when to stop exploring and start exploiting.
      • 
+
    • The solution is based on dynamic programming and backward calculation starting from the final pull (analogous to the secretary problem with full information).
      • 
+
    
+
    
+
    
+
    
+
    The Bellman approach II
    
+
    
+
      
+
    • Consider the example with machine A and B again.
      • 
+
    • The following graph shows the possible outcomes of the next 4 pulls at machine B.
      • 
+
    • When should we stop exploring and start exploiting?
      • 
+
    
+
    
+
    
+
    
+
    The Bellman approach III
    
+
    
+
    
+
    
+
    
+
    
+
    
+
    graph TD
+    D1(["(1,1)"]) --> |Win| D2A(["(2,1)"])
+    D1 --> |Lose| D2B(["(1,2)"])
+    
+    D2A --> |Win| D3AA(["(3,1)"])
+    D2A --> |Lose| D3AB(["(2,2)"])
+    D2B --> |Win| D3AB(["(2,2)"])
+    D2B --> |Lose| D3BB(["(1,3)"])
+    
+    D3AA --> |Win| D4AAA(["(4,1)"])
+    D3AA --> |Lose| D4AAB(["(3,2)"])
+    D3AB --> |Win| D4AAB(["(3,2)"])
+    D3AB --> |Lose| D4ABB(["(2,3)"])
+    D3BB --> |Win| D4ABB(["(2,3)"])
+    D3BB --> |Lose| D4BBB(["(1,4)"])
+    
+    D4AAA --> |Win| D5AAAA(["(5,1)"])
+    D4AAA --> |Lose| D5AAAB(["(4,2)"])
+    D4AAB --> |Win| D5AAAB(["(4,2)"])
+    D4AAB --> |Lose| D5AABB(["(3,3)"])
+    D4ABB --> |Win| D5AABB(["(3,3)"])
+    D4ABB --> |Lose| D5ABBB(["(2,4)"])
+    D4BBB --> |Win| D5ABBB(["(2,4)"])
+    D4BBB --> |Lose| D5BBBB(["(1,5)"])
+
    
+
    
+
    
+
    
+
    
+
    
+
    
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+
    
+
    The Bellman approach IV
    
+
    
+
+
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    Loses/Wins12345678910
    10.500.600.670.710.750.780.800.820.830.85
    20.400.500.570.630.670.700.730.750.770.79
    30.330.430.500.560.600.640.670.690.710.73
    40.290.380.440.500.550.580.620.640.670.69
    50.250.330.400.450.500.540.570.600.630.65
    60.220.300.360.420.460.500.530.560.590.61
    70.200.270.330.380.430.470.500.530.560.58
    80.180.250.310.360.400.440.470.500.530.55
    90.170.230.290.330.380.410.440.470.500.52
    100.150.210.270.310.350.390.420.450.480.50
    
+
    
+
    
+
    
+
    The Bellman approach V
    
+
    Calculated with the following equation: \[
+\mathbb{E}[B] = \frac{w + 1}{w + l + 2}
+\] where w is the number of wins and l is the number of loses.
    
+
    
+
    
+
    The Bellman approach VI
    
+
    
+
      
+
    • The calculation of the optimal strategy is very extensive when there are many arms and a long interval.
      • 
+
    • And yet the approach does not help us in many scenarios because we do not know the exact number of opportunities/time in the casino (length of the interval).
      • 
+
    • At this point, it looked like the multi-armed bandit problem would remain a problem without a solution.
      • 
+
    
+
    
+
    
+
    
+
    
+
    The Gittins Index
    
+
+
    
+
    
+
    The Gittins Index I1
    
+
    
+
      
+
    • In the 1970s Unilever asked a young mathematician, John Gittins, to help optimize their drug trials.
      • 
+
    • Given different compounds, what is the quickest way to determine which is likely to be effective?
      • 
+
    • Gittins found an optimal strategy and abstracted the problem to a general level.
      • 
+
    • He found the solution to the multi-armed bandit problem.
      • 
+
    
+
    
+
    
+
    
+
    The Gittins Index II
    
+
    
+
      
+
    • A major problem with the multi-armed banded problem is that previous solutions made very critical assumptions about the underlying interval.
      • 
+
    • For example, that the length of the interval is known at the beginning of the analysis.
      • 
+
    • Gittins developed a charming solution to this problem. In his approach, future wins (e.g., cash flows) are discounted so that any interval length (including infinity) can be considered.
      • 
+
    
+
    
+
    
+
    
+
    Reality check: Discounting
    
+
    
+
      
+
    • Does discounting future wins make sense?
      • 
+
    • Regarding monetary wins, it does. For example, due to interest rates and opportunity costs.
      • 
+
    • Regarding non-monetary wins, it is more difficult to justify.
      • 
+
    • But its not counterintuitive.
      • 
+
    • What is more important to you today, tonight’s dinner, or ceteris paribus the dinner in a week’s time?
      • 
+
    
+
    
+
    
+
    
+
    The Gittins Index III
    
+
    
+
      
+
    • The Gittins index can be used for any problems of the form of the multi-armed bandit problem.
      • 
+
    • That means it solves the explore-exploit trade-off.
      • 
+
    • Let’s consider our machine A and B example one last time.
+
        
+
      • Machine A: 15 pulls, 9 wins, 6 loses.
        • 
+
      • Machine B: 2 pulls, 1 win, 1 lose.
        • 
+
      • 
+
    
+
    
+
    
+
    
+
    The Gittins Index IV
    
+
    
+
+
+++++++++++++
+
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    Loses/Wins0123456789
    0.7029.8001.8452.8723.8905.9039.9141.9221.9287.9342
    1.5001.6346.7072.7539.7869.8115.8307.8461.8588.8695
    2.3796.5163.6010.6579.6996.7318.7573.7782.7956.8103
    3.3021.4342.5184.5809.6276.6642.6940.7187.7396.7573
    4.2488.3720.4561.5179.5676.6071.6395.6666.6899.7101
    5.2103.3245.4058.4677.5168.5581.5923.6212.6461.6677
    6.1815.2871.3647.4257.4748.5156.5510.5811.6071.6300
    7.1591.2569.3308.3900.4387.4795.5144.5454.5723.5960
    8.1413.2323.3025.3595.4073.4479.4828.5134.5409.5652
    9.1269.2116.2784.3332.3799.4200.4548.4853.5125.5373
    
+
    
+
    
+
    
+
    Question: Choose machine A or B according to the Gittins index?
    
+
    
+
      
+
    • The index shows a clear win-stay pattern.
      • 
+
    • There is a relaxed lose-shift pattern.
      • 
+
    • At the (0,0) point we see the exploration bonus (premium).
      • 
+
    • The index converges to 1/2 for a 50/50 chance game.
      • 
+
    • The index for machine B (0.6346) is higher than for machine A (0.6300).
      • 
+
    
+
    
+
    
+
    
+
    The Gittins Index V
    
+
    
+
      
+
    • The problem with the Gittins index is that it is very difficult to calculate.
      • 
+
    • See the following equation: \[G_i(s_i, f_i) := \sup_{\tau \geq 1} \frac{\mathbb{E}\left[\sum_{t=0}^{\tau-1} \beta^t \cdot r_i^t \middle| s_i, f_i\right]}{\mathbb{E}\left[\sum_{t=0}^{\tau-1} \beta^t\right]}\]
      • 
+
    • Where \(G_i(s_i, f_i)\) is the Gittins index for machine \(i\), \(s_i\) is the number of wins, \(f_i\) is the number of losses, \(\beta\) is the discount factor, and \(r_i^t\) is the reward for machine \(i\) at time \(t\).
      • 
+
    
+
    
+
    
+
    
+
    
+
    Explore vs Exploit: Summary
    
+
+
    
+
    
+
    Explore vs Exploit: Summary
    
+
    
+
      
+
    • Consider an explore vs exploit decision situation.
      • 
+
    • As you learned exploiting comes with a known (expected) outcome for example E(A) = 0.6
      • 
+
    • Exploring comes with an unknown outcome E(B) = ?
      • 
+
    • What should you do according to decision science?
      • 
+
    
+
    
+
    
+
    
+
    Explore vs Exploit: Anecdotally
    
+
    
+
      
+
    • If you have a long interval, you should explore, choose B untill you are sure about E(B).
      • 
+
    • If you have a short interval, you should exploit, choose A.
      • 
+
    
+
    
+
    
+
    
+
    Explore vs Exploit: Mathematically
    
+
    
+
      
+
    • If E(A) and E(B) are known, choose higher expected value.
      • 
+
    • If E(B) is unknown, but you know the length of the interval, the Bellman-approach provides the optimal strategy.
      • 
+
    • If E(B) is unknown, and you do not know the length of the interval, the Gittins index provides the optimal strategy.
      • 
+
    
+
    
+
    
+
    
+
    Explore vs Exploit: Key Takeaways
    
+
    
+
    “The grass is always greener on the other side of the fence.”
    
+
    
+
    
+
      
+
    • The math tells us why:
      • 
+
    • Exploration in it self has a value, since trying new things increases our chance of finding the best.
      • 
+
    • Your todays takeaway from the lecture should be: Be sensitive to how much time you have left in the casino and explore, explore, explore…
      • 
+
    
+
    
+
    
+
    
+
    
+
    Literature
    
+
+
    
+
    
+
    Interesting literature to start
    
+
      
+
    • Christian, B., & Griffiths, T. (2016). Algorithms to live by: the computer science of human decisions. First international edition. New York, Henry Holt and Company.1
      • 
+
    • Ferguson, T.S. (1989) ‘Who solved the secretary problem?’, Statistical Science, 4(3). doi:10.1214/ss/1177012493.
      • 
+
    
+
    
+
    
+
    Books on Programming
    
+
      
+
    • Downey, A. B. (2024). Think Python: How to think like a computer scientist (Third edition). O’Reilly. Here
      • 
+
    • Elter, S. (2021). Schrödinger programmiert Python: Das etwas andere Fachbuch (1. Auflage). Rheinwerk Verlag.
      • 
+
    
+
    
+
    
+
    
+
    
+
    
+
+
    
+
    Note
    
+
    
+
    
+
    Think Python is a great book to start with. It’s available online for free. Schrödinger Programmiert Python is a great alternative for German students, as it is a very playful introduction to programming with lots of examples.
    
+
    
+
    
+
    
+
    
+
    
+
    
+
    More Literature
    
+
    For more interesting literature, take a look at the literature list of this course.
    
+
+
+
    
+
+    
    
+  
    
+
+  
+  
+  
+  
+  
+  
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+  
+  
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+  
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+    
+    
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+
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+
+
+
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+
+
+
+
+Tutorial II.I - Lists and Tuples – Programming: Everyday Decision-Making Algorithms
+
+
+
+
+
+
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+
+
+
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+
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+  
    
+  
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+  
+
    
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+    
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+
    
+
+
    
+
    
+
    Tutorial II.I - Lists and Tuples
    
+
    Programming: Everyday Decision-Making Algorithms
    
+
    
+
+
+
+
    
+
+    
+  
+    
+  
    
+  
+
+
+
    
+
+
+
    
+
    Introduction
    
+
    When deciding where to eat, we often face a dilemma: should we go to our favorite restaurant (exploit) or try somewhere new (explore)? This is a perfect example of the explore-exploit trade-off! To help us analyze this problem, we need to learn about lists and tuples in Python.
    
+
      
+
    • Lists are like our dining history - we can add new restaurants and remove ones we don’t like
      • 
+
    • Tuples are like a restaurant’s fixed menu - once set, it doesn’t change
      • 
+
    
+
    Let’s learn these concepts by helping a food critic make better restaurant decisions!
    
+
    
+
    
+
    
+
+
    
+
    
+Note
+
    
+
    
+
    
+
    If a cell is marked with YOUR CODE BELOW, you are expected to write your code in that cell.
    
+
    
+
    
+
    
+
    
+
    Section 1 - Lists
    
+
    Lists in Python are ordered collections of items that can be modified. Think of them as a restaurant review notebook where each page can be added, removed, or edited. Lists are created using square brackets [] and can contain any type of data (numbers, strings, even other lists!). They are fundamental data structures in Python that help us organize and manage collections of data. They’re particularly useful for our restaurant decision-making scenario as they allow us to:
    
+
      
+
    • Track multiple restaurants in a single variable
      • 
+
    • Modify our preferences over time
      • 
+
    • Access restaurants by their position in our list
      • 
+
    
+
    Here are some examples:
    
+
    
+
    # Creating a list of restaurant ratings
+ratings = [4.5, 3.8, 4.2, 4.7, 3.9]
+
+# Creating a list of restaurant names
+restaurants = ["Pasta Place", "Sushi Bar", "Burger Joint"]
+
+# Creating a mixed list (not recommended, but possible)
+mixed_data = ["Pasta Place", 4.5, True]
    
+
    
+
    
+
    Working with Lists
    
+
    Lists are flexible. Here are the most common operations:
    
+
      
+
    1. Adding items (like discovering a new restaurant):
+
        
+
      • append() adds to the end
        • 
+
      • insert() adds at a specific position
        • 
+
      2. 
+
    
+
    
+
    # Adding a new restaurant
+restaurants = ["Pasta Place", "Sushi Bar"]
+restaurants.append("Pizza Palace") # Adds to the end
+print(restaurants)
+
+# You can also insert at a specific position
+restaurants.insert(1, "Taco Shop") # Adds at position 1
+print(restaurants) # ["Pasta Place", "Taco Shop", "Sushi Bar", "Pizza Palace"]
    
+
    
+
    ['Pasta Place', 'Sushi Bar', 'Pizza Palace']
+['Pasta Place', 'Taco Shop', 'Sushi Bar', 'Pizza Palace']
    
+
    
+
    
+
      
+
    1. Removing items (like removing a restaurant you don’t like):
+
        
+
      • pop() removes the last item
        • 
+
      • remove() removes a specific item
        • 
+
      2. 
+
    
+
    
+
    # Removing the last restaurant
+restaurants = ["Pasta Place", "Taco Shop", "Sushi Bar", "Pizza Palace"]
+restaurants.pop() # Removes and returns the last item
+print(restaurants)
+
+# Removing a specific item
+restaurants.remove("Pasta Place") 
+print(restaurants)
    
+
    
+
    ['Pasta Place', 'Taco Shop', 'Sushi Bar']
+['Taco Shop', 'Sushi Bar']
    
+
    
+
    
+
      
+
    1. Accessing items (like looking up a restaurant by position):
+
        
+
      • [0] gives you the first item
        • 
+
      • [1:3] gives you items second and third
        • 
+
      • [-1] gives you the last item
        • 
+
      2. 
+
    
+
    
+
    restaurants = ["Pasta Place", "Sushi Bar", "Burger Joint"]
+first_choice = restaurants[0] # Gets "Pasta Place"
+last_choice = restaurants[-1] # Gets "Burger Joint"
+some_choices = restaurants[0:2] # Gets ["Pasta Place", "Sushi Bar"]
    
+
    
+
    
+
    
+
    
+
+
    
+
    
+Tip
+
    
+
    
+
    
+
    In Python, we start counting positions from 0, not 1. So restaurants[0] gives you the first restaurant!
    
+
    
+
    
+
    
+
    
+
    Exercise 1.1 - Create a Restaurant List
    
+
    reate a list favorite_spots with your top three favorite restaurants. Remember to:
    
+
      
+
    • Use square brackets []
      • 
+
    • Put restaurant names in quotes (they’re strings!)
      • 
+
    • Separate items with commas
      • 
+
    
+
    
+
    # YOUR CODE BELOW
    
+
    
+
    
+
    
+Code
+
    # Test your answer
+assert len(favorite_spots) == 3, "You should have exactly 3 restaurants"
+assert isinstance(favorite_spots, list), "favorite_spots should be a list"
+assert all(isinstance(x, str) for x in favorite_spots), "All items should be strings"
+print("Your favorite restaurants:", favorite_spots)
    
+
    
+
    
+
    
+
    
+
    Exercise 1.2 - Add a New Discovery
    
+
    You’ve discovered a new restaurant called “The Golden Fork”. Add it to your favorite_spots list using the append() method. Think of this as writing a new entry in your restaurant diary!
    
+
    
+
    # YOUR CODE BELOW
    
+
    
+
    
+
    
+Code
+
    # Test your answer
+assert "The Golden Fork" in favorite_spots, "The Golden Fork should be in the list"
+assert len(favorite_spots) == 4, "You should now have 4 restaurants"
+print("Updated restaurant list:", favorite_spots)
    
+
    
+
    
+
    
+
    
+
    Exercise 1.3 - Remove a Restaurant
    
+
    The last restaurant in your list closed down. Remove it using the pop() method.
    
+
    
+
    # YOUR CODE BELOW
    
+
    
+
    
+
    
+Code
+
    # Test your answer
+assert "The Golden Fork" not in favorite_spots, "The Golden Fork should be removed"
+assert len(favorite_spots) == 3, "You should now have 3 restaurants"
+print("Updated restaurant list:", favorite_spots)
    
+
    
+
    
+
    
+
    
+
    
+
    Section 2 - Nested Lists
    
+
    Sometimes we need to store multiple pieces of information about each restaurant. We can use lists inside lists (nested lists) for this! Think of it as a detailed restaurant spreadsheet:
    
+
    
+
    # Restaurant data: [name, rating, times_visited]
+restaurant_data = [
+["Pasta Place", 4.5, 3], # Each inner list is one restaurant's data
+["Sushi Bar", 4.2, 1],
+["Burger Joint", 3.8, 2]
+]
+
+# To access data:
+first_restaurant_name = restaurant_data[0][0] # "Pasta Place"
+first_restaurant_rating = restaurant_data[0][1] # 4.5
+first_restaurant_visits = restaurant_data[0][2] # 3
    
+
    
+
    
+
    
+
    
+
+
    
+
    
+Tip
+
    
+
    
+
    
+
    When accessing nested lists, the first [] selects the outer list item, and the second [] selects from within that item. Like finding a page in a book (first number) and then a paragraph on that page (second number).
    
+
    
+
    
+
    
+
    Exercise 2.1 - Access Restaurant Info
    
+
    Using the restaurant_data list above, create variables best_restaurant and best_rating containing the name and rating of the restaurant with the highest rating. You’ll need to:
    
+
      
+
    1. Look at each restaurant’s rating (position 1 in each inner list)
      2. 
+
    2. Keep track of the highest rating and its restaurant name
      3. 
+
    
+
    
+
    restaurant_data = [
+    ["Pasta Place", 4.5, 3],
+    ["Sushi Bar", 4.2, 1],
+    ["Burger Joint", 3.8, 2]
+]
+# YOUR CODE BELOW
    
+
    
+
    
+
    
+Code
+
    # Test your answer
+assert best_restaurant == "Pasta Place", "Should be the restaurant with highest rating"
+assert best_rating == 4.5, "Should be the highest rating"
+print(f"The best restaurant is {best_restaurant} with a rating of {best_rating}")
    
+
    
+
    
+
    
+
    
+
    
+
    Exercise 2.2 - Create a Categorized Restaurant List
    
+
    Create a nested list categorized_restaurants where each inner list contains: 1. Two cuisine categories - here "Italian" and "Japanese" 2. A list of restaurant names with two entries for each category
    
+
    
+
    # Example structure:
+# [
+#    ["German", ["Brauhaus", "Bierhaus"]],
+#    ["Swedish", ["Fika", "Ivar's"]]
+# ]
+
+# YOUR CODE BELOW
    
+
    
+
    
+
    
+Code
+
    # Test your answer
+assert isinstance(categorized_restaurants, list), "Should be a list"
+assert all(len(x) == 2 for x in categorized_restaurants), "Each list should have 2 elements, first is cuisine, second is list of restaurants"
+assert all(isinstance(x[0], str) for x in categorized_restaurants), "Categories should be strings"
+assert all(isinstance(x[1], list) for x in categorized_restaurants), "Restaurant lists should be lists"
+print("Your categorized restaurants:", categorized_restaurants)
    
+
    
+
    
+
    
+
    
+
    Section 3 - Tuples for Fixed Data
    
+
    While lists are great for data that changes (like your favorite restaurants), sometimes we need to store data that shouldn’t change (like a restaurant’s location or founding date). That’s where tuples come in! Tuples are like lists but immutable (unchangeable). They use parentheses () instead of square brackets []:
    
+
    
+
    # Restaurant info that won't change
+restaurant_info = ("Pasta Place", "Italian", "Downtown")
+name = restaurant_info[0]  # Access like lists
+cuisine = restaurant_info[1]
+location = restaurant_info[2]
    
+
    
+
    
+
    Why use tuples?
    
+
      
+
    1. They protect data that shouldn’t change
      2. 
+
    2. They use less memory than lists
      3. 
+
    3. They can be used as dictionary keys (which we’ll learn about later)
      4. 
+
    
+
    
+
    
+
    
+
+
    
+
    
+Tip
+
    
+
    
+
    
+
    Think of tuples as sealed envelopes - once you seal them, you can’t change what’s inside. Lists are like notebooks where you can add or remove pages.
    
+
    
+
    
+
    
+
    
+
    Exercise 3.1 - Create Restaurant Profile
    
+
    Create a tuple restaurant_profile with three elements: restaurant name, cuisine type, and founding year. You can freely choose the values for these elements, just make sure they are of the correct type.
    
+
    
+
    # YOUR CODE BELOW
    
+
    
+
    
+
    
+Code
+
    # Test your answer
+assert isinstance(restaurant_profile, tuple), "Should be a tuple"
+assert len(restaurant_profile) == 3, "Should have exactly 3 elements"
+assert isinstance(restaurant_profile[0], str), "First element should be a string (name)"
+assert isinstance(restaurant_profile[1], str), "Second element should be a string (cuisine)"
+assert isinstance(restaurant_profile[2], int), "Third element should be an integer (year)"
+print("Restaurant profile:", restaurant_profile)
    
+
    
+
    
+
    
+
    
+
    
+
    Conclusion
    
+
    Great work! You’ve learned about lists and tuples in Python through the lens of restaurant decision-making. These tools are essential for:
    
+
      
+
    • Tracking your favorite restaurants (lists)
      • 
+
    • Managing ratings and visits (nested lists)
      • 
+
    • Storing fixed restaurant information (tuples)
      • 
+
    
+
    In the context of the explore-exploit trade-off:
    
+
      
+
    • Lists could help us track our exploration (new restaurants we try)
      • 
+
    • Nested lists could help us make informed decisions (by storing ratings and visit counts)
      • 
+
    • Tuples could help us remember important fixed information about each place
      • 
+
    
+
    
+
    
+
    Solutions
    
+
    You will likely find solutions to most exercises online. However, we strongly encourage you to work on these exercises independently without searching explicitly for the exact answers to the exercises. Understanding someone else’s solution is very different from developing your own. Use the lecture notes and try to solve the exercises on your own. This approach will significantly enhance your learning and problem-solving skills.
    
+
    Remember, the goal is not just to complete the exercises, but to understand the concepts and improve your programming abilities. If you encounter difficulties, review the lecture materials, experiment with different approaches, and don’t hesitate to ask for clarification during class discussions.
    
+
    Later, you will find the solutions to these exercises online in the associated GitHub repository, but we will also quickly go over them next week. To access the solutions, click on the Github button on the lower right and search for the folder with today’s lecture and tutorial. Alternatively, you can ask ChatGPT or Claude to explain them to you. But please remember, the goal is not just to complete the exercises, but to understand the concepts and improve your programming abilities.
    
+
    
+
    Continue to the next tutorial to learn about loops in the context of the explore-exploit problem!
    
+
+
+
    
+
+
     
+
+
     
+
+
+
+
+
+
\ No newline at end of file
diff --git a/part-02/tutorial-04-lists 3.ipynb b/part-02/tutorial-04-lists 3.ipynb
new file mode 100644
index 0000000..1eb94c6
--- /dev/null
+++ b/part-02/tutorial-04-lists 3.ipynb	
@@ -0,0 +1,557 @@
+{
+  "cells": [
+    {
+      "cell_type": "markdown",
+      "metadata": {},
+      "source": [
+        "# Tutorial II.I - Lists and Tuples\n",
+        "\n",
+        "Programming: Everyday Decision-Making Algorithms\n",
+        "\n",
+        "# Introduction\n",
+        "\n",
+        "When deciding where to eat, we often face a dilemma: should we go to our\n",
+        "favorite restaurant (exploit) or try somewhere new (explore)? This is a\n",
+        "perfect example of the explore-exploit trade-off! To help us analyze\n",
+        "this problem, we need to learn about lists and tuples in Python.\n",
+        "\n",
+        "-   Lists are like our dining history - we can add new restaurants and\n",
+        "    remove ones we don’t like\n",
+        "-   Tuples are like a restaurant’s fixed menu - once set, it doesn’t\n",
+        "    change\n",
+        "\n",
+        "Let’s learn these concepts by helping a food critic make better\n",
+        "restaurant decisions!\n",
+        "\n",
+        "> **Note**\n",
+        ">\n",
+        "> If a cell is marked with `YOUR CODE BELOW`, you are expected to write\n",
+        "> your code in that cell.\n",
+        "\n",
+        "# Section 1 - Lists\n",
+        "\n",
+        "Lists in Python are ordered collections of items that can be modified.\n",
+        "Think of them as a restaurant review notebook where each page can be\n",
+        "added, removed, or edited. Lists are created using square brackets `[]`\n",
+        "and can contain any type of data (numbers, strings, even other lists!).\n",
+        "They are fundamental data structures in Python that help us organize and\n",
+        "manage collections of data. They’re particularly useful for our\n",
+        "restaurant decision-making scenario as they allow us to:\n",
+        "\n",
+        "-   Track multiple restaurants in a single variable\n",
+        "-   Modify our preferences over time\n",
+        "-   Access restaurants by their position in our list\n",
+        "\n",
+        "Here are some examples:"
+      ],
+      "id": "b95673c1-f6b0-42b6-be09-03349e928967"
+    },
+    {
+      "cell_type": "code",
+      "execution_count": 1,
+      "metadata": {},
+      "outputs": [],
+      "source": [
+        "# Creating a list of restaurant ratings\n",
+        "ratings = [4.5, 3.8, 4.2, 4.7, 3.9]\n",
+        "\n",
+        "# Creating a list of restaurant names\n",
+        "restaurants = [\"Pasta Place\", \"Sushi Bar\", \"Burger Joint\"]\n",
+        "\n",
+        "# Creating a mixed list (not recommended, but possible)\n",
+        "mixed_data = [\"Pasta Place\", 4.5, True]"
+      ],
+      "id": "ebbae872"
+    },
+    {
+      "cell_type": "markdown",
+      "metadata": {},
+      "source": [
+        "## Working with Lists\n",
+        "\n",
+        "Lists are flexible. Here are the most common operations:\n",
+        "\n",
+        "1.  **Adding items** (like discovering a new restaurant):\n",
+        "    -   `append()` adds to the end\n",
+        "    -   `insert()` adds at a specific position"
+      ],
+      "id": "b4c609e8-5991-4b71-b4e4-ffbd478d53ad"
+    },
+    {
+      "cell_type": "code",
+      "execution_count": 2,
+      "metadata": {},
+      "outputs": [
+        {
+          "output_type": "stream",
+          "name": "stdout",
+          "text": [
+            "['Pasta Place', 'Sushi Bar', 'Pizza Palace']\n",
+            "['Pasta Place', 'Taco Shop', 'Sushi Bar', 'Pizza Palace']"
+          ]
+        }
+      ],
+      "source": [
+        "# Adding a new restaurant\n",
+        "restaurants = [\"Pasta Place\", \"Sushi Bar\"]\n",
+        "restaurants.append(\"Pizza Palace\") # Adds to the end\n",
+        "print(restaurants)\n",
+        "\n",
+        "# You can also insert at a specific position\n",
+        "restaurants.insert(1, \"Taco Shop\") # Adds at position 1\n",
+        "print(restaurants) # [\"Pasta Place\", \"Taco Shop\", \"Sushi Bar\", \"Pizza Palace\"]"
+      ],
+      "id": "65eb108e"
+    },
+    {
+      "cell_type": "markdown",
+      "metadata": {},
+      "source": [
+        "1.  **Removing items** (like removing a restaurant you don’t like):\n",
+        "    -   `pop()` removes the last item\n",
+        "    -   `remove()` removes a specific item"
+      ],
+      "id": "d9d6143b-0e3d-48bb-8667-f149031e8455"
+    },
+    {
+      "cell_type": "code",
+      "execution_count": 3,
+      "metadata": {},
+      "outputs": [
+        {
+          "output_type": "stream",
+          "name": "stdout",
+          "text": [
+            "['Pasta Place', 'Taco Shop', 'Sushi Bar']\n",
+            "['Taco Shop', 'Sushi Bar']"
+          ]
+        }
+      ],
+      "source": [
+        "# Removing the last restaurant\n",
+        "restaurants = [\"Pasta Place\", \"Taco Shop\", \"Sushi Bar\", \"Pizza Palace\"]\n",
+        "restaurants.pop() # Removes and returns the last item\n",
+        "print(restaurants)\n",
+        "\n",
+        "# Removing a specific item\n",
+        "restaurants.remove(\"Pasta Place\") \n",
+        "print(restaurants)"
+      ],
+      "id": "025b7104"
+    },
+    {
+      "cell_type": "markdown",
+      "metadata": {},
+      "source": [
+        "1.  **Accessing items** (like looking up a restaurant by position):\n",
+        "    -   `[0]` gives you the first item\n",
+        "    -   `[1:3]` gives you items second and third\n",
+        "    -   `[-1]` gives you the last item"
+      ],
+      "id": "de31114a-e3e6-4d0a-ae46-411ca5e3536d"
+    },
+    {
+      "cell_type": "code",
+      "execution_count": 4,
+      "metadata": {},
+      "outputs": [],
+      "source": [
+        "restaurants = [\"Pasta Place\", \"Sushi Bar\", \"Burger Joint\"]\n",
+        "first_choice = restaurants[0] # Gets \"Pasta Place\"\n",
+        "last_choice = restaurants[-1] # Gets \"Burger Joint\"\n",
+        "some_choices = restaurants[0:2] # Gets [\"Pasta Place\", \"Sushi Bar\"]"
+      ],
+      "id": "d847d205"
+    },
+    {
+      "cell_type": "markdown",
+      "metadata": {},
+      "source": [
+        "> **Tip**\n",
+        ">\n",
+        "> In Python, we start counting positions from 0, not 1. So\n",
+        "> `restaurants[0]` gives you the first restaurant!\n",
+        "\n",
+        "## Exercise 1.1 - Create a Restaurant List\n",
+        "\n",
+        "reate a list `favorite_spots` with your top three favorite restaurants.\n",
+        "Remember to:\n",
+        "\n",
+        "-   Use square brackets `[]`\n",
+        "-   Put restaurant names in quotes (they’re strings!)\n",
+        "-   Separate items with commas"
+      ],
+      "id": "5d3f3432-8fa4-4be9-a1ff-8aa39fa3bbe1"
+    },
+    {
+      "cell_type": "code",
+      "execution_count": 5,
+      "metadata": {},
+      "outputs": [],
+      "source": [
+        "# YOUR CODE BELOW"
+      ],
+      "id": "363a27a9"
+    },
+    {
+      "cell_type": "code",
+      "execution_count": 6,
+      "metadata": {},
+      "outputs": [],
+      "source": [
+        "# Test your answer\n",
+        "assert len(favorite_spots) == 3, \"You should have exactly 3 restaurants\"\n",
+        "assert isinstance(favorite_spots, list), \"favorite_spots should be a list\"\n",
+        "assert all(isinstance(x, str) for x in favorite_spots), \"All items should be strings\"\n",
+        "print(\"Your favorite restaurants:\", favorite_spots)"
+      ],
+      "id": "7534642b"
+    },
+    {
+      "cell_type": "markdown",
+      "metadata": {},
+      "source": [
+        "## Exercise 1.2 - Add a New Discovery\n",
+        "\n",
+        "You’ve discovered a new restaurant called “The Golden Fork”. Add it to\n",
+        "your `favorite_spots` list using the `append()` method. Think of this as\n",
+        "writing a new entry in your restaurant diary!"
+      ],
+      "id": "f6ff43e1-8d13-4f6b-b632-ed8dcd73db32"
+    },
+    {
+      "cell_type": "code",
+      "execution_count": 7,
+      "metadata": {},
+      "outputs": [],
+      "source": [
+        "# YOUR CODE BELOW"
+      ],
+      "id": "2a00708e"
+    },
+    {
+      "cell_type": "code",
+      "execution_count": 8,
+      "metadata": {},
+      "outputs": [],
+      "source": [
+        "# Test your answer\n",
+        "assert \"The Golden Fork\" in favorite_spots, \"The Golden Fork should be in the list\"\n",
+        "assert len(favorite_spots) == 4, \"You should now have 4 restaurants\"\n",
+        "print(\"Updated restaurant list:\", favorite_spots)"
+      ],
+      "id": "a70d9679"
+    },
+    {
+      "cell_type": "markdown",
+      "metadata": {},
+      "source": [
+        "## Exercise 1.3 - Remove a Restaurant\n",
+        "\n",
+        "The last restaurant in your list closed down. Remove it using the\n",
+        "`pop()` method."
+      ],
+      "id": "7b081d3d-e783-4c58-bdcc-3f4e33cc3cd5"
+    },
+    {
+      "cell_type": "code",
+      "execution_count": 9,
+      "metadata": {},
+      "outputs": [],
+      "source": [
+        "# YOUR CODE BELOW"
+      ],
+      "id": "a452e549"
+    },
+    {
+      "cell_type": "code",
+      "execution_count": 10,
+      "metadata": {},
+      "outputs": [],
+      "source": [
+        "# Test your answer\n",
+        "assert \"The Golden Fork\" not in favorite_spots, \"The Golden Fork should be removed\"\n",
+        "assert len(favorite_spots) == 3, \"You should now have 3 restaurants\"\n",
+        "print(\"Updated restaurant list:\", favorite_spots)"
+      ],
+      "id": "48ccc964"
+    },
+    {
+      "cell_type": "markdown",
+      "metadata": {},
+      "source": [
+        "# Section 2 - Nested Lists\n",
+        "\n",
+        "Sometimes we need to store multiple pieces of information about each\n",
+        "restaurant. We can use lists inside lists (nested lists) for this! Think\n",
+        "of it as a detailed restaurant spreadsheet:"
+      ],
+      "id": "69d8ee2a-97a9-4915-8575-2da4ed654e8d"
+    },
+    {
+      "cell_type": "code",
+      "execution_count": 11,
+      "metadata": {},
+      "outputs": [],
+      "source": [
+        "# Restaurant data: [name, rating, times_visited]\n",
+        "restaurant_data = [\n",
+        "[\"Pasta Place\", 4.5, 3], # Each inner list is one restaurant's data\n",
+        "[\"Sushi Bar\", 4.2, 1],\n",
+        "[\"Burger Joint\", 3.8, 2]\n",
+        "]\n",
+        "\n",
+        "# To access data:\n",
+        "first_restaurant_name = restaurant_data[0][0] # \"Pasta Place\"\n",
+        "first_restaurant_rating = restaurant_data[0][1] # 4.5\n",
+        "first_restaurant_visits = restaurant_data[0][2] # 3"
+      ],
+      "id": "a283c308"
+    },
+    {
+      "cell_type": "markdown",
+      "metadata": {},
+      "source": [
+        "> **Tip**\n",
+        ">\n",
+        "> When accessing nested lists, the first `[]` selects the outer list\n",
+        "> item, and the second `[]` selects from within that item. Like finding\n",
+        "> a page in a book (first number) and then a paragraph on that page\n",
+        "> (second number).\n",
+        "\n",
+        "## Exercise 2.1 - Access Restaurant Info\n",
+        "\n",
+        "Using the `restaurant_data` list above, create variables\n",
+        "`best_restaurant` and `best_rating` containing the name and rating of\n",
+        "the restaurant with the highest rating. You’ll need to:\n",
+        "\n",
+        "1.  Look at each restaurant’s rating (position 1 in each inner list)\n",
+        "2.  Keep track of the highest rating and its restaurant name"
+      ],
+      "id": "f1db90bf-593d-477b-b27f-003ab5900d40"
+    },
+    {
+      "cell_type": "code",
+      "execution_count": 12,
+      "metadata": {},
+      "outputs": [],
+      "source": [
+        "restaurant_data = [\n",
+        "    [\"Pasta Place\", 4.5, 3],\n",
+        "    [\"Sushi Bar\", 4.2, 1],\n",
+        "    [\"Burger Joint\", 3.8, 2]\n",
+        "]\n",
+        "# YOUR CODE BELOW"
+      ],
+      "id": "107c7ce8"
+    },
+    {
+      "cell_type": "code",
+      "execution_count": 13,
+      "metadata": {},
+      "outputs": [],
+      "source": [
+        "# Test your answer\n",
+        "assert best_restaurant == \"Pasta Place\", \"Should be the restaurant with highest rating\"\n",
+        "assert best_rating == 4.5, \"Should be the highest rating\"\n",
+        "print(f\"The best restaurant is {best_restaurant} with a rating of {best_rating}\")"
+      ],
+      "id": "e8be33a1"
+    },
+    {
+      "cell_type": "markdown",
+      "metadata": {},
+      "source": [
+        "# Exercise 2.2 - Create a Categorized Restaurant List\n",
+        "\n",
+        "Create a nested list `categorized_restaurants` where each inner list\n",
+        "contains: 1. Two cuisine categories - here `\"Italian\"` and `\"Japanese\"`\n",
+        "2. A list of restaurant names with two entries for each category"
+      ],
+      "id": "0657870a-c0f4-4a90-b69d-44a5adbc3ab6"
+    },
+    {
+      "cell_type": "code",
+      "execution_count": 14,
+      "metadata": {},
+      "outputs": [],
+      "source": [
+        "# Example structure:\n",
+        "# [\n",
+        "#    [\"German\", [\"Brauhaus\", \"Bierhaus\"]],\n",
+        "#    [\"Swedish\", [\"Fika\", \"Ivar's\"]]\n",
+        "# ]\n",
+        "\n",
+        "# YOUR CODE BELOW"
+      ],
+      "id": "54cca2bf"
+    },
+    {
+      "cell_type": "code",
+      "execution_count": 15,
+      "metadata": {},
+      "outputs": [],
+      "source": [
+        "# Test your answer\n",
+        "assert isinstance(categorized_restaurants, list), \"Should be a list\"\n",
+        "assert all(len(x) == 2 for x in categorized_restaurants), \"Each list should have 2 elements, first is cuisine, second is list of restaurants\"\n",
+        "assert all(isinstance(x[0], str) for x in categorized_restaurants), \"Categories should be strings\"\n",
+        "assert all(isinstance(x[1], list) for x in categorized_restaurants), \"Restaurant lists should be lists\"\n",
+        "print(\"Your categorized restaurants:\", categorized_restaurants)"
+      ],
+      "id": "1d7a9783"
+    },
+    {
+      "cell_type": "markdown",
+      "metadata": {},
+      "source": [
+        "# Section 3 - Tuples for Fixed Data\n",
+        "\n",
+        "While lists are great for data that changes (like your favorite\n",
+        "restaurants), sometimes we need to store data that shouldn’t change\n",
+        "(like a restaurant’s location or founding date). That’s where tuples\n",
+        "come in! Tuples are like lists but immutable (unchangeable). They use\n",
+        "parentheses `()` instead of square brackets `[]`:"
+      ],
+      "id": "2694a1ca-d65b-498a-8f43-79e01ad4830f"
+    },
+    {
+      "cell_type": "code",
+      "execution_count": 16,
+      "metadata": {},
+      "outputs": [],
+      "source": [
+        "# Restaurant info that won't change\n",
+        "restaurant_info = (\"Pasta Place\", \"Italian\", \"Downtown\")\n",
+        "name = restaurant_info[0]  # Access like lists\n",
+        "cuisine = restaurant_info[1]\n",
+        "location = restaurant_info[2]"
+      ],
+      "id": "a7e0e8e1"
+    },
+    {
+      "cell_type": "markdown",
+      "metadata": {},
+      "source": [
+        "## Why use tuples?\n",
+        "\n",
+        "1.  They protect data that shouldn’t change\n",
+        "2.  They use less memory than lists\n",
+        "3.  They can be used as dictionary keys (which we’ll learn about later)\n",
+        "\n",
+        "> **Tip**\n",
+        ">\n",
+        "> Think of tuples as sealed envelopes - once you seal them, you can’t\n",
+        "> change what’s inside. Lists are like notebooks where you can add or\n",
+        "> remove pages.\n",
+        "\n",
+        "## Exercise 3.1 - Create Restaurant Profile\n",
+        "\n",
+        "Create a tuple `restaurant_profile` with three elements: restaurant\n",
+        "name, cuisine type, and founding year. You can freely choose the values\n",
+        "for these elements, just make sure they are of the correct type."
+      ],
+      "id": "f686cb07-4686-40eb-b53e-3039446dc48f"
+    },
+    {
+      "cell_type": "code",
+      "execution_count": 17,
+      "metadata": {},
+      "outputs": [],
+      "source": [
+        "# YOUR CODE BELOW"
+      ],
+      "id": "3e71f75f"
+    },
+    {
+      "cell_type": "code",
+      "execution_count": 18,
+      "metadata": {},
+      "outputs": [],
+      "source": [
+        "# Test your answer\n",
+        "assert isinstance(restaurant_profile, tuple), \"Should be a tuple\"\n",
+        "assert len(restaurant_profile) == 3, \"Should have exactly 3 elements\"\n",
+        "assert isinstance(restaurant_profile[0], str), \"First element should be a string (name)\"\n",
+        "assert isinstance(restaurant_profile[1], str), \"Second element should be a string (cuisine)\"\n",
+        "assert isinstance(restaurant_profile[2], int), \"Third element should be an integer (year)\"\n",
+        "print(\"Restaurant profile:\", restaurant_profile)"
+      ],
+      "id": "0f39450f"
+    },
+    {
+      "cell_type": "markdown",
+      "metadata": {},
+      "source": [
+        "# Conclusion\n",
+        "\n",
+        "Great work! You’ve learned about lists and tuples in Python through the\n",
+        "lens of restaurant decision-making. These tools are essential for:\n",
+        "\n",
+        "-   Tracking your favorite restaurants (lists)\n",
+        "-   Managing ratings and visits (nested lists)\n",
+        "-   Storing fixed restaurant information (tuples)\n",
+        "\n",
+        "In the context of the explore-exploit trade-off:\n",
+        "\n",
+        "-   Lists could help us track our exploration (new restaurants we try)\n",
+        "-   Nested lists could help us make informed decisions (by storing\n",
+        "    ratings and visit counts)\n",
+        "-   Tuples could help us remember important fixed information about each\n",
+        "    place\n",
+        "\n",
+        "# Solutions\n",
+        "\n",
+        "You will likely find solutions to most exercises online. However, we\n",
+        "strongly encourage you to work on these exercises independently without\n",
+        "searching explicitly for the exact answers to the exercises.\n",
+        "Understanding someone else’s solution is very different from developing\n",
+        "your own. Use the lecture notes and try to solve the exercises on your\n",
+        "own. This approach will significantly enhance your learning and\n",
+        "problem-solving skills.\n",
+        "\n",
+        "Remember, the goal is not just to complete the exercises, but to\n",
+        "understand the concepts and improve your programming abilities. If you\n",
+        "encounter difficulties, review the lecture materials, experiment with\n",
+        "different approaches, and don’t hesitate to ask for clarification during\n",
+        "class discussions.\n",
+        "\n",
+        "Later, you will find the solutions to these exercises online in the\n",
+        "associated GitHub repository, but we will also quickly go over them next\n",
+        "week. To access the solutions, click on the Github button on the lower\n",
+        "right and search for the folder with today’s lecture and tutorial.\n",
+        "Alternatively, you can ask ChatGPT or Claude to explain them to you. But\n",
+        "please remember, the goal is not just to complete the exercises, but to\n",
+        "understand the concepts and improve your programming abilities.\n",
+        "\n",
+        "------------------------------------------------------------------------\n",
+        "\n",
+        "*Continue to the next tutorial to learn about loops in the context of\n",
+        "the explore-exploit problem!*"
+      ],
+      "id": "6e18a915-51e7-4b0f-8357-aecc2fa689bf"
+    }
+  ],
+  "nbformat": 4,
+  "nbformat_minor": 5,
+  "metadata": {
+    "kernelspec": {
+      "name": "python3",
+      "display_name": "Python 3 (ipykernel)",
+      "language": "python",
+      "path": "/Users/tvlcek/miniconda3/share/jupyter/kernels/python3"
+    },
+    "language_info": {
+      "name": "python",
+      "codemirror_mode": {
+        "name": "ipython",
+        "version": "3"
+      },
+      "file_extension": ".py",
+      "mimetype": "text/x-python",
+      "nbconvert_exporter": "python",
+      "pygments_lexer": "ipython3",
+      "version": "3.12.7"
+    }
+  }
+}
\ No newline at end of file
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  06 - Exploration
   
    
+
+      
+  
+        
  • 
+      
     
+            
+           
+      
    
+      
   
    • 
@@ -331,7 +366,7 @@ 
    Section 1 - Lists
    
 
  • Access restaurants by their position in our list
    • 
 
 
    Here are some examples:
    
-
    
+
    
 
    # Creating a list of restaurant ratings
 ratings = [4.5, 3.8, 4.2, 4.7, 3.9]
 
@@ -351,7 +386,7 @@ 
    Working with Lists
    
 
  • insert() adds at a specific position
    • 
 
 
-
    
+
    
 
    # Adding a new restaurant
 restaurants = ["Pasta Place", "Sushi Bar"]
 restaurants.append("Pizza Palace") # Adds to the end
@@ -372,7 +407,7 @@ 
    Working with Lists
    
 
  • remove() removes a specific item
    • 
 
 
-
    
+
    
 
    # Removing the last restaurant
 restaurants = ["Pasta Place", "Taco Shop", "Sushi Bar", "Pizza Palace"]
 restaurants.pop() # Removes and returns the last item
@@ -394,7 +429,7 @@ 
    Working with Lists
    
 
  • [-1] gives you the last item
    • 
 
 
-
    
+
    
 
    restaurants = ["Pasta Place", "Sushi Bar", "Burger Joint"]
 first_choice = restaurants[0] # Gets "Pasta Place"
 last_choice = restaurants[-1] # Gets "Burger Joint"
@@ -422,10 +457,10 @@ 
    Ex
 
  • Put restaurant names in quotes (they’re strings!)
    • 
 
  • Separate items with commas
    • 
 
-
    
+
    
 
    # YOUR CODE BELOW
    
 
    
-
    
+
    
 
    
 Code
 
    # Test your answer
@@ -439,10 +474,10 @@ 
    Ex
 
    
 
    Exercise 1.2 - Add a New Discovery
    
 
    You’ve discovered a new restaurant called “The Golden Fork”. Add it to your favorite_spots list using the append() method. Think of this as writing a new entry in your restaurant diary!
    
-
    
+
    
 
    # YOUR CODE BELOW
    
 
    
-
    
+
    
 
    
 Code
 
    # Test your answer
@@ -455,10 +490,10 @@ 
    Exercis
 
    
 
    Exercise 1.3 - Remove a Restaurant
    
 
    The last restaurant in your list closed down. Remove it using the pop() method.
    
-
    
+
    
 
    # YOUR CODE BELOW
    
 
    
-
    
+
    
 
    
 Code
 
    # Test your answer
@@ -472,7 +507,7 @@ 
    Exercis
 
    
 
    Section 2 - Nested Lists
    
 
    Sometimes we need to store multiple pieces of information about each restaurant. We can use lists inside lists (nested lists) for this! Think of it as a detailed restaurant spreadsheet:
    
-
    
+
    
 
    # Restaurant data: [name, rating, times_visited]
 restaurant_data = [
 ["Pasta Place", 4.5, 3], # Each inner list is one restaurant's data
@@ -505,7 +540,7 @@ 
    Exer
 
  • Look at each restaurant’s rating (position 1 in each inner list)
    • 
 
  • Keep track of the highest rating and its restaurant name
    • 
 
-
    
+
    
 
    restaurant_data = [
     ["Pasta Place", 4.5, 3],
     ["Sushi Bar", 4.2, 1],
@@ -513,7 +548,7 @@ 
    Exer
 ]
 # YOUR CODE BELOW
    
 
    
-
    
+
    
 
    
 Code
 
    # Test your answer
@@ -527,7 +562,7 @@ 
    Exer
 
    
 
    Exercise 2.2 - Create a Categorized Restaurant List
    
 
    Create a nested list categorized_restaurants where each inner list contains: 1. Two cuisine categories - here "Italian" and "Japanese" 2. A list of restaurant names with two entries for each category
    
-
    
+
    
 
    # Example structure:
 # [
 #    ["German", ["Brauhaus", "Bierhaus"]],
@@ -536,7 +571,7 @@ 
    Exercise 2.2 - Create a Categorized Restaurant List
    
 
 # YOUR CODE BELOW
    
 
    
-
    
+
    
 
    
 Code
 
    # Test your answer
@@ -551,7 +586,7 @@ 
    Exercise 2.2 - Create a Categorized Restaurant List
    
 
    
 
    Section 3 - Tuples for Fixed Data
    
 
    While lists are great for data that changes (like your favorite restaurants), sometimes we need to store data that shouldn’t change (like a restaurant’s location or founding date). That’s where tuples come in! Tuples are like lists but immutable (unchangeable). They use parentheses () instead of square brackets []:
    
-
    
+
    
 
    # Restaurant info that won't change
 restaurant_info = ("Pasta Place", "Italian", "Downtown")
 name = restaurant_info[0]  # Access like lists
@@ -582,10 +617,10 @@ 
    Why use tuples?
    
 
    
 
    Exercise 3.1 - Create Restaurant Profile
    
 
    Create a tuple restaurant_profile with three elements: restaurant name, cuisine type, and founding year. You can freely choose the values for these elements, just make sure they are of the correct type.
    
-
    
+
    
 
    # YOUR CODE BELOW
    
 
    
-
    
+
    
 
    
 Code
 
    # Test your answer
diff --git a/part-02/tutorial-04-lists.ipynb b/part-02/tutorial-04-lists.ipynb
index 00ead03..c354411 100644
--- a/part-02/tutorial-04-lists.ipynb
+++ b/part-02/tutorial-04-lists.ipynb
@@ -44,7 +44,7 @@
         "\n",
         "Here are some examples:"
       ],
-      "id": "001c9268-bffa-4090-bf12-2614aa2eae4b"
+      "id": "70f4dd48-647f-4cfc-84ae-2f38ccaed6b5"
     },
     {
       "cell_type": "code",
@@ -61,7 +61,7 @@
         "# Creating a mixed list (not recommended, but possible)\n",
         "mixed_data = [\"Pasta Place\", 4.5, True]"
       ],
-      "id": "93dc7e14"
+      "id": "514b5e7f"
     },
     {
       "cell_type": "markdown",
@@ -75,7 +75,7 @@
         "    -   `append()` adds to the end\n",
         "    -   `insert()` adds at a specific position"
       ],
-      "id": "74c28978-1bb1-4873-a069-bad645aae554"
+      "id": "1e7a0663-5642-4bb6-a874-d7ac709e4f8c"
     },
     {
       "cell_type": "code",
@@ -101,7 +101,7 @@
         "restaurants.insert(1, \"Taco Shop\") # Adds at position 1\n",
         "print(restaurants) # [\"Pasta Place\", \"Taco Shop\", \"Sushi Bar\", \"Pizza Palace\"]"
       ],
-      "id": "49dde3c9"
+      "id": "5e2e32f5"
     },
     {
       "cell_type": "markdown",
@@ -111,7 +111,7 @@
         "    -   `pop()` removes the last item\n",
         "    -   `remove()` removes a specific item"
       ],
-      "id": "4484a61c-bb6c-4e15-a49b-dcc59064af4c"
+      "id": "aca0737f-e168-479b-8098-9fbd72369514"
     },
     {
       "cell_type": "code",
@@ -137,7 +137,7 @@
         "restaurants.remove(\"Pasta Place\") \n",
         "print(restaurants)"
       ],
-      "id": "38fe35d1"
+      "id": "09f46f03"
     },
     {
       "cell_type": "markdown",
@@ -148,7 +148,7 @@
         "    -   `[1:3]` gives you items second and third\n",
         "    -   `[-1]` gives you the last item"
       ],
-      "id": "026b3ff0-7d78-4e4f-b1da-360df4627d76"
+      "id": "966c0c76-23f8-4131-8dba-29bec5673181"
     },
     {
       "cell_type": "code",
@@ -161,7 +161,7 @@
         "last_choice = restaurants[-1] # Gets \"Burger Joint\"\n",
         "some_choices = restaurants[0:2] # Gets [\"Pasta Place\", \"Sushi Bar\"]"
       ],
-      "id": "f32ef028"
+      "id": "5ec5e387"
     },
     {
       "cell_type": "markdown",
@@ -181,7 +181,7 @@
         "-   Put restaurant names in quotes (they’re strings!)\n",
         "-   Separate items with commas"
       ],
-      "id": "b329ccbc-4d33-49ba-82f8-7804192db6ee"
+      "id": "c7432de2-84c2-4a74-8c7b-0c1e00e7f273"
     },
     {
       "cell_type": "code",
@@ -191,7 +191,7 @@
       "source": [
         "# YOUR CODE BELOW"
       ],
-      "id": "18d3f732"
+      "id": "cb8db304"
     },
     {
       "cell_type": "code",
@@ -205,7 +205,7 @@
         "assert all(isinstance(x, str) for x in favorite_spots), \"All items should be strings\"\n",
         "print(\"Your favorite restaurants:\", favorite_spots)"
       ],
-      "id": "7be79ba2"
+      "id": "5f745f61"
     },
     {
       "cell_type": "markdown",
@@ -217,7 +217,7 @@
         "your `favorite_spots` list using the `append()` method. Think of this as\n",
         "writing a new entry in your restaurant diary!"
       ],
-      "id": "68c15658-c65c-44ed-a8e8-a93b88b7fa23"
+      "id": "b7c6d5ad-3daa-43a0-ac6b-1b477d9572e6"
     },
     {
       "cell_type": "code",
@@ -227,7 +227,7 @@
       "source": [
         "# YOUR CODE BELOW"
       ],
-      "id": "e1a6a29a"
+      "id": "e73cd532"
     },
     {
       "cell_type": "code",
@@ -240,7 +240,7 @@
         "assert len(favorite_spots) == 4, \"You should now have 4 restaurants\"\n",
         "print(\"Updated restaurant list:\", favorite_spots)"
       ],
-      "id": "9d886a94"
+      "id": "77983061"
     },
     {
       "cell_type": "markdown",
@@ -251,7 +251,7 @@
         "The last restaurant in your list closed down. Remove it using the\n",
         "`pop()` method."
       ],
-      "id": "890feb40-4aa5-4546-8402-e550f078ccb0"
+      "id": "04ecbe14-2ec8-47e2-8b17-75367c6cc777"
     },
     {
       "cell_type": "code",
@@ -261,7 +261,7 @@
       "source": [
         "# YOUR CODE BELOW"
       ],
-      "id": "46e30e34"
+      "id": "19c3a465"
     },
     {
       "cell_type": "code",
@@ -274,7 +274,7 @@
         "assert len(favorite_spots) == 3, \"You should now have 3 restaurants\"\n",
         "print(\"Updated restaurant list:\", favorite_spots)"
       ],
-      "id": "0678187a"
+      "id": "4d0bcbd8"
     },
     {
       "cell_type": "markdown",
@@ -286,7 +286,7 @@
         "restaurant. We can use lists inside lists (nested lists) for this! Think\n",
         "of it as a detailed restaurant spreadsheet:"
       ],
-      "id": "c047de97-ec17-4b40-9558-684c87ea7e43"
+      "id": "b9d4a400-1e03-48ad-9583-8be5a6f2f69d"
     },
     {
       "cell_type": "code",
@@ -306,7 +306,7 @@
         "first_restaurant_rating = restaurant_data[0][1] # 4.5\n",
         "first_restaurant_visits = restaurant_data[0][2] # 3"
       ],
-      "id": "63dfc6ec"
+      "id": "81f3e4c9"
     },
     {
       "cell_type": "markdown",
@@ -328,7 +328,7 @@
         "1.  Look at each restaurant’s rating (position 1 in each inner list)\n",
         "2.  Keep track of the highest rating and its restaurant name"
       ],
-      "id": "f468c719-e8b9-404d-9eb5-1232e5f4924c"
+      "id": "9c8b1548-a7b9-4591-97b2-baa816ebbbbf"
     },
     {
       "cell_type": "code",
@@ -343,7 +343,7 @@
         "]\n",
         "# YOUR CODE BELOW"
       ],
-      "id": "f52d6d51"
+      "id": "19b9d1e6"
     },
     {
       "cell_type": "code",
@@ -356,7 +356,7 @@
         "assert best_rating == 4.5, \"Should be the highest rating\"\n",
         "print(f\"The best restaurant is {best_restaurant} with a rating of {best_rating}\")"
       ],
-      "id": "4c750bbb"
+      "id": "7a44b61a"
     },
     {
       "cell_type": "markdown",
@@ -368,7 +368,7 @@
         "contains: 1. Two cuisine categories - here `\"Italian\"` and `\"Japanese\"`\n",
         "2. A list of restaurant names with two entries for each category"
       ],
-      "id": "158b997e-f784-4ccc-81b3-7fc91d77655f"
+      "id": "ee3d5cae-8a17-45cf-b26a-a86b20f68184"
     },
     {
       "cell_type": "code",
@@ -384,7 +384,7 @@
         "\n",
         "# YOUR CODE BELOW"
       ],
-      "id": "3745bd4d"
+      "id": "fb420c87"
     },
     {
       "cell_type": "code",
@@ -399,7 +399,7 @@
         "assert all(isinstance(x[1], list) for x in categorized_restaurants), \"Restaurant lists should be lists\"\n",
         "print(\"Your categorized restaurants:\", categorized_restaurants)"
       ],
-      "id": "764e4f82"
+      "id": "b5ca0f0c"
     },
     {
       "cell_type": "markdown",
@@ -413,7 +413,7 @@
         "come in! Tuples are like lists but immutable (unchangeable). They use\n",
         "parentheses `()` instead of square brackets `[]`:"
       ],
-      "id": "b25962a2-e9ac-4ab2-ba8c-770bc435403f"
+      "id": "74e36894-65ed-47b4-852d-ef426723e9e7"
     },
     {
       "cell_type": "code",
@@ -427,7 +427,7 @@
         "cuisine = restaurant_info[1]\n",
         "location = restaurant_info[2]"
       ],
-      "id": "e1398e98"
+      "id": "94ca9783"
     },
     {
       "cell_type": "markdown",
@@ -451,7 +451,7 @@
         "name, cuisine type, and founding year. You can freely choose the values\n",
         "for these elements, just make sure they are of the correct type."
       ],
-      "id": "3c5c5659-0657-45bf-9e6a-7cb10241ab3d"
+      "id": "dc07a93a-6ca2-4103-9e7a-ffb5570b5368"
     },
     {
       "cell_type": "code",
@@ -461,7 +461,7 @@
       "source": [
         "# YOUR CODE BELOW"
       ],
-      "id": "99f9fe7e"
+      "id": "b3bff07d"
     },
     {
       "cell_type": "code",
@@ -477,7 +477,7 @@
         "assert isinstance(restaurant_profile[2], int), \"Third element should be an integer (year)\"\n",
         "print(\"Restaurant profile:\", restaurant_profile)"
       ],
-      "id": "81b69135"
+      "id": "6fef1254"
     },
     {
       "cell_type": "markdown",
@@ -529,7 +529,7 @@
         "*Continue to the next tutorial to learn about loops in the context of\n",
         "the explore-exploit problem!*"
       ],
-      "id": "98794e72-5fe8-4740-8cda-521c1f6b1b11"
+      "id": "491641f5-be79-40fb-bb4e-9a6a2d444314"
     }
   ],
   "nbformat": 4,
diff --git a/part-02/tutorial-04-lists.pdf b/part-02/tutorial-04-lists.pdf
index ecbfbdbb6d50f43626a9c9f825f0a3d71c09962f..d47b3872bb3754fda22cd083db0276445eb4a86d 100644
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diff --git a/part-02/tutorial-05-loops 3.html b/part-02/tutorial-05-loops 3.html
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+Tutorial II.II - Loops – Programming: Everyday Decision-Making Algorithms
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    Tutorial II.II - Loops
    
+
    Programming: Everyday Decision-Making Algorithms
    
+
    
+
+
+
+
    
+
+    
+  
+    
+  
    
+  
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+
    
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+
    
+
    Introduction
    
+
    Loops are a fundamental concept in programming that allow us to repeat a set of instructions multiple times. They’re essential for tasks that require processing large datasets, iterating through complex sequences, or automating repetitive processes. In the context of clinical trials, loops help us systematically analyze multiple treatments or patient outcomes.
    
+
    
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+
    
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+
    
+
    
+Note
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+
    
+
    If a cell is marked with YOUR CODE BELOW, you are expected to write your code in that cell.
    
+
    
+
    
+
    
+
    
+
    Section 1 - For Loops
    
+
    A for loop allows us to iterate through a sequence of items. In clinical trials, this is particularly useful when we need to process multiple treatments or patient outcomes. The basic syntax is:
    
+
    for item in sequence:
+    # do something with item
    
+
    Think of it like reviewing patient charts: instead of manually checking each chart, you can automate the process to review them one by one systematically. This is especially valuable when dealing with large clinical trials or multiple treatment groups. Example with treatment options:
    
+
    
+
    treatments = ["Standard Drug", "New Drug A", "New Drug B"]
+for treatment in treatments:
+    print(f"Evaluating efficacy of {treatment}")
    
+
    
+
    Evaluating efficacy of Standard Drug
+Evaluating efficacy of New Drug A
+Evaluating efficacy of New Drug B
    
+
    
+
    
+
    
+
    
+
    Range in For Loops
    
+
    When you need to iterate a specific number of times, the range() function is invaluable. It generates a sequence of numbers. It can take up to three arguments:
    
+
      
+
    • start: The starting number (inclusive)
      • 
+
    • stop: The ending number (exclusive)
      • 
+
    • step: The difference between each number in the sequence
      • 
+
    
+
    
+
    # Visual representation of range
+print("range(5):", list(range(5)))
+print("range(1, 6):", list(range(1, 6)))
+print("range(0, 10, 2):", list(range(0, 10, 2)))
    
+
    
+
    range(5): [0, 1, 2, 3, 4]
+range(1, 6): [1, 2, 3, 4, 5]
+range(0, 10, 2): [0, 2, 4, 6, 8]
    
+
    
+
    
+
    We can then use this sequence in a for loop to iterate through the numbers.
    
+
    
+
    # Simulate 5 trial phases
+for phase in range(5):  # 0 to 4
+    print(f"Starting Phase {phase + 1}")
    
+
    
+
    Starting Phase 1
+Starting Phase 2
+Starting Phase 3
+Starting Phase 4
+Starting Phase 5
    
+
    
+
    
+
    
+
    # Range with start, stop, and step
+for dose in range(100, 501, 100):  # 100 to 500 in steps of 100
+    print(f"Testing dosage: {dose}mg")
    
+
    
+
    Testing dosage: 100mg
+Testing dosage: 200mg
+Testing dosage: 300mg
+Testing dosage: 400mg
+Testing dosage: 500mg
    
+
    
+
    
+
    
+
    Break and Continue Statements
    
+
      
+
    • break: Immediately exits the loop
      • 
+
    • continue: Skips to the next iteration
      • 
+
    
+
    
+
    efficacy_scores = [65, 85, 45, 82, 58]
+for score in efficacy_scores:
+    if score < 50:  # Skip low efficacy treatments
+        continue
+    print(f"Treatment efficacy: {score}%")
+    if score >= 85:  # We found a highly effective treatment!
+        print("Found a promising treatment - consider focusing on this one!")
+        break
    
+
    
+
    Treatment efficacy: 65%
+Treatment efficacy: 85%
+Found a promising treatment - consider focusing on this one!
    
+
    
+
    
+
    
+
    
+
    Tuple Unpacking
    
+
    Tuple unpacking is a powerful feature that allows you to assign multiple variables in a single statement. It’s often used in for loops to access elements from a list or tuple. For example:
    
+
    
+
    treatments = [("Standard Drug", 75), ("New Drug A", 85), ("Alternative B", 68), ("New Drug C", 92)]
+for name, efficacy in treatments:
+    print(f"Treatment: {name}, Efficacy: {efficacy}%")
    
+
    
+
    Treatment: Standard Drug, Efficacy: 75%
+Treatment: New Drug A, Efficacy: 85%
+Treatment: Alternative B, Efficacy: 68%
+Treatment: New Drug C, Efficacy: 92%
    
+
    
+
    
+
    
+
    
+
    Exercise 1.1 - Count Adverse Events
    
+
    Track the number of treatments that had too many adverse events (more than 5) with a for loop. Add 1 to high_adverse_count for each treatment that had more than 5 adverse events.
    
+
    
+
    adverse_events = [3, 7, 2, 6, 8, 1, 4]
+high_adverse_count = 0
+
+# YOUR CODE BELOW
    
+
    
+
    
+
    
+Code
+
    # Assertions to verify your solution
+assert isinstance(high_adverse_count, int), "high_adverse_count should be an integer"
+assert high_adverse_count == 3, "There should be exactly 3 treatments with high adverse events"
+print("Success! You've correctly counted the high adverse event treatments.")
    
+
    
+
    
+
    
+
    
+
    Exercise 1.2 - Calculate Average Treatment Efficacy
    
+
    Calculate the average efficacy of the treatments using a for loop. First, add each rate to the total. Then, calculate the average by dividing the total by the number of treatments.
    
+
    
+
    efficacy_rates = [78, 72, 85, 65, 80]
+average_efficacy = 0
+total = 0
+# YOUR CODE BELOW
    
+
    
+
    
+
    
+Code
+
    # Assertions to verify your solution
+assert isinstance(average_efficacy, (int, float)), "average_efficacy should be a number"
+assert average_efficacy == 76, "average_efficacy should be 76"
+print("Success! Your average calculation is correct.")
    
+
    
+
    
+
    
+
    
+
    
+
+
    
+
    
+Tip
+
    
+
    
+
    
+
      
+
    • Add each rate to the total
      • 
+
    • Calculate the average by dividing the total by the number of treatments
      • 
+
    • Note that len(efficacy_rates) gives you the count of treatments
      • 
+
    
+
    
+
    
+
    
+
    
+
    Exercise 1.3 - Find Promising Treatments
    
+
    Add all treatments with an efficacy rate of at least 80% to the list promising_treatments.
    
+
    
+
    treatments = [("Standard Drug", 75), ("New Drug A", 85), ("Alternative B", 68), ("New Drug C", 92)]
+promising_treatments = []
+
+# YOUR CODE BELOW
    
+
    
+
    
+
    
+Code
+
    # Assertions to verify your solution
+assert len(promising_treatments) == 2, "Should find exactly 2 promising treatments"
+assert all(isinstance(t, str) for t in promising_treatments), "promising_treatments should contain strings"
+assert "New Drug A" in promising_treatments, "New Drug A should be in promising_treatments"
+print("Success! You've correctly identified the promising treatments.")
    
+
    
+
    
+
    
+
    
+
    
+
+
    
+
    
+Tip
+
    
+
    
+
    
+
      
+
    • Each treatment is represented as a tuple: (name, efficacy_rate)
      • 
+
    • You need to check if the efficacy rate (second element) is ≥ 80%
      • 
+
    • If it meets the criteria, add the treatment name (first element) to promising_treatments
      • 
+
    • You could use tuple unpacking in your loop for cleaner code
      • 
+
    
+
    
+
    
+
    
+
    
+
    
+
    Section 2 - While Loops
    
+
    While loops continue executing as long as a condition is true. They’re perfect for situations where we don’t know in advance how many iterations we’ll need, like finding an effective treatment. Think of them as running clinical trials until you either find a breakthrough treatment or run out of research funding.
    
+
    
+
    resources = 100  # Starting research resources
+treatments_tested = 0
+current_best = 0
+
+while resources > 0:
+    print(f"Resources remaining: {resources}")
+    resources -= 20  # Each trial phase costs 20 units
+    treatments_tested += 1
+    
+print(f"Tested {treatments_tested} treatment variations")
    
+
    
+
    Resources remaining: 100
+Resources remaining: 80
+Resources remaining: 60
+Resources remaining: 40
+Resources remaining: 20
+Tested 5 treatment variations
    
+
    
+
    
+
    We can also use them without specific conditions at the beginning:
    
+
    
+
    trials = 0
+while True:
+    if trials > 5:
+        break
+    print(f"Trial {trials}")
+    trials += 1
    
+
    
+
    Trial 0
+Trial 1
+Trial 2
+Trial 3
+Trial 4
+Trial 5
    
+
    
+
    
+
    
+
    
+
    
+
+
    
+
    
+Note
+
    
+
    
+
    
+
    While loops are particularly useful when:
    
+
      
+
    • You don’t know how many iterations you’ll need
      • 
+
    • You’re looking for a specific outcome
      • 
+
    • You need to stop based on resource constraints
      • 
+
    
+
    
+
    
+
    Be careful with while loops! An infinite loop can crash your program:
    
+
    while True:  # Dangerous!
+    print("This will never end")
    
+
    
+
    
+
    
+
+
    
+
    
+Warning
+
    
+
    
+
    
+
    Always ensure:
    
+
      
+
    • The condition will eventually become false
      • 
+
    • Resources or counters are properly updated
      • 
+
    • You have a way to break out if needed
      • 
+
    
+
    
+
    
+
    
+
    Exercise 2.1 - Breakthrough Treatment
    
+
    Use a while loop to find the first treatment with an efficacy score of at least 88. Count the number of trials it takes to find this treatment and store it in the variable trials. Save the efficacy score of the breakthrough treatment in the variable current_efficacy. Note, that the efficacy_scores list is indexed from 0!
    
+
    
+
    efficacy_scores = [72, 68, 78, 88, 71, 65, 59]
+current_efficacy = 0
+trials = 0
+
+# YOUR CODE BELOW
    
+
    
+
    
+
    
+Code
+
    # Assertions to verify your solution
+assert trials == 4, "Should take exactly 4 trials to find the breakthrough"
+assert current_efficacy == 88, "Should find efficacy score of 88"
+print("Success! You've found the breakthrough treatment efficiently.")
    
+
    
+
    
+
    
+
    
+
    Exercise 2.2 - Resource Management
    
+
    Continue trials until either resources are depleted or a breakthrough (efficacy >= 90) is found. Count the number of trials it takes to find this treatment and store it in the variable trials_conducted. Save the efficacy score of the breakthrough treatment in the variable current_best. Note, that the efficacy_scores list is indexed from 0!
    
+
    
+
    resources = 100
+cost_per_trial = 25
+current_best = 0
+trials_conducted = 0
+efficacy_scores = [75, 82, 88, 92, 85, 78]  # Simulated trial results
+
+# YOUR CODE BELOW
    
+
    
+
    
+
    
+Code
+
    # Assertions to verify your solution
+assert trials_conducted == 4, "Should conduct 4 trials"
+assert current_best >= 90, "Should find a treatment with >= 90 efficacy"
+assert resources >= 0, "Should not exceed resource limit"
+print("Success! You've managed resources effectively.")
    
+
    
+
    
+
    
+
    
+
    
+
+
    
+
    
+Tip
+
    
+
    
+
    
+
      
+
    • Track both resources and efficacy simultaneously
      • 
+
    • Stop if either:
+
        
+
      • Resources fall below cost_per_trial
        • 
+
      • A breakthrough treatment (≥ 90% efficacy) is found
        • 
+
      • 
+
    • Remember to deduct costs for each trial
      • 
+
    
+
    
+
    
+
    
+
    
+
    
+
    Conclusion
    
+
    Excellent work! You’ve learned about two powerful loop structures in Python through the lens of clinical trials and treatment exploration:
    
+
      
+
    • for loops help us:
+
        
+
      • Process data systematically
        • 
+
      • Analyze outcomes efficiently
        • 
+
      • Work with structured data like treatment efficacy rates
        • 
+
      • 
+
    • while loops are perfect for:
+
        
+
      • Resource-constrained scenarios
        • 
+
      • Finding certain outcomes
        • 
+
      • Situations with unknown iteration counts
        • 
+
      • 
+
    
+
    In the context of clinical trials: - for loops are like reviewing a predetermined set of patient data - while loops are like continuing research until you either find a successful treatment or exhaust your resources
    
+
    These loop structures are fundamental tools, allowing us to process large datasets and make informed decisions in the context of the explore-exploit trade-off.
    
+
    
+
    
+
    
+
    Solutions
    
+
    You will likely find solutions to most exercises online. However, we strongly encourage you to work on these exercises independently without searching explicitly for the exact answers to the exercises. Understanding someone else’s solution is very different from developing your own. Use the lecture notes and try to solve the exercises on your own. This approach will significantly enhance your learning and problem-solving skills.
    
+
    Remember, the goal is not just to complete the exercises, but to understand the concepts and improve your programming abilities. If you encounter difficulties, review the lecture materials, experiment with different approaches, and don’t hesitate to ask for clarification during class discussions.
    
+
    Later, you will find the solutions to these exercises online in the associated GitHub repository, but we will also quickly go over them next week. To access the solutions, click on the Github button on the lower right and search for the folder with today’s lecture and tutorial. Alternatively, you can ask ChatGPT or Claude to explain them to you. But please remember, the goal is not just to complete the exercises, but to understand the concepts and improve your programming abilities.
    
+
    Continue to the next tutorial to tie all previous concepts together in the context of the explore-exploit problem in a casino!
    
+
+
+
    
+
+
     
+
+
     
+
+
+
+
+
+
\ No newline at end of file
diff --git a/part-02/tutorial-05-loops 3.ipynb b/part-02/tutorial-05-loops 3.ipynb
new file mode 100644
index 0000000..1adae27
--- /dev/null
+++ b/part-02/tutorial-05-loops 3.ipynb	
@@ -0,0 +1,643 @@
+{
+  "cells": [
+    {
+      "cell_type": "markdown",
+      "metadata": {},
+      "source": [
+        "# Tutorial II.II - Loops\n",
+        "\n",
+        "Programming: Everyday Decision-Making Algorithms\n",
+        "\n",
+        "# Introduction\n",
+        "\n",
+        "Loops are a fundamental concept in programming that allow us to repeat a\n",
+        "set of instructions multiple times. They’re essential for tasks that\n",
+        "require processing large datasets, iterating through complex sequences,\n",
+        "or automating repetitive processes. In the context of clinical trials,\n",
+        "loops help us systematically analyze multiple treatments or patient\n",
+        "outcomes.\n",
+        "\n",
+        "> **Note**\n",
+        ">\n",
+        "> If a cell is marked with `YOUR CODE BELOW`, you are expected to write\n",
+        "> your code in that cell.\n",
+        "\n",
+        "# Section 1 - For Loops\n",
+        "\n",
+        "A `for` loop allows us to iterate through a sequence of items. In\n",
+        "clinical trials, this is particularly useful when we need to process\n",
+        "multiple treatments or patient outcomes. The basic syntax is:\n",
+        "\n",
+        "``` python\n",
+        "for item in sequence:\n",
+        "    # do something with item\n",
+        "```\n",
+        "\n",
+        "Think of it like reviewing patient charts: instead of manually checking\n",
+        "each chart, you can automate the process to review them one by one\n",
+        "systematically. This is especially valuable when dealing with large\n",
+        "clinical trials or multiple treatment groups. Example with treatment\n",
+        "options:"
+      ],
+      "id": "641999d9-6c01-456f-9285-f52186866fe1"
+    },
+    {
+      "cell_type": "code",
+      "execution_count": 1,
+      "metadata": {},
+      "outputs": [
+        {
+          "output_type": "stream",
+          "name": "stdout",
+          "text": [
+            "Evaluating efficacy of Standard Drug\n",
+            "Evaluating efficacy of New Drug A\n",
+            "Evaluating efficacy of New Drug B"
+          ]
+        }
+      ],
+      "source": [
+        "treatments = [\"Standard Drug\", \"New Drug A\", \"New Drug B\"]\n",
+        "for treatment in treatments:\n",
+        "    print(f\"Evaluating efficacy of {treatment}\")"
+      ],
+      "id": "cfe0767f"
+    },
+    {
+      "cell_type": "markdown",
+      "metadata": {},
+      "source": [
+        "# Range in For Loops\n",
+        "\n",
+        "When you need to iterate a specific number of times, the `range()`\n",
+        "function is invaluable. It generates a sequence of numbers. It can take\n",
+        "up to three arguments:\n",
+        "\n",
+        "-   `start`: The starting number (inclusive)\n",
+        "-   `stop`: The ending number (exclusive)\n",
+        "-   `step`: The difference between each number in the sequence"
+      ],
+      "id": "f20f6941-c264-4f36-8164-98c06a25f412"
+    },
+    {
+      "cell_type": "code",
+      "execution_count": 2,
+      "metadata": {},
+      "outputs": [
+        {
+          "output_type": "stream",
+          "name": "stdout",
+          "text": [
+            "range(5): [0, 1, 2, 3, 4]\n",
+            "range(1, 6): [1, 2, 3, 4, 5]\n",
+            "range(0, 10, 2): [0, 2, 4, 6, 8]"
+          ]
+        }
+      ],
+      "source": [
+        "# Visual representation of range\n",
+        "print(\"range(5):\", list(range(5)))\n",
+        "print(\"range(1, 6):\", list(range(1, 6)))\n",
+        "print(\"range(0, 10, 2):\", list(range(0, 10, 2)))"
+      ],
+      "id": "db724b03"
+    },
+    {
+      "cell_type": "markdown",
+      "metadata": {},
+      "source": [
+        "We can then use this sequence in a `for` loop to iterate through the\n",
+        "numbers."
+      ],
+      "id": "a6fc0845-e0ba-4380-90b6-4ccc39243843"
+    },
+    {
+      "cell_type": "code",
+      "execution_count": 3,
+      "metadata": {},
+      "outputs": [
+        {
+          "output_type": "stream",
+          "name": "stdout",
+          "text": [
+            "Starting Phase 1\n",
+            "Starting Phase 2\n",
+            "Starting Phase 3\n",
+            "Starting Phase 4\n",
+            "Starting Phase 5"
+          ]
+        }
+      ],
+      "source": [
+        "# Simulate 5 trial phases\n",
+        "for phase in range(5):  # 0 to 4\n",
+        "    print(f\"Starting Phase {phase + 1}\")"
+      ],
+      "id": "163135de"
+    },
+    {
+      "cell_type": "code",
+      "execution_count": 4,
+      "metadata": {},
+      "outputs": [
+        {
+          "output_type": "stream",
+          "name": "stdout",
+          "text": [
+            "Testing dosage: 100mg\n",
+            "Testing dosage: 200mg\n",
+            "Testing dosage: 300mg\n",
+            "Testing dosage: 400mg\n",
+            "Testing dosage: 500mg"
+          ]
+        }
+      ],
+      "source": [
+        "# Range with start, stop, and step\n",
+        "for dose in range(100, 501, 100):  # 100 to 500 in steps of 100\n",
+        "    print(f\"Testing dosage: {dose}mg\")"
+      ],
+      "id": "09e331e4"
+    },
+    {
+      "cell_type": "markdown",
+      "metadata": {},
+      "source": [
+        "## Break and Continue Statements\n",
+        "\n",
+        "-   `break`: Immediately exits the loop\n",
+        "-   `continue`: Skips to the next iteration"
+      ],
+      "id": "75faab6f-06b2-4d46-9d54-b2bea4458009"
+    },
+    {
+      "cell_type": "code",
+      "execution_count": 5,
+      "metadata": {},
+      "outputs": [
+        {
+          "output_type": "stream",
+          "name": "stdout",
+          "text": [
+            "Treatment efficacy: 65%\n",
+            "Treatment efficacy: 85%\n",
+            "Found a promising treatment - consider focusing on this one!"
+          ]
+        }
+      ],
+      "source": [
+        "efficacy_scores = [65, 85, 45, 82, 58]\n",
+        "for score in efficacy_scores:\n",
+        "    if score < 50:  # Skip low efficacy treatments\n",
+        "        continue\n",
+        "    print(f\"Treatment efficacy: {score}%\")\n",
+        "    if score >= 85:  # We found a highly effective treatment!\n",
+        "        print(\"Found a promising treatment - consider focusing on this one!\")\n",
+        "        break"
+      ],
+      "id": "218d3e59"
+    },
+    {
+      "cell_type": "markdown",
+      "metadata": {},
+      "source": [
+        "## Tuple Unpacking\n",
+        "\n",
+        "Tuple unpacking is a powerful feature that allows you to assign multiple\n",
+        "variables in a single statement. It’s often used in `for` loops to\n",
+        "access elements from a list or tuple. For example:"
+      ],
+      "id": "2624e519-c4eb-40d1-94ec-0bd034628595"
+    },
+    {
+      "cell_type": "code",
+      "execution_count": 6,
+      "metadata": {},
+      "outputs": [
+        {
+          "output_type": "stream",
+          "name": "stdout",
+          "text": [
+            "Treatment: Standard Drug, Efficacy: 75%\n",
+            "Treatment: New Drug A, Efficacy: 85%\n",
+            "Treatment: Alternative B, Efficacy: 68%\n",
+            "Treatment: New Drug C, Efficacy: 92%"
+          ]
+        }
+      ],
+      "source": [
+        "treatments = [(\"Standard Drug\", 75), (\"New Drug A\", 85), (\"Alternative B\", 68), (\"New Drug C\", 92)]\n",
+        "for name, efficacy in treatments:\n",
+        "    print(f\"Treatment: {name}, Efficacy: {efficacy}%\")"
+      ],
+      "id": "13c88cca"
+    },
+    {
+      "cell_type": "markdown",
+      "metadata": {},
+      "source": [
+        "## Exercise 1.1 - Count Adverse Events\n",
+        "\n",
+        "Track the number of treatments that had too many adverse events (more\n",
+        "than 5) with a `for` loop. Add 1 to `high_adverse_count` for each\n",
+        "treatment that had more than 5 adverse events."
+      ],
+      "id": "4b2c7301-0de3-4c35-8231-c7760d5c3119"
+    },
+    {
+      "cell_type": "code",
+      "execution_count": 7,
+      "metadata": {},
+      "outputs": [],
+      "source": [
+        "adverse_events = [3, 7, 2, 6, 8, 1, 4]\n",
+        "high_adverse_count = 0\n",
+        "\n",
+        "# YOUR CODE BELOW"
+      ],
+      "id": "0af394a7"
+    },
+    {
+      "cell_type": "code",
+      "execution_count": 8,
+      "metadata": {},
+      "outputs": [],
+      "source": [
+        "# Assertions to verify your solution\n",
+        "assert isinstance(high_adverse_count, int), \"high_adverse_count should be an integer\"\n",
+        "assert high_adverse_count == 3, \"There should be exactly 3 treatments with high adverse events\"\n",
+        "print(\"Success! You've correctly counted the high adverse event treatments.\")"
+      ],
+      "id": "b4e4d9a4"
+    },
+    {
+      "cell_type": "markdown",
+      "metadata": {},
+      "source": [
+        "## Exercise 1.2 - Calculate Average Treatment Efficacy\n",
+        "\n",
+        "Calculate the average efficacy of the treatments using a `for` loop.\n",
+        "First, add each rate to the total. Then, calculate the average by\n",
+        "dividing the total by the number of treatments."
+      ],
+      "id": "b68564cc-7734-4c1e-94c3-cdfcf80caa99"
+    },
+    {
+      "cell_type": "code",
+      "execution_count": 9,
+      "metadata": {},
+      "outputs": [],
+      "source": [
+        "efficacy_rates = [78, 72, 85, 65, 80]\n",
+        "average_efficacy = 0\n",
+        "total = 0\n",
+        "# YOUR CODE BELOW"
+      ],
+      "id": "53fd20f2"
+    },
+    {
+      "cell_type": "code",
+      "execution_count": 10,
+      "metadata": {},
+      "outputs": [],
+      "source": [
+        "# Assertions to verify your solution\n",
+        "assert isinstance(average_efficacy, (int, float)), \"average_efficacy should be a number\"\n",
+        "assert average_efficacy == 76, \"average_efficacy should be 76\"\n",
+        "print(\"Success! Your average calculation is correct.\")"
+      ],
+      "id": "3d6df7c6"
+    },
+    {
+      "cell_type": "markdown",
+      "metadata": {},
+      "source": [
+        "> **Tip**\n",
+        ">\n",
+        "> -   Add each rate to the total\n",
+        "> -   Calculate the average by dividing the total by the number of\n",
+        ">     treatments\n",
+        "> -   Note that `len(efficacy_rates)` gives you the count of treatments\n",
+        "\n",
+        "## Exercise 1.3 - Find Promising Treatments\n",
+        "\n",
+        "Add all treatments with an efficacy rate of at least 80% to the list\n",
+        "`promising_treatments`."
+      ],
+      "id": "677c6ad8-daab-4ade-b0a5-24c9973d4f4e"
+    },
+    {
+      "cell_type": "code",
+      "execution_count": 11,
+      "metadata": {},
+      "outputs": [],
+      "source": [
+        "treatments = [(\"Standard Drug\", 75), (\"New Drug A\", 85), (\"Alternative B\", 68), (\"New Drug C\", 92)]\n",
+        "promising_treatments = []\n",
+        "\n",
+        "# YOUR CODE BELOW"
+      ],
+      "id": "514c4549"
+    },
+    {
+      "cell_type": "code",
+      "execution_count": 12,
+      "metadata": {},
+      "outputs": [],
+      "source": [
+        "# Assertions to verify your solution\n",
+        "assert len(promising_treatments) == 2, \"Should find exactly 2 promising treatments\"\n",
+        "assert all(isinstance(t, str) for t in promising_treatments), \"promising_treatments should contain strings\"\n",
+        "assert \"New Drug A\" in promising_treatments, \"New Drug A should be in promising_treatments\"\n",
+        "print(\"Success! You've correctly identified the promising treatments.\")"
+      ],
+      "id": "bbcef66e"
+    },
+    {
+      "cell_type": "markdown",
+      "metadata": {},
+      "source": [
+        "> **Tip**\n",
+        ">\n",
+        "> -   Each treatment is represented as a tuple: `(name, efficacy_rate)`\n",
+        "> -   You need to check if the efficacy rate (second element) is ≥ 80%\n",
+        "> -   If it meets the criteria, add the treatment name (first element)\n",
+        ">     to `promising_treatments`\n",
+        "> -   You could use tuple unpacking in your loop for cleaner code\n",
+        "\n",
+        "# Section 2 - While Loops\n",
+        "\n",
+        "While loops continue executing as long as a condition is true. They’re\n",
+        "perfect for situations where we don’t know in advance how many\n",
+        "iterations we’ll need, like finding an effective treatment. Think of\n",
+        "them as running clinical trials until you either find a breakthrough\n",
+        "treatment or run out of research funding."
+      ],
+      "id": "2c439d26-d8f6-4fbd-aad6-17bc5b0600b3"
+    },
+    {
+      "cell_type": "code",
+      "execution_count": 13,
+      "metadata": {},
+      "outputs": [
+        {
+          "output_type": "stream",
+          "name": "stdout",
+          "text": [
+            "Resources remaining: 100\n",
+            "Resources remaining: 80\n",
+            "Resources remaining: 60\n",
+            "Resources remaining: 40\n",
+            "Resources remaining: 20\n",
+            "Tested 5 treatment variations"
+          ]
+        }
+      ],
+      "source": [
+        "resources = 100  # Starting research resources\n",
+        "treatments_tested = 0\n",
+        "current_best = 0\n",
+        "\n",
+        "while resources > 0:\n",
+        "    print(f\"Resources remaining: {resources}\")\n",
+        "    resources -= 20  # Each trial phase costs 20 units\n",
+        "    treatments_tested += 1\n",
+        "    \n",
+        "print(f\"Tested {treatments_tested} treatment variations\")"
+      ],
+      "id": "879699d0"
+    },
+    {
+      "cell_type": "markdown",
+      "metadata": {},
+      "source": [
+        "We can also use them without specific conditions at the beginning:"
+      ],
+      "id": "1101cc1d-fbfa-4622-8a4f-7dd6c528d0da"
+    },
+    {
+      "cell_type": "code",
+      "execution_count": 14,
+      "metadata": {},
+      "outputs": [
+        {
+          "output_type": "stream",
+          "name": "stdout",
+          "text": [
+            "Trial 0\n",
+            "Trial 1\n",
+            "Trial 2\n",
+            "Trial 3\n",
+            "Trial 4\n",
+            "Trial 5"
+          ]
+        }
+      ],
+      "source": [
+        "trials = 0\n",
+        "while True:\n",
+        "    if trials > 5:\n",
+        "        break\n",
+        "    print(f\"Trial {trials}\")\n",
+        "    trials += 1"
+      ],
+      "id": "01cabd9e"
+    },
+    {
+      "cell_type": "markdown",
+      "metadata": {},
+      "source": [
+        "> **Note**\n",
+        ">\n",
+        "> While loops are particularly useful when:\n",
+        ">\n",
+        "> -   You don’t know how many iterations you’ll need\n",
+        "> -   You’re looking for a specific outcome\n",
+        "> -   You need to stop based on resource constraints\n",
+        "\n",
+        "Be careful with while loops! An infinite loop can crash your program:\n",
+        "\n",
+        "``` python\n",
+        "while True:  # Dangerous!\n",
+        "    print(\"This will never end\")\n",
+        "```\n",
+        "\n",
+        "> **Warning**\n",
+        ">\n",
+        "> Always ensure:\n",
+        ">\n",
+        "> -   The condition will eventually become false\n",
+        "> -   Resources or counters are properly updated\n",
+        "> -   You have a way to break out if needed\n",
+        "\n",
+        "## Exercise 2.1 - Breakthrough Treatment\n",
+        "\n",
+        "Use a `while` loop to find the first treatment with an efficacy score of\n",
+        "at least 88. Count the number of trials it takes to find this treatment\n",
+        "and store it in the variable `trials`. Save the efficacy score of the\n",
+        "breakthrough treatment in the variable `current_efficacy`. Note, that\n",
+        "the `efficacy_scores` list is indexed from 0!"
+      ],
+      "id": "649165bf-9143-49df-aead-ad41c552efde"
+    },
+    {
+      "cell_type": "code",
+      "execution_count": 15,
+      "metadata": {},
+      "outputs": [],
+      "source": [
+        "efficacy_scores = [72, 68, 78, 88, 71, 65, 59]\n",
+        "current_efficacy = 0\n",
+        "trials = 0\n",
+        "\n",
+        "# YOUR CODE BELOW"
+      ],
+      "id": "244b8b53"
+    },
+    {
+      "cell_type": "code",
+      "execution_count": 16,
+      "metadata": {},
+      "outputs": [],
+      "source": [
+        "# Assertions to verify your solution\n",
+        "assert trials == 4, \"Should take exactly 4 trials to find the breakthrough\"\n",
+        "assert current_efficacy == 88, \"Should find efficacy score of 88\"\n",
+        "print(\"Success! You've found the breakthrough treatment efficiently.\")"
+      ],
+      "id": "f64a616c"
+    },
+    {
+      "cell_type": "markdown",
+      "metadata": {},
+      "source": [
+        "## Exercise 2.2 - Resource Management\n",
+        "\n",
+        "Continue trials until either resources are depleted or a breakthrough\n",
+        "(efficacy \\>= 90) is found. Count the number of trials it takes to find\n",
+        "this treatment and store it in the variable `trials_conducted`. Save the\n",
+        "efficacy score of the breakthrough treatment in the variable\n",
+        "`current_best`. Note, that the `efficacy_scores` list is indexed from 0!"
+      ],
+      "id": "4bb075ae-1c24-44fc-bcae-603747107c8f"
+    },
+    {
+      "cell_type": "code",
+      "execution_count": 17,
+      "metadata": {},
+      "outputs": [],
+      "source": [
+        "resources = 100\n",
+        "cost_per_trial = 25\n",
+        "current_best = 0\n",
+        "trials_conducted = 0\n",
+        "efficacy_scores = [75, 82, 88, 92, 85, 78]  # Simulated trial results\n",
+        "\n",
+        "# YOUR CODE BELOW"
+      ],
+      "id": "69631877"
+    },
+    {
+      "cell_type": "code",
+      "execution_count": 18,
+      "metadata": {},
+      "outputs": [],
+      "source": [
+        "# Assertions to verify your solution\n",
+        "assert trials_conducted == 4, \"Should conduct 4 trials\"\n",
+        "assert current_best >= 90, \"Should find a treatment with >= 90 efficacy\"\n",
+        "assert resources >= 0, \"Should not exceed resource limit\"\n",
+        "print(\"Success! You've managed resources effectively.\")"
+      ],
+      "id": "0f4930f1"
+    },
+    {
+      "cell_type": "markdown",
+      "metadata": {},
+      "source": [
+        "> **Tip**\n",
+        ">\n",
+        "> -   Track both resources and efficacy simultaneously\n",
+        "> -   Stop if either:\n",
+        ">     -   Resources fall below cost_per_trial\n",
+        ">     -   A breakthrough treatment (≥ 90% efficacy) is found\n",
+        "> -   Remember to deduct costs for each trial\n",
+        "\n",
+        "# Conclusion\n",
+        "\n",
+        "Excellent work! You’ve learned about two powerful loop structures in\n",
+        "Python through the lens of clinical trials and treatment exploration:\n",
+        "\n",
+        "-   `for` loops help us:\n",
+        "    -   Process data systematically\n",
+        "    -   Analyze outcomes efficiently\n",
+        "    -   Work with structured data like treatment efficacy rates\n",
+        "-   `while` loops are perfect for:\n",
+        "    -   Resource-constrained scenarios\n",
+        "    -   Finding certain outcomes\n",
+        "    -   Situations with unknown iteration counts\n",
+        "\n",
+        "In the context of clinical trials: - `for` loops are like reviewing a\n",
+        "predetermined set of patient data - `while` loops are like continuing\n",
+        "research until you either find a successful treatment or exhaust your\n",
+        "resources\n",
+        "\n",
+        "These loop structures are fundamental tools, allowing us to process\n",
+        "large datasets and make informed decisions in the context of the\n",
+        "explore-exploit trade-off.\n",
+        "\n",
+        "------------------------------------------------------------------------\n",
+        "\n",
+        "# Solutions\n",
+        "\n",
+        "You will likely find solutions to most exercises online. However, we\n",
+        "strongly encourage you to work on these exercises independently without\n",
+        "searching explicitly for the exact answers to the exercises.\n",
+        "Understanding someone else’s solution is very different from developing\n",
+        "your own. Use the lecture notes and try to solve the exercises on your\n",
+        "own. This approach will significantly enhance your learning and\n",
+        "problem-solving skills.\n",
+        "\n",
+        "Remember, the goal is not just to complete the exercises, but to\n",
+        "understand the concepts and improve your programming abilities. If you\n",
+        "encounter difficulties, review the lecture materials, experiment with\n",
+        "different approaches, and don’t hesitate to ask for clarification during\n",
+        "class discussions.\n",
+        "\n",
+        "Later, you will find the solutions to these exercises online in the\n",
+        "associated GitHub repository, but we will also quickly go over them next\n",
+        "week. To access the solutions, click on the Github button on the lower\n",
+        "right and search for the folder with today’s lecture and tutorial.\n",
+        "Alternatively, you can ask ChatGPT or Claude to explain them to you. But\n",
+        "please remember, the goal is not just to complete the exercises, but to\n",
+        "understand the concepts and improve your programming abilities.\n",
+        "\n",
+        "*Continue to the next tutorial to tie all previous concepts together in\n",
+        "the context of the explore-exploit problem in a casino!*"
+      ],
+      "id": "30f4a7fa-4705-44a5-ac9c-9ef9ccc8652b"
+    }
+  ],
+  "nbformat": 4,
+  "nbformat_minor": 5,
+  "metadata": {
+    "kernelspec": {
+      "name": "python3",
+      "display_name": "Python 3 (ipykernel)",
+      "language": "python",
+      "path": "/Users/tvlcek/miniconda3/share/jupyter/kernels/python3"
+    },
+    "language_info": {
+      "name": "python",
+      "codemirror_mode": {
+        "name": "ipython",
+        "version": "3"
+      },
+      "file_extension": ".py",
+      "mimetype": "text/x-python",
+      "nbconvert_exporter": "python",
+      "pygments_lexer": "ipython3",
+      "version": "3.12.7"
+    }
+  }
+}
\ No newline at end of file
diff --git a/part-02/tutorial-05-loops 3.pdf b/part-02/tutorial-05-loops 3.pdf
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dKkFe3j}FC0hWcTJ;o7=TxUh
  06 - Exploration
   
    
+
+      
+  
+        
  • 
+      
     
+            
+           
+      
    
+      
   
    • 
@@ -320,7 +355,7 @@ 
    Section 1 - For Loops
    
 
    for item in sequence:
     # do something with item
    
 
    Think of it like reviewing patient charts: instead of manually checking each chart, you can automate the process to review them one by one systematically. This is especially valuable when dealing with large clinical trials or multiple treatment groups. Example with treatment options:
    
-
    
+
    
 
    treatments = ["Standard Drug", "New Drug A", "New Drug B"]
 for treatment in treatments:
     print(f"Evaluating efficacy of {treatment}")
    
@@ -339,7 +374,7 @@ 
    Range in For Loops
    
 
  • stop: The ending number (exclusive)
    • 
 
  • step: The difference between each number in the sequence
    • 
 
-
    
+
    
 
    # Visual representation of range
 print("range(5):", list(range(5)))
 print("range(1, 6):", list(range(1, 6)))
@@ -351,7 +386,7 @@ 
    Range in For Loops
    
 
    
 
    
 
    We can then use this sequence in a for loop to iterate through the numbers.
    
-
    
+
    
 
    # Simulate 5 trial phases
 for phase in range(5):  # 0 to 4
     print(f"Starting Phase {phase + 1}")
    
@@ -363,7 +398,7 @@ 
    Range in For Loops
    
 Starting Phase 5
    
 
    
 
    
-
    
+
    
 
    # Range with start, stop, and step
 for dose in range(100, 501, 100):  # 100 to 500 in steps of 100
     print(f"Testing dosage: {dose}mg")
    
@@ -381,7 +416,7 @@ 
    Break and Co
 
  • break: Immediately exits the loop
    • 
 
  • continue: Skips to the next iteration
    • 
 
-
    
+
    
 
    efficacy_scores = [65, 85, 45, 82, 58]
 for score in efficacy_scores:
     if score < 50:  # Skip low efficacy treatments
@@ -400,7 +435,7 @@ 
    Break and Co
 
    
 
    Tuple Unpacking
    
 
    Tuple unpacking is a powerful feature that allows you to assign multiple variables in a single statement. It’s often used in for loops to access elements from a list or tuple. For example:
    
-
    
+
    
 
    treatments = [("Standard Drug", 75), ("New Drug A", 85), ("Alternative B", 68), ("New Drug C", 92)]
 for name, efficacy in treatments:
     print(f"Treatment: {name}, Efficacy: {efficacy}%")
    
@@ -415,13 +450,13 @@ 
    Tuple Unpacking
    
 
    
 
    Exercise 1.1 - Count Adverse Events
    
 
    Track the number of treatments that had too many adverse events (more than 5) with a for loop. Add 1 to high_adverse_count for each treatment that had more than 5 adverse events.
    
-
    
+
    
 
    adverse_events = [3, 7, 2, 6, 8, 1, 4]
 high_adverse_count = 0
 
 # YOUR CODE BELOW
    
 
    
-
    
+
    
 
    
 Code
 
    # Assertions to verify your solution
@@ -434,13 +469,13 @@ 
    Exerci
 
    
 
    Exercise 1.2 - Calculate Average Treatment Efficacy
    
 
    Calculate the average efficacy of the treatments using a for loop. First, add each rate to the total. Then, calculate the average by dividing the total by the number of treatments.
    
-
    
+
    
 
    efficacy_rates = [78, 72, 85, 65, 80]
 average_efficacy = 0
 total = 0
 # YOUR CODE BELOW
    
 
    
-
    
+
    
 
    
 Code
 
    # Assertions to verify your solution
@@ -470,13 +505,13 @@ 
    
 
    Exercise 1.3 - Find Promising Treatments
    
 
    Add all treatments with an efficacy rate of at least 80% to the list promising_treatments.
    
-
    
+
    
 
    treatments = [("Standard Drug", 75), ("New Drug A", 85), ("Alternative B", 68), ("New Drug C", 92)]
 promising_treatments = []
 
 # YOUR CODE BELOW
    
 
    
-
    
+
    
 
    
 Code
 
    # Assertions to verify your solution
@@ -509,7 +544,7 @@ 
    E
 
    
 
    Section 2 - While Loops
    
 
    While loops continue executing as long as a condition is true. They’re perfect for situations where we don’t know in advance how many iterations we’ll need, like finding an effective treatment. Think of them as running clinical trials until you either find a breakthrough treatment or run out of research funding.
    
-
    
+
    
 
    resources = 100  # Starting research resources
 treatments_tested = 0
 current_best = 0
@@ -530,7 +565,7 @@ 
    Section 2 - While Loops
    
 
    
 
    
 
    We can also use them without specific conditions at the beginning:
    
-
    
+
    
 
    trials = 0
 while True:
     if trials > 5:
@@ -588,14 +623,14 @@ 
    Section 2 - While Loops
    
 
    
 
    Exercise 2.1 - Breakthrough Treatment
    
 
    Use a while loop to find the first treatment with an efficacy score of at least 88. Count the number of trials it takes to find this treatment and store it in the variable trials. Save the efficacy score of the breakthrough treatment in the variable current_efficacy. Note, that the efficacy_scores list is indexed from 0!
    
-
    
+
    
 
    efficacy_scores = [72, 68, 78, 88, 71, 65, 59]
 current_efficacy = 0
 trials = 0
 
 # YOUR CODE BELOW
    
 
    
-
    
+
    
 
    
 Code
 
    # Assertions to verify your solution
@@ -608,7 +643,7 @@ 
    Exer
 
    
 
    Exercise 2.2 - Resource Management
    
 
    Continue trials until either resources are depleted or a breakthrough (efficacy >= 90) is found. Count the number of trials it takes to find this treatment and store it in the variable trials_conducted. Save the efficacy score of the breakthrough treatment in the variable current_best. Note, that the efficacy_scores list is indexed from 0!
    
-
    
+
    
 
    resources = 100
 cost_per_trial = 25
 current_best = 0
@@ -617,7 +652,7 @@ 
    Exercis
 
 # YOUR CODE BELOW
    
 
    
-
    
+
    
 
    
 Code
 
    # Assertions to verify your solution
diff --git a/part-02/tutorial-05-loops.ipynb b/part-02/tutorial-05-loops.ipynb
index 2dfafd1..9254b57 100644
--- a/part-02/tutorial-05-loops.ipynb
+++ b/part-02/tutorial-05-loops.ipynb
@@ -39,7 +39,7 @@
         "clinical trials or multiple treatment groups. Example with treatment\n",
         "options:"
       ],
-      "id": "510292c2-693f-4e00-ae8f-e1e3e05b04bd"
+      "id": "21bb5820-3b4c-48b0-8524-ed106002c397"
     },
     {
       "cell_type": "code",
@@ -61,7 +61,7 @@
         "for treatment in treatments:\n",
         "    print(f\"Evaluating efficacy of {treatment}\")"
       ],
-      "id": "91a69ef9"
+      "id": "878dd574"
     },
     {
       "cell_type": "markdown",
@@ -77,7 +77,7 @@
         "-   `stop`: The ending number (exclusive)\n",
         "-   `step`: The difference between each number in the sequence"
       ],
-      "id": "4e5eb1b4-305b-4bc6-82af-f46edb484dd1"
+      "id": "f7321cad-03e1-4524-9a5e-167a68a53e91"
     },
     {
       "cell_type": "code",
@@ -100,7 +100,7 @@
         "print(\"range(1, 6):\", list(range(1, 6)))\n",
         "print(\"range(0, 10, 2):\", list(range(0, 10, 2)))"
       ],
-      "id": "91caf85e"
+      "id": "121cd586"
     },
     {
       "cell_type": "markdown",
@@ -109,7 +109,7 @@
         "We can then use this sequence in a `for` loop to iterate through the\n",
         "numbers."
       ],
-      "id": "bcc022b7-4b1f-403b-927c-345acec81631"
+      "id": "60020b5f-ec3e-422d-89f4-310cd722e50c"
     },
     {
       "cell_type": "code",
@@ -133,7 +133,7 @@
         "for phase in range(5):  # 0 to 4\n",
         "    print(f\"Starting Phase {phase + 1}\")"
       ],
-      "id": "b4c34958"
+      "id": "391dcf48"
     },
     {
       "cell_type": "code",
@@ -157,7 +157,7 @@
         "for dose in range(100, 501, 100):  # 100 to 500 in steps of 100\n",
         "    print(f\"Testing dosage: {dose}mg\")"
       ],
-      "id": "98bd5392"
+      "id": "1b04d069"
     },
     {
       "cell_type": "markdown",
@@ -168,7 +168,7 @@
         "-   `break`: Immediately exits the loop\n",
         "-   `continue`: Skips to the next iteration"
       ],
-      "id": "7ac81306-f620-4d96-8e63-a74b3ac51a89"
+      "id": "08130aef-1230-4a1e-9a13-554057a4d011"
     },
     {
       "cell_type": "code",
@@ -195,7 +195,7 @@
         "        print(\"Found a promising treatment - consider focusing on this one!\")\n",
         "        break"
       ],
-      "id": "1b1016ce"
+      "id": "9befd3e1"
     },
     {
       "cell_type": "markdown",
@@ -207,7 +207,7 @@
         "variables in a single statement. It’s often used in `for` loops to\n",
         "access elements from a list or tuple. For example:"
       ],
-      "id": "d04c4b8d-672c-4df8-901d-94f1c557f907"
+      "id": "a536f8fa-cf20-4dc3-bbe9-73039c818a57"
     },
     {
       "cell_type": "code",
@@ -230,7 +230,7 @@
         "for name, efficacy in treatments:\n",
         "    print(f\"Treatment: {name}, Efficacy: {efficacy}%\")"
       ],
-      "id": "877fcd21"
+      "id": "82d04582"
     },
     {
       "cell_type": "markdown",
@@ -242,7 +242,7 @@
         "than 5) with a `for` loop. Add 1 to `high_adverse_count` for each\n",
         "treatment that had more than 5 adverse events."
       ],
-      "id": "a7440874-0d5c-4bb0-95a5-c62bc3dc1f9e"
+      "id": "400afd2d-ab32-45b1-9cfe-4896be2b565a"
     },
     {
       "cell_type": "code",
@@ -255,7 +255,7 @@
         "\n",
         "# YOUR CODE BELOW"
       ],
-      "id": "61412aff"
+      "id": "92f35c02"
     },
     {
       "cell_type": "code",
@@ -268,7 +268,7 @@
         "assert high_adverse_count == 3, \"There should be exactly 3 treatments with high adverse events\"\n",
         "print(\"Success! You've correctly counted the high adverse event treatments.\")"
       ],
-      "id": "c62b1d9c"
+      "id": "e5b64864"
     },
     {
       "cell_type": "markdown",
@@ -280,7 +280,7 @@
         "First, add each rate to the total. Then, calculate the average by\n",
         "dividing the total by the number of treatments."
       ],
-      "id": "159b0497-3d7e-455f-8a63-ff4cb48049cd"
+      "id": "2fb5ba41-2e5a-401c-a201-3e439d01da24"
     },
     {
       "cell_type": "code",
@@ -293,7 +293,7 @@
         "total = 0\n",
         "# YOUR CODE BELOW"
       ],
-      "id": "100adea0"
+      "id": "0c367f7f"
     },
     {
       "cell_type": "code",
@@ -306,7 +306,7 @@
         "assert average_efficacy == 76, \"average_efficacy should be 76\"\n",
         "print(\"Success! Your average calculation is correct.\")"
       ],
-      "id": "2508caf4"
+      "id": "30df589d"
     },
     {
       "cell_type": "markdown",
@@ -324,7 +324,7 @@
         "Add all treatments with an efficacy rate of at least 80% to the list\n",
         "`promising_treatments`."
       ],
-      "id": "057e224d-2853-4143-bda2-ace7b5ee5970"
+      "id": "1b31433c-379c-4e36-9a16-4fa3e424c762"
     },
     {
       "cell_type": "code",
@@ -337,7 +337,7 @@
         "\n",
         "# YOUR CODE BELOW"
       ],
-      "id": "59ba4fa7"
+      "id": "b5112257"
     },
     {
       "cell_type": "code",
@@ -351,7 +351,7 @@
         "assert \"New Drug A\" in promising_treatments, \"New Drug A should be in promising_treatments\"\n",
         "print(\"Success! You've correctly identified the promising treatments.\")"
       ],
-      "id": "4b36b73a"
+      "id": "3dc03ddc"
     },
     {
       "cell_type": "markdown",
@@ -373,7 +373,7 @@
         "them as running clinical trials until you either find a breakthrough\n",
         "treatment or run out of research funding."
       ],
-      "id": "fd8339fd-b5d1-4a9b-8994-2d123af9f862"
+      "id": "f4325856-51bd-4267-a5ae-f5bd5ffac9b6"
     },
     {
       "cell_type": "code",
@@ -405,7 +405,7 @@
         "    \n",
         "print(f\"Tested {treatments_tested} treatment variations\")"
       ],
-      "id": "20be5ca4"
+      "id": "b0606984"
     },
     {
       "cell_type": "markdown",
@@ -413,7 +413,7 @@
       "source": [
         "We can also use them without specific conditions at the beginning:"
       ],
-      "id": "926734d0-5991-4a07-8588-783efee29a6c"
+      "id": "1079dba5-972f-4ddc-aaad-31decd17321f"
     },
     {
       "cell_type": "code",
@@ -441,7 +441,7 @@
         "    print(f\"Trial {trials}\")\n",
         "    trials += 1"
       ],
-      "id": "3b98b337"
+      "id": "020330ad"
     },
     {
       "cell_type": "markdown",
@@ -478,7 +478,7 @@
         "breakthrough treatment in the variable `current_efficacy`. Note, that\n",
         "the `efficacy_scores` list is indexed from 0!"
       ],
-      "id": "eff088b2-bd4e-4485-a0b8-ebc82fee0ea3"
+      "id": "34abbf62-278c-46a9-a0a3-04e59837cd66"
     },
     {
       "cell_type": "code",
@@ -492,7 +492,7 @@
         "\n",
         "# YOUR CODE BELOW"
       ],
-      "id": "862db404"
+      "id": "596c0122"
     },
     {
       "cell_type": "code",
@@ -505,7 +505,7 @@
         "assert current_efficacy == 88, \"Should find efficacy score of 88\"\n",
         "print(\"Success! You've found the breakthrough treatment efficiently.\")"
       ],
-      "id": "c0bf674a"
+      "id": "82380125"
     },
     {
       "cell_type": "markdown",
@@ -519,7 +519,7 @@
         "efficacy score of the breakthrough treatment in the variable\n",
         "`current_best`. Note, that the `efficacy_scores` list is indexed from 0!"
       ],
-      "id": "f7ee5783-2ccc-463a-8e51-03278fc8b812"
+      "id": "0c2f0722-3bcf-464e-aa33-02953ad3af6c"
     },
     {
       "cell_type": "code",
@@ -535,7 +535,7 @@
         "\n",
         "# YOUR CODE BELOW"
       ],
-      "id": "cdd490f2"
+      "id": "b6862c11"
     },
     {
       "cell_type": "code",
@@ -549,7 +549,7 @@
         "assert resources >= 0, \"Should not exceed resource limit\"\n",
         "print(\"Success! You've managed resources effectively.\")"
       ],
-      "id": "38f8305c"
+      "id": "680c5613"
     },
     {
       "cell_type": "markdown",
@@ -615,7 +615,7 @@
         "*Continue to the next tutorial to tie all previous concepts together in\n",
         "the context of the explore-exploit problem in a casino!*"
       ],
-      "id": "8a777a1c-c8e3-435c-8c27-1f7259a3efd6"
+      "id": "77d74fed-c75c-481c-923a-9eeb00b65246"
     }
   ],
   "nbformat": 4,
diff --git a/part-02/tutorial-05-loops.pdf b/part-02/tutorial-05-loops.pdf
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+Tutorial II.III - Explore and Exploit – Programming: Everyday Decision-Making Algorithms
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    Tutorial II.III - Explore and Exploit
    
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    Programming: Everyday Decision-Making Algorithms
    
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+
    Introduction
    
+
    Welcome to the final tutorial of Part II! We’ll tie together everything we’ve learned so far - variables, lists, conditions, and loops - to tackle a classic explore-exploit problem: the one-armed bandit (slot machine). This is a perfect example of balancing exploration (trying different strategies) with exploitation (sticking to what works).
    
+
    
+
    
+
    Section 1 - Setting Up Our Casino
    
+
    First, let’s create a simple slot machine simulator using what we learned about variables and lists. In order to do this, we’ll need to import the random module, which we can do using the import statement. Don’t worry about the details of this statement for now - we’ll cover it in more detail in a future tutorial.
    
+
    
+
    import random
+
+# Initial setup
+money = 100 # Starting money
+bet = 10 # How much we bet each time
+payouts = [0, 5, 10, 20, 50] # Different possible wins
+
+print("Possible outcomes:")
+for payout in payouts:
+    print(f"🎰 Win ${payout}")
    
+
    
+
    Possible outcomes:
+🎰 Win $0
+🎰 Win $5
+🎰 Win $10
+🎰 Win $20
+🎰 Win $50
    
+
    
+
    
+
    In this setup, we’re creating a simple slot machine where: - You start with $100 - Each play costs $10 - There are 5 possible payouts: $0 (loss), $5 (small win), $10 (break even), $20 (good win), and $50 (jackpot) - The random.choice() function simulates pulling the lever by randomly selecting one of these payouts
    
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+Note
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+
    In real slot machines, the probabilities of different payouts aren’t equal. Higher payouts are much less likely to occur than lower ones. Our simplified version gives each payout an equal chance.
    
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+
    
+
    To simulate playing the slot machine once, we can start as follows:
    
+
    
+
    # Simulate playing the slot machine once
+win = random.choice(payouts)
+money += win
+print(f"You bet ${bet}")
+print(f"You won ${win}!")
+print(f"Your new balance is ${money}")
    
+
    
+
    You bet $10
+You won $50!
+Your new balance is $150
    
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+Tip
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    += is a shorthand for “add and assign”. So money += 10 is equivalent to money = money + 10. This also works for other arithmetic operations, like -=, *=, and /=.
    
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+
    
+
    Exercise 1.1 - Multiple Attempts
    
+
    Now let’s use a loop to play multiple times and track our results. Write a loop that:
    
+
      
+
    1. Plays the slot machine 10 times
      2. 
+
    2. Subtracts the bet amount each time
      3. 
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    3. Adds a random payout
      4. 
+
    4. Stores the results in a list
      5. 
+
    
+
    
+
    money = 100 # Reset our money
+bet = 10 # How much we bet each time
+results = [] # List to store how much money we have after each play
+
+# YOUR CODE BELOW
    
+
    
+
    
+
    
+Code
+
    # Check your results
+assert len(results) == 10, "You should have 10 results in your list"
+assert all(isinstance(x, (int, float)) for x in results), "All results should be numbers"
+print(f"You played the slot machine {len(results)} times")
+print(f"Your final balance is ${results[-1]}")
+print(f"Unfortunately, the payout rates are not realistic here...")
    
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+Tip
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    Use the append() method to add an element to a list. For example, results.append(money) will add the current value of money to the results list.
    
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+
    Exercise 1.2 - Playing with a Budget
    
+
    Now let’s simulate playing the slot machine multiple times with a budget. We’ll use a while loop to play until we run out of money. This is more realistic than playing a fixed number of times, as real players need to stop when they’re out of money!
    
+
    The machine_payout_rate represents how generous the machine is:
    
+
      
+
    • The function random.random() generates a random number between 0 and 1.
      • 
+
    • A rate of 2.0 means you get back exactly what you bet (on average)
      • 
+
    • Our rate of 1.5 means you could win up to 1.5 times your bet but on average you’ll get back 0.75 times your bet
      • 
+
    
+
    # Compute the payout for the current play
+machine_payout_rate = 1.5
+payout = random.random() * machine_payout_rate * bet
    
+
    Use a while loop to play the slot machine until you run out of money, and store the amount of money you have after each play in the results list. Further, print out the amount of money you have after each play with a formatted string.
    
+
    
+
    import random
+
+machine_payout_rate = 1.5 # Payout rate for the machine
+bet = 10 # Bet size
+money = 100 # Our starting money
+results = [] # Store results of each play here
+
+# YOUR CODE BELOW 
    
+
    
+
    
+
    
+Code
+
    # Check your results
+assert len(results) > 0, "You should have at least one result"
+assert all(isinstance(x, (int, float)) for x in results), "All results should be numbers"
+assert results[-1] <= bet, "Should stop playing when money is less than bet amount"
+assert all(abs(results[i] - results[i-1]) <= bet * machine_payout_rate for i in range(1, len(results))), "Each play should not change money by more than maximum possible payout"
+print(f"You played the slot machine {len(results)} times")
    
+
    
+
    
+
    
+
    
+
    Section 2 - Nested Loops
    
+
    Now let’s use nested loops to try different slot machines with different payout rates. This is where exploration comes in! Nested loops are a way to repeat a loop multiple times, and we can use them to try different options. It’s essentially a loop inside another loop.
    
+
    
+
    
+
    
+
+
    
+
    
+Tip
+
    
+
    
+
    
+
    Nested loops are like a clock: the outer loop is like the hour hand (moves slowly), and the inner loop is like the minute hand (completes a full cycle for each move of the hour hand).
    
+
    
+
    
+
    For example, for machine in range(3) will run a loop 3 times. We can use nested loops to try all combinations of two different options.
    
+
    
+
    for machine in range(3):
+    for payout in range(4):
+        print(f"Machine Nr. {machine}, Payout Nr. {payout}")
    
+
    
+
    Machine Nr. 0, Payout Nr. 0
+Machine Nr. 0, Payout Nr. 1
+Machine Nr. 0, Payout Nr. 2
+Machine Nr. 0, Payout Nr. 3
+Machine Nr. 1, Payout Nr. 0
+Machine Nr. 1, Payout Nr. 1
+Machine Nr. 1, Payout Nr. 2
+Machine Nr. 1, Payout Nr. 3
+Machine Nr. 2, Payout Nr. 0
+Machine Nr. 2, Payout Nr. 1
+Machine Nr. 2, Payout Nr. 2
+Machine Nr. 2, Payout Nr. 3
    
+
    
+
    
+
    
+
    
+
    Exercise 2.1 - Simulating Multiple Machines
    
+
    The setup is the same as in Exercise 1.2, but we’re now comparing three different machines, each with its own payout rate. Use a while loop for each machine and a for loop to try all machines. As the bank always wins, we’re not interested in the results for each machine, but rather in the number of times we can play each machine before we run out of money.
    
+
    Store the number of plays in a list called plays with three elements, one for each machine. The goal is to find out which machine lets us play the longest with our budget. This is a common exploration strategy: try each option several times to understand its characteristics.
    
+
    
+
    import random
+# Different machines might have different payout rates
+machine_1_payout_rate = 1.2
+machine_2_payout_rate = 1.5
+machine_3_payout_rate = 1.8
+
+bet = 10 # Bet size at each play
+budget = 100 # Our starting money for each machine!
+plays = [0, 0, 0] # List to store number of plays for each machine
+
+# YOUR CODE BELOW
    
+
    
+
    
+
    
+Code
+
    # Check your results
+assert len(plays) == 3, "Should have results for three machines"
+assert all(isinstance(x, int) and x >= 0 for x in plays), "Number of plays should be non-negative integers"
+assert all(x <= budget/bet * 6 for x in plays), "Number of plays seems unreasonably high given budget"
+print(f"You played the slot machine {plays[0]} times on machine 1")
+print(f"You played the slot machine {plays[1]} times on machine 2")
+print(f"You played the slot machine {plays[2]} times on machine 3")
    
+
    
+
    
+
    
+
    
+
    Exercise 2.2 - Exploring the Machines
    
+
    Now let’s find out which machine is the best and which one is the worst by comparing the number of plays for each machine. Store the index of the best machine in best_machine and the index of the worst machine in worst_machine. You can use the max(plays) function to find the maximum number of plays in the plays list and the plays.index(max(plays)) function to find the index of the maximum number of plays.
    
+
    
+
    # YOUR CODE BELOW
    
+
    
+
    
+
    
+Code
+
    # Check your results
+assert isinstance(best_machine, int) and 0 <= best_machine <= 2, "Best machine should be 0, 1, or 2"
+assert isinstance(worst_machine, int) and 0 <= worst_machine <= 2, "Worst machine should be 0, 1, or 2"
+assert best_machine != worst_machine, "Best and worst machine cannot be the same"
+print(f"The best machine is machine {best_machine}")
+print(f"The worst machine is machine {worst_machine}")
    
+
    
+
    
+
    
+
    
+
    Conclusion
    
+
    Excellent work! You’ve successfully combined multiple programming concepts to tackle a real explore-exploit problem:
    
+
      
+
    • Variables and types for tracking money and bets
      • 
+
    • Lists for storing payouts and results
      • 
+
    • Loops (including nested loops) for testing different machines
      • 
+
    • Conditions for finding the best machine
      • 
+
    
+
    This is a simplified version of how casinos and gambling companies might analyze their games, though in reality, they use much more sophisticated algorithms! Remember though, that the casino always wins!
    
+
    
+
    
+
    Solutions
    
+
    You will likely find solutions to most exercises online. However, we strongly encourage you to work on these exercises independently without searching explicitly for the exact answers to the exercises. Understanding someone else’s solution is very different from developing your own. Use the lecture notes and try to solve the exercises on your own. This approach will significantly enhance your learning and problem-solving skills.
    
+
    Remember, the goal is not just to complete the exercises, but to understand the concepts and improve your programming abilities. If you encounter difficulties, review the lecture materials, experiment with different approaches, and don’t hesitate to ask for clarification during class discussions.
    
+
    Later, you will find the solutions to these exercises online in the associated GitHub repository, but we will also quickly go over them next week. To access the solutions, click on the Github button on the lower right and search for the folder with today’s lecture and tutorial. Alternatively, you can ask ChatGPT or Claude to explain them to you. But please remember, the goal is not just to complete the exercises, but to understand the concepts and improve your programming abilities.
    
+
    
+
    That’s it for part II! Next week, we’ll learn about functions and how to use them to make our code more efficient and reusable.
    
+
+
+
    
+
+
     
+
+
     
+
+
+
+
+
+
\ No newline at end of file
diff --git a/part-02/tutorial-06-explore-exploit 2.pdf b/part-02/tutorial-06-explore-exploit 2.pdf
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zTB_AxtxYH2l4hb-$7 **Note**\n",
+        ">\n",
+        "> In real slot machines, the probabilities of different payouts aren’t\n",
+        "> equal. Higher payouts are much less likely to occur than lower ones.\n",
+        "> Our simplified version gives each payout an equal chance.\n",
+        "\n",
+        "To simulate playing the slot machine once, we can start as follows:"
+      ],
+      "id": "96cffb55-cbaf-4206-a192-5892c16ad448"
+    },
+    {
+      "cell_type": "code",
+      "execution_count": 2,
+      "metadata": {},
+      "outputs": [
+        {
+          "output_type": "stream",
+          "name": "stdout",
+          "text": [
+            "You bet $10\n",
+            "You won $50!\n",
+            "Your new balance is $150"
+          ]
+        }
+      ],
+      "source": [
+        "# Simulate playing the slot machine once\n",
+        "win = random.choice(payouts)\n",
+        "money += win\n",
+        "print(f\"You bet ${bet}\")\n",
+        "print(f\"You won ${win}!\")\n",
+        "print(f\"Your new balance is ${money}\")"
+      ],
+      "id": "16fe2cf6"
+    },
+    {
+      "cell_type": "markdown",
+      "metadata": {},
+      "source": [
+        "> **Tip**\n",
+        ">\n",
+        "> `+=` is a shorthand for “add and assign”. So `money += 10` is\n",
+        "> equivalent to `money = money + 10`. This also works for other\n",
+        "> arithmetic operations, like `-=`, `*=`, and `/=`.\n",
+        "\n",
+        "# Exercise 1.1 - Multiple Attempts\n",
+        "\n",
+        "Now let’s use a loop to play multiple times and track our results. Write\n",
+        "a loop that:\n",
+        "\n",
+        "1.  Plays the slot machine 10 times\n",
+        "2.  Subtracts the bet amount each time\n",
+        "3.  Adds a random payout\n",
+        "4.  Stores the results in a list"
+      ],
+      "id": "0712e964-ba91-4134-8f0e-f955b9d97f05"
+    },
+    {
+      "cell_type": "code",
+      "execution_count": 3,
+      "metadata": {},
+      "outputs": [],
+      "source": [
+        "money = 100 # Reset our money\n",
+        "bet = 10 # How much we bet each time\n",
+        "results = [] # List to store how much money we have after each play\n",
+        "\n",
+        "# YOUR CODE BELOW"
+      ],
+      "id": "ee13a44d"
+    },
+    {
+      "cell_type": "code",
+      "execution_count": 4,
+      "metadata": {},
+      "outputs": [],
+      "source": [
+        "# Check your results\n",
+        "assert len(results) == 10, \"You should have 10 results in your list\"\n",
+        "assert all(isinstance(x, (int, float)) for x in results), \"All results should be numbers\"\n",
+        "print(f\"You played the slot machine {len(results)} times\")\n",
+        "print(f\"Your final balance is ${results[-1]}\")\n",
+        "print(f\"Unfortunately, the payout rates are not realistic here...\")"
+      ],
+      "id": "bd7504e5"
+    },
+    {
+      "cell_type": "markdown",
+      "metadata": {},
+      "source": [
+        "> **Tip**\n",
+        ">\n",
+        "> Use the `append()` method to add an element to a list. For example,\n",
+        "> `results.append(money)` will add the current value of `money` to the\n",
+        "> `results` list.\n",
+        "\n",
+        "# Exercise 1.2 - Playing with a Budget\n",
+        "\n",
+        "Now let’s simulate playing the slot machine multiple times with a\n",
+        "budget. We’ll use a `while` loop to play until we run out of money. This\n",
+        "is more realistic than playing a fixed number of times, as real players\n",
+        "need to stop when they’re out of money!\n",
+        "\n",
+        "The `machine_payout_rate` represents how generous the machine is:\n",
+        "\n",
+        "-   The function `random.random()` generates a random number between 0\n",
+        "    and 1.\n",
+        "-   A rate of 2.0 means you get back exactly what you bet (on average)\n",
+        "-   Our rate of 1.5 means you could win up to 1.5 times your bet but on\n",
+        "    average you’ll get back 0.75 times your bet\n",
+        "\n",
+        "``` python\n",
+        "# Compute the payout for the current play\n",
+        "machine_payout_rate = 1.5\n",
+        "payout = random.random() * machine_payout_rate * bet\n",
+        "```\n",
+        "\n",
+        "Use a `while` loop to play the slot machine until you run out of money,\n",
+        "and store the amount of money you have after each play in the `results`\n",
+        "list. Further, print out the amount of money you have after each play\n",
+        "with a formatted string."
+      ],
+      "id": "48b6b778-d19a-4d14-9a83-adb84aab1454"
+    },
+    {
+      "cell_type": "code",
+      "execution_count": 5,
+      "metadata": {},
+      "outputs": [],
+      "source": [
+        "import random\n",
+        "\n",
+        "machine_payout_rate = 1.5 # Payout rate for the machine\n",
+        "bet = 10 # Bet size\n",
+        "money = 100 # Our starting money\n",
+        "results = [] # Store results of each play here\n",
+        "\n",
+        "# YOUR CODE BELOW \n"
+      ],
+      "id": "65dbed59"
+    },
+    {
+      "cell_type": "code",
+      "execution_count": 6,
+      "metadata": {},
+      "outputs": [],
+      "source": [
+        "# Check your results\n",
+        "assert len(results) > 0, \"You should have at least one result\"\n",
+        "assert all(isinstance(x, (int, float)) for x in results), \"All results should be numbers\"\n",
+        "assert results[-1] <= bet, \"Should stop playing when money is less than bet amount\"\n",
+        "assert all(abs(results[i] - results[i-1]) <= bet * machine_payout_rate for i in range(1, len(results))), \"Each play should not change money by more than maximum possible payout\"\n",
+        "print(f\"You played the slot machine {len(results)} times\")"
+      ],
+      "id": "1b541d43"
+    },
+    {
+      "cell_type": "markdown",
+      "metadata": {},
+      "source": [
+        "# Section 2 - Nested Loops\n",
+        "\n",
+        "Now let’s use nested loops to try different slot machines with different\n",
+        "payout rates. This is where exploration comes in! Nested loops are a way\n",
+        "to repeat a loop multiple times, and we can use them to try different\n",
+        "options. It’s essentially a loop inside another loop.\n",
+        "\n",
+        "> **Tip**\n",
+        ">\n",
+        "> Nested loops are like a clock: the outer loop is like the hour hand\n",
+        "> (moves slowly), and the inner loop is like the minute hand (completes\n",
+        "> a full cycle for each move of the hour hand).\n",
+        "\n",
+        "For example, `for machine in range(3)` will run a loop 3 times. We can\n",
+        "use nested loops to try all combinations of two different options."
+      ],
+      "id": "7002eb9d-254d-4d3c-b164-3e27e7b4f80c"
+    },
+    {
+      "cell_type": "code",
+      "execution_count": 7,
+      "metadata": {},
+      "outputs": [
+        {
+          "output_type": "stream",
+          "name": "stdout",
+          "text": [
+            "Machine Nr. 0, Payout Nr. 0\n",
+            "Machine Nr. 0, Payout Nr. 1\n",
+            "Machine Nr. 0, Payout Nr. 2\n",
+            "Machine Nr. 0, Payout Nr. 3\n",
+            "Machine Nr. 1, Payout Nr. 0\n",
+            "Machine Nr. 1, Payout Nr. 1\n",
+            "Machine Nr. 1, Payout Nr. 2\n",
+            "Machine Nr. 1, Payout Nr. 3\n",
+            "Machine Nr. 2, Payout Nr. 0\n",
+            "Machine Nr. 2, Payout Nr. 1\n",
+            "Machine Nr. 2, Payout Nr. 2\n",
+            "Machine Nr. 2, Payout Nr. 3"
+          ]
+        }
+      ],
+      "source": [
+        "for machine in range(3):\n",
+        "    for payout in range(4):\n",
+        "        print(f\"Machine Nr. {machine}, Payout Nr. {payout}\")"
+      ],
+      "id": "97c8268d"
+    },
+    {
+      "cell_type": "markdown",
+      "metadata": {},
+      "source": [
+        "# Exercise 2.1 - Simulating Multiple Machines\n",
+        "\n",
+        "The setup is the same as in Exercise 1.2, but we’re now comparing three\n",
+        "different machines, each with its own payout rate. Use a `while` loop\n",
+        "for each machine and a `for` loop to try all machines. As the bank\n",
+        "always wins, we’re not interested in the results for each machine, but\n",
+        "rather in the number of times we can play each machine before we run out\n",
+        "of money.\n",
+        "\n",
+        "Store the number of plays in a list called `plays` with three elements,\n",
+        "one for each machine. The goal is to find out which machine lets us play\n",
+        "the longest with our budget. This is a common exploration strategy: try\n",
+        "each option several times to understand its characteristics."
+      ],
+      "id": "5d563971-923f-4b8c-96b2-33062a9c4aa1"
+    },
+    {
+      "cell_type": "code",
+      "execution_count": 8,
+      "metadata": {},
+      "outputs": [],
+      "source": [
+        "import random\n",
+        "# Different machines might have different payout rates\n",
+        "machine_1_payout_rate = 1.2\n",
+        "machine_2_payout_rate = 1.5\n",
+        "machine_3_payout_rate = 1.8\n",
+        "\n",
+        "bet = 10 # Bet size at each play\n",
+        "budget = 100 # Our starting money for each machine!\n",
+        "plays = [0, 0, 0] # List to store number of plays for each machine\n",
+        "\n",
+        "# YOUR CODE BELOW"
+      ],
+      "id": "1fba9da8"
+    },
+    {
+      "cell_type": "code",
+      "execution_count": 9,
+      "metadata": {},
+      "outputs": [],
+      "source": [
+        "# Check your results\n",
+        "assert len(plays) == 3, \"Should have results for three machines\"\n",
+        "assert all(isinstance(x, int) and x >= 0 for x in plays), \"Number of plays should be non-negative integers\"\n",
+        "assert all(x <= budget/bet * 6 for x in plays), \"Number of plays seems unreasonably high given budget\"\n",
+        "print(f\"You played the slot machine {plays[0]} times on machine 1\")\n",
+        "print(f\"You played the slot machine {plays[1]} times on machine 2\")\n",
+        "print(f\"You played the slot machine {plays[2]} times on machine 3\")"
+      ],
+      "id": "951ce1ef"
+    },
+    {
+      "cell_type": "markdown",
+      "metadata": {},
+      "source": [
+        "# Exercise 2.2 - Exploring the Machines\n",
+        "\n",
+        "Now let’s find out which machine is the best and which one is the worst\n",
+        "by comparing the number of plays for each machine. Store the index of\n",
+        "the best machine in `best_machine` and the index of the worst machine in\n",
+        "`worst_machine`. You can use the `max(plays)` function to find the\n",
+        "maximum number of plays in the `plays` list and the\n",
+        "`plays.index(max(plays))` function to find the index of the maximum\n",
+        "number of plays."
+      ],
+      "id": "5ca9f212-747c-4ca5-ba64-c5eb4e1f9941"
+    },
+    {
+      "cell_type": "code",
+      "execution_count": 10,
+      "metadata": {},
+      "outputs": [],
+      "source": [
+        "# YOUR CODE BELOW"
+      ],
+      "id": "9356b267"
+    },
+    {
+      "cell_type": "code",
+      "execution_count": 11,
+      "metadata": {},
+      "outputs": [],
+      "source": [
+        "# Check your results\n",
+        "assert isinstance(best_machine, int) and 0 <= best_machine <= 2, \"Best machine should be 0, 1, or 2\"\n",
+        "assert isinstance(worst_machine, int) and 0 <= worst_machine <= 2, \"Worst machine should be 0, 1, or 2\"\n",
+        "assert best_machine != worst_machine, \"Best and worst machine cannot be the same\"\n",
+        "print(f\"The best machine is machine {best_machine}\")\n",
+        "print(f\"The worst machine is machine {worst_machine}\")"
+      ],
+      "id": "dd520673"
+    },
+    {
+      "cell_type": "markdown",
+      "metadata": {},
+      "source": [
+        "# Conclusion\n",
+        "\n",
+        "Excellent work! You’ve successfully combined multiple programming\n",
+        "concepts to tackle a real explore-exploit problem:\n",
+        "\n",
+        "-   Variables and types for tracking money and bets\n",
+        "-   Lists for storing payouts and results\n",
+        "-   Loops (including nested loops) for testing different machines\n",
+        "-   Conditions for finding the best machine\n",
+        "\n",
+        "This is a simplified version of how casinos and gambling companies might\n",
+        "analyze their games, though in reality, they use much more sophisticated\n",
+        "algorithms! Remember though, that the casino always wins!\n",
+        "\n",
+        "# Solutions\n",
+        "\n",
+        "You will likely find solutions to most exercises online. However, we\n",
+        "strongly encourage you to work on these exercises independently without\n",
+        "searching explicitly for the exact answers to the exercises.\n",
+        "Understanding someone else’s solution is very different from developing\n",
+        "your own. Use the lecture notes and try to solve the exercises on your\n",
+        "own. This approach will significantly enhance your learning and\n",
+        "problem-solving skills.\n",
+        "\n",
+        "Remember, the goal is not just to complete the exercises, but to\n",
+        "understand the concepts and improve your programming abilities. If you\n",
+        "encounter difficulties, review the lecture materials, experiment with\n",
+        "different approaches, and don’t hesitate to ask for clarification during\n",
+        "class discussions.\n",
+        "\n",
+        "Later, you will find the solutions to these exercises online in the\n",
+        "associated GitHub repository, but we will also quickly go over them next\n",
+        "week. To access the solutions, click on the Github button on the lower\n",
+        "right and search for the folder with today’s lecture and tutorial.\n",
+        "Alternatively, you can ask ChatGPT or Claude to explain them to you. But\n",
+        "please remember, the goal is not just to complete the exercises, but to\n",
+        "understand the concepts and improve your programming abilities.\n",
+        "\n",
+        "------------------------------------------------------------------------\n",
+        "\n",
+        "*That’s it for part II! Next week, we’ll learn about functions and how\n",
+        "to use them to make our code more efficient and reusable.*"
+      ],
+      "id": "be7fbc55-ae8a-4350-acaf-368b48bf4542"
+    }
+  ],
+  "nbformat": 4,
+  "nbformat_minor": 5,
+  "metadata": {
+    "kernelspec": {
+      "name": "python3",
+      "display_name": "Python 3 (ipykernel)",
+      "language": "python",
+      "path": "/Users/tvlcek/miniconda3/share/jupyter/kernels/python3"
+    },
+    "language_info": {
+      "name": "python",
+      "codemirror_mode": {
+        "name": "ipython",
+        "version": "3"
+      },
+      "file_extension": ".py",
+      "mimetype": "text/x-python",
+      "nbconvert_exporter": "python",
+      "pygments_lexer": "ipython3",
+      "version": "3.12.7"
+    }
+  }
+}
\ No newline at end of file
diff --git a/part-02/tutorial-06-explore-exploit.html b/part-02/tutorial-06-explore-exploit.html
index d3c8fdd..1cf31bc 100644
--- a/part-02/tutorial-06-explore-exploit.html
+++ b/part-02/tutorial-06-explore-exploit.html
@@ -220,6 +220,41 @@
   
  06 - Exploration
   
    
+
+      
+  
+        
  • 
+      
     
+            
+           
+      
    
+      
   
    • 
@@ -296,7 +331,7 @@ 
    Introduction
    
 
    
 
    Section 1 - Setting Up Our Casino
    
 
    First, let’s create a simple slot machine simulator using what we learned about variables and lists. In order to do this, we’ll need to import the random module, which we can do using the import statement. Don’t worry about the details of this statement for now - we’ll cover it in more detail in a future tutorial.
    
-
    
+
    
 
    import random
 
 # Initial setup
@@ -331,7 +366,7 @@ 
    Section 1 - Setting Up Our Casino
    
 
    
 
    
 
    To simulate playing the slot machine once, we can start as follows:
    
-
    
+
    
 
    # Simulate playing the slot machine once
 win = random.choice(payouts)
 money += win
@@ -340,8 +375,8 @@ 
    Section 1 - Setting Up Our Casino
    
 print(f"Your new balance is ${money}")
    
 
    
 
    You bet $10
-You won $5!
-Your new balance is $105
    
+You won $0!
+Your new balance is $100
    
 
    
 
    
 
    
@@ -367,14 +402,14 @@ 
    Exercise 1.1 - Multiple Attempts
    
 
  • Adds a random payout
    • 
 
  • Stores the results in a list
    • 
 
-
    
+
    
 
    money = 100 # Reset our money
 bet = 10 # How much we bet each time
 results = [] # List to store how much money we have after each play
 
 # YOUR CODE BELOW
    
 
    
-
    
+
    
 
    
 Code
 
    # Check your results
@@ -412,7 +447,7 @@ 
    Exercise 1.2 - Playing with a Budget
    
 machine_payout_rate = 1.5
 payout = random.random() * machine_payout_rate * bet
    
 
    Use a while loop to play the slot machine until you run out of money, and store the amount of money you have after each play in the results list. Further, print out the amount of money you have after each play with a formatted string.
    
-
    
+
    
 
    import random
 
 machine_payout_rate = 1.5 # Payout rate for the machine
@@ -422,7 +457,7 @@ 
    Exercise 1.2 - Playing with a Budget
    
 
 # YOUR CODE BELOW 
    
 
    
-
    
+
    
 
    
 Code
 
    # Check your results
@@ -451,7 +486,7 @@ 
    Section 2 - Nested Loops
    
 
    
 
    
 
    For example, for machine in range(3) will run a loop 3 times. We can use nested loops to try all combinations of two different options.
    
-
    
+
    
 
    for machine in range(3):
     for payout in range(4):
         print(f"Machine Nr. {machine}, Payout Nr. {payout}")
    
@@ -475,7 +510,7 @@ 
    Section 2 - Nested Loops
    
 
    Exercise 2.1 - Simulating Multiple Machines
    
 
    The setup is the same as in Exercise 1.2, but we’re now comparing three different machines, each with its own payout rate. Use a while loop for each machine and a for loop to try all machines. As the bank always wins, we’re not interested in the results for each machine, but rather in the number of times we can play each machine before we run out of money.
    
 
    Store the number of plays in a list called plays with three elements, one for each machine. The goal is to find out which machine lets us play the longest with our budget. This is a common exploration strategy: try each option several times to understand its characteristics.
    
-
    
+
    
 
    import random
 # Different machines might have different payout rates
 machine_1_payout_rate = 1.2
@@ -488,7 +523,7 @@ 
    Exercise 2.1 - Simulating Multiple Machines
    
 
 # YOUR CODE BELOW
    
 
    
-
    
+
    
 
    
 Code
 
    # Check your results
@@ -504,10 +539,10 @@ 
    Exercise 2.1 - Simulating Multiple Machines
    
 
    
 
    Exercise 2.2 - Exploring the Machines
    
 
    Now let’s find out which machine is the best and which one is the worst by comparing the number of plays for each machine. Store the index of the best machine in best_machine and the index of the worst machine in worst_machine. You can use the max(plays) function to find the maximum number of plays in the plays list and the plays.index(max(plays)) function to find the index of the maximum number of plays.
    
-
    
+
    
 
    # YOUR CODE BELOW
    
 
    
-
    
+
    
 
    
 Code
 
    # Check your results
diff --git a/part-02/tutorial-06-explore-exploit.ipynb b/part-02/tutorial-06-explore-exploit.ipynb
index 92b4d68..b0a8bd2 100644
--- a/part-02/tutorial-06-explore-exploit.ipynb
+++ b/part-02/tutorial-06-explore-exploit.ipynb
@@ -24,7 +24,7 @@
         "statement. Don’t worry about the details of this statement for now -\n",
         "we’ll cover it in more detail in a future tutorial."
       ],
-      "id": "ffc193ad-0ac4-4919-955a-7a3928e7ef88"
+      "id": "c1bbd37e-d285-4e9c-87f3-eb6f7141f3f8"
     },
     {
       "cell_type": "code",
@@ -56,7 +56,7 @@
         "for payout in payouts:\n",
         "    print(f\"🎰 Win ${payout}\")"
       ],
-      "id": "7f3438f4"
+      "id": "97ca5604"
     },
     {
       "cell_type": "markdown",
@@ -76,7 +76,7 @@
         "\n",
         "To simulate playing the slot machine once, we can start as follows:"
       ],
-      "id": "846187e1-ffc8-434c-9660-4015387a084b"
+      "id": "95c32077-b9c0-4b25-8d48-491db35dcaef"
     },
     {
       "cell_type": "code",
@@ -88,8 +88,8 @@
           "name": "stdout",
           "text": [
             "You bet $10\n",
-            "You won $0!\n",
-            "Your new balance is $100"
+            "You won $20!\n",
+            "Your new balance is $120"
           ]
         }
       ],
@@ -101,7 +101,7 @@
         "print(f\"You won ${win}!\")\n",
         "print(f\"Your new balance is ${money}\")"
       ],
-      "id": "50cf1f0d"
+      "id": "a6f7e34b"
     },
     {
       "cell_type": "markdown",
@@ -123,7 +123,7 @@
         "3.  Adds a random payout\n",
         "4.  Stores the results in a list"
       ],
-      "id": "43ed32a9-647e-4705-8673-c827e9490b1c"
+      "id": "ba9f4c80-e92e-4ec2-b939-34b6cc7ea307"
     },
     {
       "cell_type": "code",
@@ -137,7 +137,7 @@
         "\n",
         "# YOUR CODE BELOW"
       ],
-      "id": "2b0d92ac"
+      "id": "2af41a2e"
     },
     {
       "cell_type": "code",
@@ -152,7 +152,7 @@
         "print(f\"Your final balance is ${results[-1]}\")\n",
         "print(f\"Unfortunately, the payout rates are not realistic here...\")"
       ],
-      "id": "b50e036c"
+      "id": "50dd1864"
     },
     {
       "cell_type": "markdown",
@@ -190,7 +190,7 @@
         "list. Further, print out the amount of money you have after each play\n",
         "with a formatted string."
       ],
-      "id": "bcaf264c-a6e4-44d3-a04d-1f2806652c35"
+      "id": "c09517af-cb14-4add-9d5d-8cc1f55c159e"
     },
     {
       "cell_type": "code",
@@ -207,7 +207,7 @@
         "\n",
         "# YOUR CODE BELOW \n"
       ],
-      "id": "5822ac84"
+      "id": "6ac006bb"
     },
     {
       "cell_type": "code",
@@ -222,7 +222,7 @@
         "assert all(abs(results[i] - results[i-1]) <= bet * machine_payout_rate for i in range(1, len(results))), \"Each play should not change money by more than maximum possible payout\"\n",
         "print(f\"You played the slot machine {len(results)} times\")"
       ],
-      "id": "0c6d0ab6"
+      "id": "20bd76e3"
     },
     {
       "cell_type": "markdown",
@@ -244,7 +244,7 @@
         "For example, `for machine in range(3)` will run a loop 3 times. We can\n",
         "use nested loops to try all combinations of two different options."
       ],
-      "id": "8a3199f2-098b-457d-900d-c6ba9d1ce93e"
+      "id": "30b3d25b-dd06-437f-97f7-2d637f7f719e"
     },
     {
       "cell_type": "code",
@@ -275,7 +275,7 @@
         "    for payout in range(4):\n",
         "        print(f\"Machine Nr. {machine}, Payout Nr. {payout}\")"
       ],
-      "id": "31044dd5"
+      "id": "c519b775"
     },
     {
       "cell_type": "markdown",
@@ -295,7 +295,7 @@
         "the longest with our budget. This is a common exploration strategy: try\n",
         "each option several times to understand its characteristics."
       ],
-      "id": "d168c83b-a92b-4464-ae67-ae644232c40e"
+      "id": "250caca4-e629-4789-989d-f8223b0ded97"
     },
     {
       "cell_type": "code",
@@ -315,7 +315,7 @@
         "\n",
         "# YOUR CODE BELOW"
       ],
-      "id": "20b7b7fe"
+      "id": "55edd0b2"
     },
     {
       "cell_type": "code",
@@ -331,7 +331,7 @@
         "print(f\"You played the slot machine {plays[1]} times on machine 2\")\n",
         "print(f\"You played the slot machine {plays[2]} times on machine 3\")"
       ],
-      "id": "4ea7b58b"
+      "id": "7e88112e"
     },
     {
       "cell_type": "markdown",
@@ -347,7 +347,7 @@
         "`plays.index(max(plays))` function to find the index of the maximum\n",
         "number of plays."
       ],
-      "id": "50f6da5a-9d06-48e1-9d14-c3c7684db8e0"
+      "id": "c19931bf-6072-466b-8ce5-42c65b277476"
     },
     {
       "cell_type": "code",
@@ -357,7 +357,7 @@
       "source": [
         "# YOUR CODE BELOW"
       ],
-      "id": "ef32bf1d"
+      "id": "8e07b34e"
     },
     {
       "cell_type": "code",
@@ -372,7 +372,7 @@
         "print(f\"The best machine is machine {best_machine}\")\n",
         "print(f\"The worst machine is machine {worst_machine}\")"
       ],
-      "id": "0230e7d8"
+      "id": "a7b94110"
     },
     {
       "cell_type": "markdown",
@@ -421,7 +421,7 @@
         "*That’s it for part II! Next week, we’ll learn about functions and how\n",
         "to use them to make our code more efficient and reusable.*"
       ],
-      "id": "23520eaf-9f1d-4c1e-ba93-19614adec770"
+      "id": "d2f910d6-36c5-4a5f-bbc6-485feb8f02bd"
     }
   ],
   "nbformat": 4,
diff --git a/part-02/tutorial-06-explore-exploit.pdf b/part-02/tutorial-06-explore-exploit.pdf
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zQfNK{cV#>TgZ+35=}36omqk1j3
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+Lecture III - Caching – Programming: Everyday Decision-Making Algorithms
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    Lecture III - Caching
    
+
    Programming: Everyday Decision-Making Algorithms
    
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+
    
+  
    Author
    
+  
    Affiliation
    
+  
+    
    
+    
    Dr. Nils Roemer 
    
+  
    
+  
    
+        
    
+            Kühne Logistics University Hamburg - Winter 2024
+          
    
+      
    
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    Caching
    
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    Caching: Making the most of limited resources
    
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+
    In the practical use of our intellect, forgetting is as important a function as remembering. – [William James]
    
+
    
+
      
+
    • Today’s lecture is on caching.
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    • The discussed topics are highly relevant for everything that has to do with computers and data.
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    • On top of that, caching is another very important concept for our everyday decision-making.
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    Let’s approach the topic using an everyday decision-making situation
    
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    • We have a problem: Our cupboard.
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    • It’s time to put things in order.
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    Question: What could we do?
    
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    • Better organization
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    • Clearing out things we no longer need
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    • Now we have two problems:
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      • Storing?
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      • Clearing out?
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    Storing
    
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    How to bring order to storage?
    
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    • Subdivide storage
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    • Efficient sorting
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    • Increase capacity
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    Subdivide storage and efficient sorting Outcome
    
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    • Time investment can improve storing.
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    • That is a difficult trade-off in itself.
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    • Nontheless: Each storage has a limited capacity.
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    Question: What do we do, when the storage is full?
    
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    We could increase the capacity
    
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    But…
    
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    • Increase capacity is costly.
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    • There is a trade-off between size and speed.
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    • Sooner or later, every storage will fill up if not cleared out.
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    Question: What types of storages can you imagine that are affected by this?
    
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    • Our cupboard
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    • Our computer (hard drive, RAM, cache, …)
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    • Our brain?!
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    Question: What is the impact of a full storage?
    
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    • Access speed drops significantly
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    • Processing time increases
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    • Overall performance decreases
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    Now we see, why clearing out is so important
    
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    • And that goes for our cupboard as well as for computers and other storages…
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    • But what stays and what goes?
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    • Question: What replacement/eviction policies can you imagine?
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      • Random Eviction
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      • First-In, First-Out (FIFO)
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      • Least Recently Used (LRU)
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    Once again, we can learn a lot from the computer sciences.
    
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    The evolution of computer memory - In the 1950s, computer science faced the same question… - …and has faced it repeatedly since then. - Processors have become faster and faster (Moore’s Law). - The demands on memory also grew.
    
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    CPU
    
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    • The processor (CPU, Central Processing Unit) is central to a computer and is often referred to as the “brain” of the system.
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    • It executes instructions and performs calculations, to process data and run programs.
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    Problem: Access Time
    
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    flowchart LR
+    subgraph Memory
+    A["Input Data"]
+    end
+    
+    subgraph CPU
+    B["Processing Data"]
+    end
+    
+    subgraph Memory
+    C["Output Data"]
+    end
+    
+    A --> B --> C
+    
+    style Memory fill:white,stroke:#01579B,stroke-width:4px
+    style CPU fill:white,stroke:#01579B,stroke-width:4px
+    style Memory fill:white,stroke:#01579B,stroke-width:4px
+    style A fill:white
+    style B fill:white
+    style C fill:white
+
    
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+
    Problem: No matter how much faster the processor gets, if input data isn’t available fast enough or can’t be stored quickly enough, the system won’t become faster overall.
    
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    Question: What is the solution?
    
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    Cache - Hierarchical memory pyramid for efficient data management
    
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    • L1 Cache, directly on CPU, very fast access time.
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    • L2 Cache, between L1 and main memory.
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    • RAM memory.
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    • Mass Storage (hard drive).
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    • The whole memory system works like a library.
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    • Find an explanation here: https://www.techtarget.com/searchstorage/definition/cache
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    Cache - Size and Speed trade-off
    
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    Library Principle
    
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    • Library storage (5 million books, Mass Storage)
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    • Subject locations (100K books, RAM)
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    • Desk (5 borrowed books, L2)
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    • Short-term memory (L1)
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    Library Principle
    
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    • The access times for the L1 and L2 cache are only so high because they only contain the most necessary data.
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    • The same should apply to your desk.
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    • Therefore, both must be cleared regularly.
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    How to clear up your?
    
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    • Optimal: Clairvoyance
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      • Store everything in the cache that will be needed
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      • Delete everything from the cache that won’t be needed
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    • Question: What is the problem with this strategy?
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    • Optimal strategy not achievable in reality
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    Realisable strategies?
    
+
      
+
    • Least recently used is the dominant strategy.
      • 
+
    • Evicts the least recently accessed item from the cache when space is needed.
      • 
+
    • Leads to much better performance on average than, for example, random eviction.
      • 
+
    • Question: Why do you think least recently used is the better strategy?
      • 
+
    
+
    
+
    
+
    Managerial and personal insights:
    
+
      
+
    • Let go of things you haven’t used in ages
      • 
+
    • Keep things where they are used
      • 
+
    • Both have been proven to contribute to a significant increase in productivity
      • 
+
    
+
    
+
    
+
    The strong limitations of caches make them a “security risk”.
    
+
      
+
    • Denial-of-Service Attacks (DoS) attacks.
+
        
+
      • Cache Flooding
        • 
+
      • Cache Poisoning
        • 
+
      • 
+
    • Overload a system with excessive requests or data.
      • 
+
    • Causing it to slow down or crash.
      • 
+
    • The system is forced to evict important data.
      • 
+
    
+
    
+
    
+
    Question: Why are the findings about cache so important for humans?
    
+
    
+
    Your Brain is a Cache, Not a Database -[Joe Chrysler]
    
+
    
+
    
+
    
+
    Weaknesses of efficient memory systems also apply to the human brain.
    
+
    Productivity and creativity are negatively affected by:
    
+
      
+
    • Overload (too much)
      • 
+
    • Exhaustion (too long)
      • 
+
    • Context switching (interruption of “flow”, 23 minutes to get back on track)
      • 
+
    • Distraction (Cache Flooding)
      • 
+
    • Fake News (Cache Poisoning)
      • 
+
    
+
    This can lead to burnout.
    
+
    
+
    
+
    Question: What do you think should we do about it?
    
+
    
+
    
+
    Stolen Focus: Why You Can’t Pay Attention - Key Insights I
    
+
    Main Idea:
    
+
      
+
    • Modern life is eroding our ability to concentrate and engage deeply, with societal factors affecting personal focus.
      • 
+
    • The reason for that has much to do with the way our brain works and how we interact with technology.
      • 
+
    
+
    
+
    
+
    Stolen Focus: Why You Can’t Pay Attention - Key Insights II
    
+
    Key Causes of Attention Loss:
    
+
      
+
    • Technology & Social Media: Designed to capture and keep attention, leading to fragmented focus.
      • 
+
    • Constant Interruptions: Notifications and multitasking disrupt deep work and concentration.
      • 
+
    • Environmental & Lifestyle Factors: Poor sleep, stress, and diet impact cognitive function.
      • 
+
    
+
    
+
    
+
    Stolen Focus: Why You Can’t Pay Attention - Key Insights III
    
+
    Consequences:
    
+
      
+
    • Reduced ability to think critically and creatively.
      • 
+
    • Difficulty sustaining attention on meaningful tasks.
      • 
+
    
+
    
+
    
+
    Stolen Focus: Why You Can’t Pay Attention - Key Insights IV
    
+
    Solutions Suggested:
    
+
      
+
    • Limit screen time and practice “monotasking.”
      • 
+
    • Prioritize sleep, nutrition, and mindful habits.
      • 
+
    
+
    
+
    
+
    Stolen Focus: Why You Can’t Pay Attention - Key Insights V
    
+
      
+
    • You can find a comprehensive summary here:
      • 
+
    
+
    
+
    https://www.youtube.com/watch?v=DqlywBxYELw
    
+
    
+
      
+
    • But even better: read the book!
      • 
+
    
+
    
+
    
+
    Stolen Focus: Why You Can’t Pay Attention - Key Insights VI
    
+
    
+
    
+
    
+
    
+
    
+
    
+
    Mitigation
    
+
      
+
    • Distraction can hardly be avoided in today’s world but can be mitigated.
      • 
+
    • This is particularly important for managers.
      • 
+
    • This lecture is designed to raise your awareness of what you can do to keep your brain working efficiently.
      • 
+
    
+
    
+
    Awareness I
    
+
    Train awareness
    
+
      
+
    • Spotlight – immediate goals – Focus
      • 
+
    • Starlight – medium-term goals – Wishes
      • 
+
    • Daylight – long-term goals – Values
      • 
+
    
+
    
+
    
+
    Awareness II
    
+
      
+
    • Prioritization
      • 
+
    • Structure (Schedule)
      • 
+
    • Breaks
      • 
+
    • Enable flow (dedicated workspace, manage notifications, clear communication)
      • 
+
    • Meditation & exercise
      • 
+
    
+
    
+
    
+
    
+
    Literature
    
+
    
+
    Interesting literature to start
    
+
      
+
    • Christian, B., & Griffiths, T. (2016). Algorithms to live by: the computer science of human decisions. First international edition. New York, Henry Holt and Company.1
      • 
+
    • Ferguson, T.S. (1989) ‘Who solved the secretary problem?’, Statistical Science, 4(3). doi:10.1214/ss/1177012493.
      • 
+
    
+
    
+
    
+
    Books on Programming
    
+
      
+
    • Downey, A. B. (2024). Think Python: How to think like a computer scientist (Third edition). O’Reilly. Here
      • 
+
    • Elter, S. (2021). Schrödinger programmiert Python: Das etwas andere Fachbuch (1. Auflage). Rheinwerk Verlag.
      • 
+
    
+
    . . .
    
+
    
+
    
+
    
+
+
    
+
    
+Note
+
    
+
    
+
    
+
    Think Python is a great book to start with. It’s available online for free. Schrödinger Programmiert Python is a great alternative for German students, as it is a very playful introduction to programming with lots of examples.
    
+
    
+
    
+
    
+
    
+
    More Literature
    
+
    For more interesting literature, take a look at the literature list of this course.
    
+
+
+
    
+
    
+
+
+
    Footnotes
    
+
+
      
+
    1. The main inspiration for this lecture. Nils and I have read it and discussed it in depth, always wanting to translate it into a course.↩︎
      2. 
+
    
+
     
+
+
     
+
+
+
+
+
+
\ No newline at end of file
diff --git a/part-03/lecture-caching.html b/part-03/lecture-caching.html
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@@ -83,9 +83,7 @@
       
-        
+        
         
       
    
+
+      
+  
+        
  • 
+      
     
+            
+ 03 Caching
+          
+            
+           
+      
    
+      
   
    • 
@@ -297,7 +330,7 @@ 
    On this page
    
 
 
    
 
-
    
+
    
 
    
 
    Lecture III - Caching
    
 
    Programming: Everyday Decision-Making Algorithms
    
diff --git a/part-03/tutorial-07-recap 2.html b/part-03/tutorial-07-recap 2.html
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@@ -0,0 +1,1057 @@
+
+
+
+
+
+
+
+
+
+Tutorial III.I - Caching and Recap – Programming: Everyday Decision-Making Algorithms
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
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+
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+
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+
    
+  
    
+  
+
    
+
+
    
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+  
+
    
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+    
+
+
    
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+
    
+
    
+
    Tutorial III.I - Caching and Recap
    
+
    Programming: Everyday Decision-Making Algorithms
    
+
    
+
+
+
+
    
+
+    
+  
+    
+  
    
+  
+
+
+
    
+
+
+
    
+
    Introduction
    
+
    Throughout our previous tutorials, we’ve explored fundamental programming concepts through the lens of everyday decision-making. Now, let’s connect these concepts to another important algorithmic idea: caching.
    
+
    The concepts we’ve learned map directly to caching principles:
    
+
      
+
    • Variables → Like cache entries (storing specific pieces of information)
      • 
+
    • Comparisons → Like cache eviction policies (what we keep/remove)
      • 
+
    • Lists → Like cache storage (what we remember)
      • 
+
    • Loops → Like cache maintenance (how we update our knowledge)
      • 
+
    
+
    
+
    
+
    
+
+
    
+
    
+What is Caching?
+
    
+
    
+
    
+
    Remember today’s lecture. Think of caching for example like your brain’s short-term memory. When you frequently need certain information (like your friend’s phone number), you keep it readily available instead of looking it up each time.
    
+
    
+
    
+
    
+
    
+
    Section 1 - Variables and Datatypes
    
+
    Just as a cache stores different types of data, Python variables can hold various datatypes. Let’s explore this through a simple caching system for a coffee shop.
    
+
    
+
    # Basic cache for coffee orders
+last_order = "Latte" # String cache
+drink_temperature = 75.5 # Float cache
+is_favorite = True # Boolean cache
+num_orders = 3 # Integer cache
    
+
    
+
    
+
    
+
    
+
+
    
+
    
+Cache Types in Real Life
+
    
+
    
+
    
+
      
+
    • Strings: Names, orders, preferences
      • 
+
    • Floats: Prices, ratings, temperatures
      • 
+
    • Booleans: Membership status, availability
      • 
+
    • Integers: Visit counts, inventory levels
      • 
+
    
+
    
+
    
+
    
+
    Exercise 1.1: Create a simple cache system for your favorite restaurant orders
    
+
      
+
    1. Create a variable last_meal for the last meal you ordered (as a string)
      2. 
+
    2. Store its price in a variable price (as a float)
      3. 
+
    3. Whether you would order it again in a variable would_order_again (as a boolean)
      4. 
+
    4. How many times you’ve ordered it in the last month in a variable num_orders (as an integer)
      5. 
+
    
+
    
+
    # YOUR CODE BELOW
    
+
    
+
    
+
    
+Code
+
    # Assertions to verify your solution
+assert isinstance(last_meal, str), "last_meal should be a string"
+assert isinstance(price, float), "price should be a float"
+assert isinstance(would_order_again, bool), "would_order_again should be a boolean"
+assert isinstance(num_orders, int), "num_orders should be an integer"
+print(f"Last meal: {last_meal}, price: {price}, would order again: {would_order_again}, number of orders in the last month: {num_orders}")
    
+
    
+
    
+
    
+
    
+
    
+
    Section 2 - Comparisons
    
+
    Cache systems need to make decisions about what data to keep or remove. This is similar to how we use comparisons in Python. For example, the following code just checks a simple cache eviction policy based on the access count and when an item was last accessed.
    
+
    
+
    # Simple cache eviction policy
+access_count = 15
+last_accessed_minutes = 25
+
+evict = False
+if access_count > 10 and last_accessed_minutes < 30:
+    evict = True
+
+print(f"Based on {access_count} accesses and the last access {last_accessed_minutes} minutes ago, should we evict? {evict}")
    
+
    
+
    Based on 15 accesses and the last access 25 minutes ago, should we evict? True
    
+
    
+
    
+
    
+
    
+
    
+
+
    
+
    
+Cache Eviction
+
    
+
    
+
    
+
    Just like deciding what to remove from your phone when storage is full, cache eviction policies help determine what data to keep or remove based on usage patterns.
    
+
    
+
    
+
    
+
    Exercise 2.1: Create a decision system for your favorite song
    
+
      
+
    1. Write a small decision system for your cached favorite song favorite_song
      2. 
+
    2. Use at least two conditions based on the song’s play count and last played time (play_count and last_played_minutes_ago)
      3. 
+
    3. You can set the parameters for the conditions yourself
      4. 
+
    4. Save the result of the decision in a variable should_evict
      5. 
+
    5. Print the result of whether we should evict the song or not
      6. 
+
    
+
    
+
    # YOUR CODE BELOW
    
+
    
+
    
+
    
+Code
+
    # Assertions to verify your solution
+assert isinstance(favorite_song, str), "favorite_song should be a string"
+assert isinstance(play_count, int), "play_count should be an integer"
+assert isinstance(last_played_minutes_ago, int), "last_played_minutes_ago should be an integer"
+assert isinstance(should_evict, bool), "should_evict should be a boolean"
+print(f"Favorite song: {favorite_song}, play count: {play_count}, last played minutes ago: {last_played_minutes_ago}, should evict: {should_evict}")
    
+
    
+
    
+
    
+
    
+
    
+
    Section 3 - Lists and Tuples
    
+
    Lists work like a cache’s storage system, holding multiple items that we might need later. Tuples are similar, but they are immutable. This means that once a tuple is created, its contents cannot be changed. To measure the size of a list or tuple, we can use the len() function.
    
+
    
+
    
+
    
+
+
    
+
    
+Think about the following code yourself!
+
    
+
    
+
    
+
    Before running the code below, try to predict:
    
+
      
+
    1. What will be in the cache after adding “Carnival of Rust”?
      2. 
+
    2. Which song will be removed?
      3. 
+
    
+
    
+
    
+
    
+
    # Recently played songs cache
+recent_songs = ["Lithonia", "Leon", "WHEN THE MUSIC STOPS", "Chop Suey", "Rain of Fire"]
+max_cache_size = 5
+new_song = "Carnival of Rust"
+
+# Cache maintenance
+if len(recent_songs) >= max_cache_size:
+    poped_song = recent_songs.pop() # Remove oldest song
+    print(f"Removed '{poped_song}' from cache")
+
+if len(recent_songs) < max_cache_size:
+    recent_songs.insert(0, new_song) # Add new song at beginning
+    print(f"Added '{new_song}' to cache")
+
+print(f"Current cache: {recent_songs}")
    
+
    
+
    
+
    
+
    
+
+
    
+
    
+Tip
+
    
+
    
+
    
+
    This behavior would not have been possible with a tuple, as we cannot change the contents of a tuple once it is created!
    
+
    
+
    
+
    We can also use lists to store tuples, which is useful for storing multiple items with different properties. For example, we can store the name and price of items in a shopping cart.
    
+
    
+
    # Shopping cart cache of a very expensive trip to the Apple store
+shopping = [("MacBook Pro", 1999.99), ("AirPods", 159.99), ("Apple Watch", 399.99)]
+
+print(f"Current shopping cart: {shopping}")
    
+
    
+
    Current shopping cart: [('MacBook Pro', 1999.99), ('AirPods', 159.99), ('Apple Watch', 399.99)]
    
+
    
+
    
+
    
+
    Exercise 3.1: Create a shopping cart cache
    
+
      
+
    1. Make a list shopping_cart of five recently viewed items in your shopping cart
      2. 
+
    2. Create tuples for the item details (name and price) and add them to the list
      3. 
+
    3. Ensure that the name is a string and the price is a float
      4. 
+
    
+
    
+
    
+
    
+
+
    
+
    
+Tip
+
    
+
    
+
    
+
    First, create a list. Inside the list, the entries should be tuples of the item name and price.
    
+
    
+
    
+
    
+
    # YOUR CODE BELOW
    
+
    
+
    
+
    
+Code
+
    # Assertions to verify your solution
+assert len(shopping_cart) == 5, "shopping_cart should have 5 items"
+assert isinstance(shopping_cart, list), "shopping_cart should be a list"
+assert all(isinstance(item, tuple) for item in shopping_cart), "All items in shopping_cart should be tuples"
+assert all(isinstance(item[0], str) and isinstance(item[1], (int, float)) for item in shopping_cart), "All items in shopping_cart should be tuples with a string and a number"
+print("Great job! Your shopping cart is ready.")
    
+
    
+
    
+
    
+
    
+
    
+
    Section 4 - Loops
    
+
    Loops are essential for cache maintenance and updates, just like how we periodically clean up our browser cache. We know two types of loops: for and while. The for loop is used when we know the number of iterations beforehand, while the while loop is used when we don’t.
    
+
    
+
    # Cache cleanup process
+cached_items = [("fork", 5), ("spoon", 0), ("knife", 12)] # (item, access_count)
+min_access_count = 10 # Minimum access count to keep an item
+
+items_to_remove = []
+for item, count in cached_items:
+    if count < min_access_count:
+        items_to_remove.append((item, count))
+
+print(f"Items to remove: {items_to_remove}")
+
+for item in items_to_remove:
+    cached_items.remove(item)
+
+print(f"Cached items after cleanup: {cached_items}")
    
+
    
+
    Items to remove: [('fork', 5), ('spoon', 0)]
+Cached items after cleanup: [('knife', 12)]
    
+
    
+
    
+
    
+
    Exercise 4.1: Clean up a browser history cache
    
+
      
+
    1. Write a loop to remove sites with low visit counts
      2. 
+
    2. If the site has been visited less than 6 times, remove it from the cache
      3. 
+
    3. Print the browser history after cleanup
      4. 
+
    
+
    
+
    
+
    
+
+
    
+
    
+Tip
+
    
+
    
+
    
+
    Be careful with the loop. You need to iterate over the list and remove items from it. If you remove items directly from the list while iterating over it, you won’t get the correct answer, as the list will change size while you iterate over it. Thus, you first need to create a list of items to keep and at the end replace the old list with the new one.
    
+
    
+
    
+
    
+
    browser_history = [
+    ("google.com", 10), 
+    ("youtube.de", 5), 
+    ("amazon.de", 1), 
+    ("netflix.de", 2), 
+    ("github.com", 15)
+]
+# YOUR CODE BELOW
    
+
    
+
    
+
    
+Code
+
    # Assertions to verify your solution
+assert len(browser_history) == 2, "browser_history should have 2 items"
+assert isinstance(browser_history, list), "browser_history should be a list"
+assert all(isinstance(item, tuple) for item in browser_history), "All items in browser_history should be tuples"
    
+
    
+
    
+
    
+
    
+
    
+
    Conclusion
    
+
    Understanding these programming fundamentals through the lens of caching helps us see how computers and human decision-making often follow similar patterns. Whether we’re deciding which restaurant to visit or which data to keep in memory, the principles remain surprisingly similar.
    
+
    
+
    
+
    Solutions
    
+
    You will likely find solutions to most exercises online. However, we strongly encourage you to work on these exercises independently without searching explicitly for the exact answers to the exercises. Understanding someone else’s solution is very different from developing your own. Use the lecture notes and try to solve the exercises on your own. This approach will significantly enhance your learning and problem-solving skills.
    
+
    Remember, the goal is not just to complete the exercises, but to understand the concepts and improve your programming abilities. If you encounter difficulties, review the lecture materials, experiment with different approaches, and don’t hesitate to ask for clarification during class discussions.
    
+
    Later, you will find the solutions to these exercises online in the associated GitHub repository, but we will also quickly go over them next week. To access the solutions, click on the Github button on the lower right and search for the folder with today’s lecture and tutorial. Alternatively, you can ask ChatGPT or Claude to explain them to you. But please remember, the goal is not just to complete the exercises, but to understand the concepts and improve your programming abilities.
    
+
    
+
    In the next tutorial, we’ll dive deeper into more advanced strategies and some new topics!
    
+
+
+
    
+
+
     
+
+
     
+
+
+
+
+
+
\ No newline at end of file
diff --git a/part-03/tutorial-07-recap.html b/part-03/tutorial-07-recap.html
index 4ff2d03..6ba8e3f 100644
--- a/part-03/tutorial-07-recap.html
+++ b/part-03/tutorial-07-recap.html
@@ -113,9 +113,7 @@
       
-        
+        
         
       
    
+
+      
+  
+        
  • 
+      
     
+            
+ 03 Caching
+          
+            
+           
+      
    
+      
   
    • 
@@ -281,7 +314,7 @@ 
    On this page
    
 
 
    
 
-
    
+
    
 
    
 
    Tutorial III.I - Caching and Recap
    
 
    Programming: Everyday Decision-Making Algorithms
    
@@ -328,7 +361,7 @@ 
    Introduction
    
 
    
 
    Section 1 - Variables and Datatypes
    
 
    Just as a cache stores different types of data, Python variables can hold various datatypes. Let’s explore this through a simple caching system for a coffee shop.
    
-
    
+
    
 
    # Basic cache for coffee orders
 last_order = "Latte" # String cache
 drink_temperature = 75.5 # Float cache
@@ -361,10 +394,10 @@ 
    
+
    
 
    # YOUR CODE BELOW
    
 
    
-
    
+
    
 
    
 Code
 
    # Assertions to verify your solution
@@ -380,7 +413,7 @@ 
    
 
    Section 2 - Comparisons
    
 
    Cache systems need to make decisions about what data to keep or remove. This is similar to how we use comparisons in Python. For example, the following code just checks a simple cache eviction policy based on the access count and when an item was last accessed.
    
-
    
+
    
 
    # Simple cache eviction policy
 access_count = 15
 last_accessed_minutes = 25
@@ -416,10 +449,10 @@ 
    
+
    
 
    # YOUR CODE BELOW
    
 
    
-
    
+
    
 
    
 Code
 
    # Assertions to verify your solution
@@ -452,7 +485,7 @@ 
    Section 3 - Lists and Tuples
    
 
 
    
 
    
-
    
+
    
 
    # Recently played songs cache
 recent_songs = ["Lithonia", "Leon", "WHEN THE MUSIC STOPS", "Chop Suey", "Rain of Fire"]
 max_cache_size = 5
@@ -483,7 +516,7 @@ 
    Section 3 - Lists and Tuples
    
 
    
 
    
 
    We can also use lists to store tuples, which is useful for storing multiple items with different properties. For example, we can store the name and price of items in a shopping cart.
    
-
    
+
    
 
    # Shopping cart cache of a very expensive trip to the Apple store
 shopping = [("MacBook Pro", 1999.99), ("AirPods", 159.99), ("Apple Watch", 399.99)]
 
@@ -512,10 +545,10 @@ 
    
 
    First, create a list. Inside the list, the entries should be tuples of the item name and price.
    
 
    
 
    
-
    
+
    
 
    # YOUR CODE BELOW
    
 
    
-
    
+
    
 
    
 Code
 
    # Assertions to verify your solution
@@ -531,7 +564,7 @@ 
    
 
    
 
    Section 4 - Loops
    
 
    Loops are essential for cache maintenance and updates, just like how we periodically clean up our browser cache. We know two types of loops: for and while. The for loop is used when we know the number of iterations beforehand, while the while loop is used when we don’t.
    
-
    
+
    
 
    # Cache cleanup process
 cached_items = [("fork", 5), ("spoon", 0), ("knife", 12)] # (item, access_count)
 min_access_count = 10 # Minimum access count to keep an item
@@ -572,7 +605,7 @@ 
    
+
    
 
    browser_history = [
     ("google.com", 10), 
     ("youtube.de", 5), 
@@ -582,7 +615,7 @@ 
    ]
 # YOUR CODE BELOW
    
 
    
-
    
+
    
 
    
 Code
 
    # Assertions to verify your solution
diff --git a/part-03/tutorial-07-recap.ipynb b/part-03/tutorial-07-recap.ipynb
index acbe793..f1c7369 100644
--- a/part-03/tutorial-07-recap.ipynb
+++ b/part-03/tutorial-07-recap.ipynb
@@ -36,7 +36,7 @@
         "hold various datatypes. Let’s explore this through a simple caching\n",
         "system for a coffee shop."
       ],
-      "id": "7235bd5d-4d9b-441b-8937-4b83c8760793"
+      "id": "1eb376d8-eee0-4c79-8964-866ffe8750f3"
     },
     {
       "cell_type": "code",
@@ -50,7 +50,7 @@
         "is_favorite = True # Boolean cache\n",
         "num_orders = 3 # Integer cache"
       ],
-      "id": "bddbcafa"
+      "id": "4fcd7d71"
     },
     {
       "cell_type": "markdown",
@@ -73,7 +73,7 @@
         "4.  How many times you’ve ordered it in the last month in a variable\n",
         "    `num_orders` (as an integer)"
       ],
-      "id": "ca7ab459-111b-4ce2-827c-4fc7bfab714b"
+      "id": "d4f50351-0c69-4fc4-9a15-19c1946ab9a6"
     },
     {
       "cell_type": "code",
@@ -83,7 +83,7 @@
       "source": [
         "# YOUR CODE BELOW"
       ],
-      "id": "d97073fc"
+      "id": "48bf7886"
     },
     {
       "cell_type": "code",
@@ -98,7 +98,7 @@
         "assert isinstance(num_orders, int), \"num_orders should be an integer\"\n",
         "print(f\"Last meal: {last_meal}, price: {price}, would order again: {would_order_again}, number of orders in the last month: {num_orders}\")"
       ],
-      "id": "47814bd1"
+      "id": "a481b15e"
     },
     {
       "cell_type": "markdown",
@@ -111,7 +111,7 @@
         "following code just checks a simple cache eviction policy based on the\n",
         "access count and when an item was last accessed."
       ],
-      "id": "dea30eaa-75c3-40f8-b578-6dcc17941e44"
+      "id": "f38f3cc2-920b-4557-b153-0dc99f1db256"
     },
     {
       "cell_type": "code",
@@ -137,7 +137,7 @@
         "\n",
         "print(f\"Based on {access_count} accesses and the last access {last_accessed_minutes} minutes ago, should we evict? {evict}\")"
       ],
-      "id": "db8cdb5e"
+      "id": "cea75001"
     },
     {
       "cell_type": "markdown",
@@ -159,7 +159,7 @@
         "4.  Save the result of the decision in a variable `should_evict`\n",
         "5.  Print the result of whether we should evict the song or not"
       ],
-      "id": "a917fa31-c397-48b0-8909-06c88fa40827"
+      "id": "319d2298-b58a-4a81-9e4b-12303b321af6"
     },
     {
       "cell_type": "code",
@@ -169,7 +169,7 @@
       "source": [
         "# YOUR CODE BELOW"
       ],
-      "id": "8fbb74cb"
+      "id": "3c600684"
     },
     {
       "cell_type": "code",
@@ -184,7 +184,7 @@
         "assert isinstance(should_evict, bool), \"should_evict should be a boolean\"\n",
         "print(f\"Favorite song: {favorite_song}, play count: {play_count}, last played minutes ago: {last_played_minutes_ago}, should evict: {should_evict}\")"
       ],
-      "id": "4c48fa78"
+      "id": "bdd3eedb"
     },
     {
       "cell_type": "markdown",
@@ -204,7 +204,7 @@
         "> 1.  What will be in the cache after adding “Carnival of Rust”?\n",
         "> 2.  Which song will be removed?"
       ],
-      "id": "1f9a7b49-61cb-471f-b2ef-aeba0624127c"
+      "id": "342422dd-1f08-41a8-b40d-3d6d8cb60cb0"
     },
     {
       "cell_type": "code",
@@ -228,7 +228,7 @@
         "\n",
         "print(f\"Current cache: {recent_songs}\")"
       ],
-      "id": "a7fe61dc"
+      "id": "a67ddaec"
     },
     {
       "cell_type": "markdown",
@@ -243,7 +243,7 @@
         "multiple items with different properties. For example, we can store the\n",
         "name and price of items in a shopping cart."
       ],
-      "id": "45216d62-7dbd-4730-a3d5-8ca137994ccd"
+      "id": "c5a002db-fc36-45f5-b341-cbc3d636fce1"
     },
     {
       "cell_type": "code",
@@ -264,7 +264,7 @@
         "\n",
         "print(f\"Current shopping cart: {shopping}\")"
       ],
-      "id": "8948258b"
+      "id": "ede5e956"
     },
     {
       "cell_type": "markdown",
@@ -283,7 +283,7 @@
         "> First, create a list. Inside the list, the entries should be tuples of\n",
         "> the item name and price."
       ],
-      "id": "69614634-28e6-47e6-bb45-c9766dde2421"
+      "id": "010128ab-3659-46ec-ba87-66b31695eeb3"
     },
     {
       "cell_type": "code",
@@ -293,7 +293,7 @@
       "source": [
         "# YOUR CODE BELOW"
       ],
-      "id": "a486bb1f"
+      "id": "f14a9be5"
     },
     {
       "cell_type": "code",
@@ -308,7 +308,7 @@
         "assert all(isinstance(item[0], str) and isinstance(item[1], (int, float)) for item in shopping_cart), \"All items in shopping_cart should be tuples with a string and a number\"\n",
         "print(\"Great job! Your shopping cart is ready.\")"
       ],
-      "id": "e8e6a9ec"
+      "id": "1eddd4e2"
     },
     {
       "cell_type": "markdown",
@@ -321,7 +321,7 @@
         "`for` and `while`. The `for` loop is used when we know the number of\n",
         "iterations beforehand, while the `while` loop is used when we don’t."
       ],
-      "id": "27ffc040-f2af-40b4-bd5a-d492005ee9d6"
+      "id": "5d549336-9589-4ad0-b73b-9a83f55451ea"
     },
     {
       "cell_type": "code",
@@ -354,7 +354,7 @@
         "\n",
         "print(f\"Cached items after cleanup: {cached_items}\")"
       ],
-      "id": "3419b142"
+      "id": "5948921a"
     },
     {
       "cell_type": "markdown",
@@ -376,7 +376,7 @@
         "> create a list of items to keep** and at the end replace the old list\n",
         "> with the new one."
       ],
-      "id": "391256f1-ba74-4fbd-84f4-31b0cdfb0347"
+      "id": "ee1de704-5646-4d27-8356-ce152f244810"
     },
     {
       "cell_type": "code",
@@ -393,7 +393,7 @@
         "]\n",
         "# YOUR CODE BELOW\n"
       ],
-      "id": "02b048d8"
+      "id": "445445bd"
     },
     {
       "cell_type": "code",
@@ -406,7 +406,7 @@
         "assert isinstance(browser_history, list), \"browser_history should be a list\"\n",
         "assert all(isinstance(item, tuple) for item in browser_history), \"All items in browser_history should be tuples\""
       ],
-      "id": "349b4925"
+      "id": "2bdd79fc"
     },
     {
       "cell_type": "markdown",
@@ -449,7 +449,7 @@
         "*In the next tutorial, we’ll dive deeper into more advanced strategies\n",
         "and some new topics!*"
       ],
-      "id": "1ec87fdf-ccd9-4e67-b2f4-61f2e19e28a9"
+      "id": "53133f95-82fd-4c5c-a58a-58a4235d264a"
     }
   ],
   "nbformat": 4,
diff --git a/part-03/tutorial-07-recap.pdf b/part-03/tutorial-07-recap.pdf
index 5cf1fb10620c877d5cd18b717835ba3a3847eed8..406c1a361d28f4983a12c3ca0299f7bb6e2f885e 100644
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diff --git a/part-03/tutorial-08-functions 2.html b/part-03/tutorial-08-functions 2.html
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+Tutorial III.II - Functions – Programming: Everyday Decision-Making Algorithms
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    Tutorial III.II - Functions
    
+
    Programming: Everyday Decision-Making Algorithms
    
+
    
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+
+
+
    
+
+    
+  
+    
+  
    
+  
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+
    Introduction
    
+
    Imagine you’re a librarian who needs to organize and retrieve books efficiently. Instead of explaining every step of finding a book each time, wouldn’t it be nice to have a set of standard procedures? In programming, these procedures are called functions! They help us organize our code into reusable blocks, just like having standard procedures in a library.
    
+
    This tutorial will teach you about functions using a library management system and a coffee machine as an example. We’ll create functions to help us manage books, track their popularity, and implement a simple caching system.
    
+
    
+
    
+
    
+
+
    
+
    
+Real-World Example
+
    
+
    
+
    
+
    Think of a function like a coffee machine:
    
+
      
+
    • Input (parameters) → Coffee beans, water, settings
      • 
+
    • Process → Internal brewing steps
      • 
+
    • Output (return value) → Your finished coffee
      • 
+
    
+
    
+
    
+
    
+
    
+
    Section 1 - Creating Basic Functions
    
+
    Functions in Python are like recipes:
    
+
      
+
    • They have a name
      • 
+
    • Might need ingredients (parameters)
      • 
+
    • Follow steps (code)
      • 
+
    • Usually produce something (return value)
      • 
+
    
+
    Let’s start with a simple function:
    
+
    
+
    # A simple function to greet library visitors
+def greet_visitor(name):
+    return f"Welcome to the library, {name}!"
+
+# Using our function
+message = greet_visitor("Tobias")
+print(message)
    
+
    
+
    Welcome to the library, Tobias!
    
+
    
+
    
+
    The structure is:
    
+
      
+
    1. The def keyword to start defining a function
      2. 
+
    2. A function name (like greet_visitor)
      3. 
+
    3. Parameters in parentheses (like name)
      4. 
+
    4. A colon : to start the function body
      5. 
+
    5. Indented code that makes up the function
      6. 
+
    6. Optional return statement to send back a value from the function
      7. 
+
    
+
    
+
    
+
    
+
+
    
+
    
+Return Value
+
    
+
    
+
    
+
    The return statement is optional. If you don’t use it, the function will return None by default.
    
+
    
+
    
+
    The following illustrates this in a more generic form:
    
+
    
+
    def function_name(parameter1, parameter2):  # ← Function signature
+    result = parameter1 + parameter2        # ← Processing
+    return result                           # ← Return value
    
+
    
+
    
+
    
+
    
+
+
    
+
    
+Common Function Errors
+
    
+
    
+
    
+
      
+
    • IndentationError: Check your function’s indentation
      • 
+
    • NameError: Make sure the function is defined before calling it
      • 
+
    • TypeError: Verify you’re passing the correct number of arguments
      • 
+
    
+
    
+
    
+
    
+
    Exercise 1.1 - Create a Book Information Function
    
+
    Create a function called get_book_info that takes three parameters: title, author, and year. It should return a formatted string with the book’s information.
    
+
    
+
    
+
    
+
+
    
+
    
+Before You Start
+
    
+
    
+
    
+
    Common mistakes to avoid:
    
+
      
+
    • Don’t forget the spaces in the formatting
      • 
+
    • Remember to use f-strings for easy string formatting
      • 
+
    • Make sure to include the parentheses around the year
      • 
+
    
+
    
+
    
+
    
+
    # If you call the function like this:
+# get_book_info("Return", "Alan Wake", 2023)
+# it should return the string:
+# "Return by Alan Wake (2023)"
+# YOUR CODE BELOW
    
+
    
+
    
+
    
+Code
+
    # Assertions to verify your solution
+assert get_book_info("1984", "George Orwell", 1949) == "1984 by George Orwell (1949)"
+print("Great job! Your book information function works as expected!")
    
+
    
+
    
+
    
+
    
+
    
+
    Section 2 - Functions with Decision Making
    
+
    Functions can contain any code we’ve learned before, including if statements. This is useful for making decisions within our functions:
    
+
    
+
    def is_book_available(copies_available, on_hold):
+    if copies_available > 0 and not on_hold:
+        return True
+    else:
+        return False
+
+# Test the function
+print("The book is available:", is_book_available(3, False))
+print("The book is available:", is_book_available(0, False))
    
+
    
+
    The book is available: True
+The book is available: False
    
+
    
+
    
+
    Here we use an if statement to check if the book is available. If the book is available, we return True, otherwise we return False.
    
+
    
+
    Common Pitfall
    
+
    When using multiple conditions, be careful with the order of operations. Consider using parentheses to make your logic clear:
    
+
    if (copies_available > 0) and (not on_hold):  # More readable than the code above
    
+
    
+
    
+
    Exercise 2.1 - Create a Function to Check if a Book is Popular
    
+
    Create a function called is_popular that takes a single parameter rating. If the rating is greater than 3, it should return True, otherwise it should return False.
    
+
    
+
    # YOUR CODE BELOW
    
+
    
+
    
+
    
+Code
+
    # Assertions to verify your solution
+assert is_popular(4) == True, "A rating of 4 or higher is considered popular"
+assert is_popular(2) == False, "A rating of 3 or lower is not popular"
+print("Excellent! Your popular book function works correctly!")
    
+
    
+
    
+
    
+
    
+
    Exercise 2.2 - Create a Book Access Function
    
+
    Many libraries have borrowing policies that depend on multiple factors. Let’s implement a realistic borrowing policy function that a library might use. Create a function called can_borrow_book that takes three parameters:
    
+
      
+
    • is_member: boolean indicating if the person is a library member
      • 
+
    • books_borrowed: number of books currently borrowed
      • 
+
    • has_overdue: boolean indicating if they have overdue books
      • 
+
    
+
    The function should return True only if:
    
+
      
+
    • They are a member AND
      • 
+
    • They have borrowed less than 3 books AND
      • 
+
    • They have no overdue books
      • 
+
    
+
    
+
    # YOUR CODE BELOW
    
+
    
+
    
+
    
+Code
+
    # Assertions to verify your solution
+assert can_borrow_book(True, 2, False) == True "Should allow borrowing"
+assert can_borrow_book(True, 3, False) == False, "Should not allow more than 3 books"
+assert can_borrow_book(True, 1, True) == False, "Should not allow with overdue books"
+print("Excellent! Your borrowing function works as it should!")
    
+
    
+
    
+
    
+
    
+
    
+
    Section 3 - Functions with Default Parameters
    
+
    Sometimes we want functions to have default values for parameters. This makes them more flexible, as we don’t have to specify all parameters every time we call the function.
    
+
    
+
    def calculate_fine(days_overdue, rate_per_day=0.50):
+    return days_overdue * rate_per_day
+
+# Using default rate
+print(f"The fine for 5 days overdue with the default rate is {calculate_fine(5)}")
+
+# Using custom rate
+print(f"The fine for 5 days overdue with a custom rate is {calculate_fine(5, 1.00)}")
    
+
    
+
    The fine for 5 days overdue with the default rate is 2.5
+The fine for 5 days overdue with a custom rate is 5.0
    
+
    
+
    
+
    
+
    Exercise 3.1 - Create a Cache Priority Function
    
+
    Create a function called calculate_cache_priority that helps decide if a book should be kept in the easily accessible section. It should take:
    
+
      
+
    • times_borrowed: How many times the book was borrowed
      • 
+
    • days_since_last_borrow: Days since last borrowed
      • 
+
    • is_reference: Whether it’s a reference book (default: False)
      • 
+
    
+
    Return a priority score calculated as:
    
+
      
+
    • For regular books: times_borrowed / (days_since_last_borrow + 1)
      • 
+
    • For reference books: 2 * (times_borrowed / (days_since_last_borrow + 1))
      • 
+
    
+
    
+
    # YOUR CODE BELOW
    
+
    
+
    
+
    
+Code
+
    # Test your answer
+assert calculate_cache_priority(10, 5) == 10/(5+1), "Check your regular book calculation"
+assert calculate_cache_priority(10, 5, True) == 2*(10/(5+1)), "Check your reference book calculation"
+print("Great! Your cache priority function works and calculates correctly!")
    
+
    
+
    
+
    
+
    
+
    
+
    Section 4 - Introduction to Methods
    
+
    Methods are special types of functions that belong to objects. While regular functions stand alone, methods are always associated with a specific object or data type. Let’s explore this with some examples:
    
+
    
+
    # String methods
+book_title = "the great gatsby"
+print(book_title.title())  # Outputs: "The Great Gatsby"
+print(book_title.upper())  # Outputs: "THE GREAT GATSBY"
    
+
    
+
    The Great Gatsby
+THE GREAT GATSBY
    
+
    
+
    
+
    
+
    # List methods
+books = ["Neuromancer", "1984", "Foundation"]
+books.append("Dune")  # Adds a book to the list
+print("Books before sorting:", books)
+books.sort()          # Sorts the list alphabetically
+print("Books after sorting:", books)
    
+
    
+
    Books before sorting: ['Neuromancer', '1984', 'Foundation', 'Dune']
+Books after sorting: ['1984', 'Dune', 'Foundation', 'Neuromancer']
    
+
    
+
    
+
    
+
    
+
    
+
+
    
+
    
+Functions vs Methods
+
    
+
    
+
    
+
    The main difference:
    
+
      
+
    • Functions are called directly: function_name(arguments)
      • 
+
    • Methods are called on objects: object.method_name(arguments)
      • 
+
    
+
    
+
    
+
    
+
    Exercise 4.1 - Working with String Methods and Functions
    
+
    Create a function called format_book_title that takes a book title as input and:
    
+
      
+
    1. Capitalizes the first letter of each word
      2. 
+
    2. Removes any extra whitespace
      3. 
+
    3. Returns the formatted title
      4. 
+
    
+
    
+
    
+
    
+
+
    
+
    
+Common String Methods
+
    
+
    
+
    
+
      
+
    • .strip() - Removes whitespace from start and end
      • 
+
    • .title() - Capitalizes first letter of each word
      • 
+
    • .lower() - Converts to lowercase
      • 
+
    • .upper() - Converts to uppercase
      • 
+
    
+
    
+
    
+
    
+
    # YOUR CODE BELOW
    
+
    
+
    
+
    
+Code
+
    # Test your answer
+assert format_book_title("  the hitchhikers guide  ") == "The Hitchhikers Guide", "Check your whitespace removal"
+assert format_book_title("dune") == "Dune", "Check your capitalization"
+print("Excellent! Your title formatting function works correctly!")
    
+
    
+
    
+
    
+
    
+
    
+
    Conclusion
    
+
    Excellent work! You’ve learned how to create and use functions in Python through the lens of library management. You now know how to:
    
+
      
+
    • Create basic functions with parameters
      • 
+
    • Use functions with decision-making logic
      • 
+
    • Work with default parameters
      • 
+
    • Return values from functions
      • 
+
    
+
    Remember:
    
+
      
+
    • Functions help us organize and reuse code
      • 
+
    • They make our code more readable and maintainable
      • 
+
    • They can take inputs (parameters) and produce outputs (return values)
      • 
+
    • They can have default values for parameters
      • 
+
    
+
    In a real library system, functions like these would be part of a larger caching system that helps optimize book retrieval times and improve user experience!
    
+
    
+
    
+
    Solutions
    
+
    You will likely find solutions to most exercises online. However, we strongly encourage you to work on these exercises independently without searching explicitly for the exact answers to the exercises. Understanding someone else’s solution is very different from developing your own. Use the lecture notes and try to solve the exercises on your own. This approach will significantly enhance your learning and problem-solving skills.
    
+
    Remember, the goal is not just to complete the exercises, but to understand the concepts and improve your programming abilities. If you encounter difficulties, review the lecture materials, experiment with different approaches, and don’t hesitate to ask for clarification during class discussions.
    
+
    Later, you will find the solutions to these exercises online in the associated GitHub repository, but we will also quickly go over them next week. To access the solutions, click on the Github button on the lower right and search for the folder with today’s lecture and tutorial. Alternatively, you can ask ChatGPT or Claude to explain them to you. But please remember, the goal is not just to complete the exercises, but to understand the concepts and improve your programming abilities.
    
+
    
+
    In the next tutorial, we’ll take a look on how to import packages and libraries to extend our functionality!
    
+
+
+
    
+
+
     
+
+
     
+
+
+
+
+
+
\ No newline at end of file
diff --git a/part-03/tutorial-08-functions.html b/part-03/tutorial-08-functions.html
index 8536def..c02672e 100644
--- a/part-03/tutorial-08-functions.html
+++ b/part-03/tutorial-08-functions.html
@@ -113,9 +113,7 @@
       
-        
+        
         
       
    
+
+      
+  
+        
  • 
+      
     
+            
+ 03 Caching
+          
+            
+           
+      
    
+      
   
    • 
@@ -283,7 +316,7 @@ 
    On this page
    
 
 
    
 
-
    
+
    
 
    
 
    Tutorial III.II - Functions
    
 
    Programming: Everyday Decision-Making Algorithms
    
@@ -336,7 +369,7 @@ 
    Section 1 - Creating Basic Functions
    
 
  • Usually produce something (return value)
    • 
 
 
    Let’s start with a simple function:
    
-
    
+
    
 
    # A simple function to greet library visitors
 def greet_visitor(name):
     return f"Welcome to the library, {name}!"
@@ -371,7 +404,7 @@ 
    Section 1 - Creating Basic Functions
    
 
    
 
    
 
    The following illustrates this in a more generic form:
    
-
    
+
    
 
    def function_name(parameter1, parameter2):  # ← Function signature
     result = parameter1 + parameter2        # ← Processing
     return result                           # ← Return value
    
@@ -414,14 +447,14 @@ 
    
+
    
 
    # If you call the function like this:
 # get_book_info("Return", "Alan Wake", 2023)
 # it should return the string:
 # "Return by Alan Wake (2023)"
 # YOUR CODE BELOW
    
 
    
-
    
+
    
 
    
 Code
 
    # Assertions to verify your solution
@@ -434,7 +467,7 @@ 
    
 
    Section 2 - Functions with Decision Making
    
 
    Functions can contain any code we’ve learned before, including if statements. This is useful for making decisions within our functions:
    
-
    
+
    
 
    def is_book_available(copies_available, on_hold):
     if copies_available > 0 and not on_hold:
         return True
@@ -458,10 +491,10 @@ 
    Common Pitfall
    
 
    
 
    Exercise 2.1 - Create a Function to Check if a Book is Popular
    
 
    Create a function called is_popular that takes a single parameter rating. If the rating is greater than 3, it should return True, otherwise it should return False.
    
-
    
+
    
 
    # YOUR CODE BELOW
    
 
    
-
    
+
    
 
    
 Code
 
    # Assertions to verify your solution
@@ -485,10 +518,10 @@ 
    
+
    
 
    # YOUR CODE BELOW
    
 
    
-
    
+
    
 
    
 Code
 
    # Assertions to verify your solution
@@ -503,7 +536,7 @@ 
    
 
    Section 3 - Functions with Default Parameters
    
 
    Sometimes we want functions to have default values for parameters. This makes them more flexible, as we don’t have to specify all parameters every time we call the function.
    
-
    
+
    
 
    def calculate_fine(days_overdue, rate_per_day=0.50):
     return days_overdue * rate_per_day
 
@@ -530,10 +563,10 @@ 
    
+
    
 
    # YOUR CODE BELOW
    
 
    
-
    
+
    
 
    
 Code
 
    # Test your answer
@@ -547,7 +580,7 @@ 
    
 
    Section 4 - Introduction to Methods
    
 
    Methods are special types of functions that belong to objects. While regular functions stand alone, methods are always associated with a specific object or data type. Let’s explore this with some examples:
    
-
    
+
    
 
    # String methods
 book_title = "the great gatsby"
 print(book_title.title())  # Outputs: "The Great Gatsby"
@@ -557,7 +590,7 @@ 
    Section 4 - Introduction to Methods
    
 THE GREAT GATSBY
    
 
    
 
    
-
    
+
    
 
    # List methods
 books = ["Neuromancer", "1984", "Foundation"]
 books.append("Dune")  # Adds a book to the list
@@ -612,10 +645,10 @@ 
    
+
    
 
    # YOUR CODE BELOW
    
 
    
-
    
+
    
 
    
 Code
 
    # Test your answer
diff --git a/part-03/tutorial-08-functions.ipynb b/part-03/tutorial-08-functions.ipynb
index 456785a..bb187ff 100644
--- a/part-03/tutorial-08-functions.ipynb
+++ b/part-03/tutorial-08-functions.ipynb
@@ -41,7 +41,7 @@
         "\n",
         "Let’s start with a simple function:"
       ],
-      "id": "cfe2e22a-a517-4498-8984-90875189e2a2"
+      "id": "91dc0828-502b-4042-abd6-8a44c57b0379"
     },
     {
       "cell_type": "code",
@@ -65,7 +65,7 @@
         "message = greet_visitor(\"Tobias\")\n",
         "print(message)"
       ],
-      "id": "abda54e6"
+      "id": "7da1cf96"
     },
     {
       "cell_type": "markdown",
@@ -87,7 +87,7 @@
         "\n",
         "The following illustrates this in a more generic form:"
       ],
-      "id": "a860da77-ee34-458b-8172-59b8371190f0"
+      "id": "2e976a9c-7150-443a-832e-a560c6be988d"
     },
     {
       "cell_type": "code",
@@ -99,7 +99,7 @@
         "    result = parameter1 + parameter2        # ← Processing\n",
         "    return result                           # ← Return value"
       ],
-      "id": "fa64d191"
+      "id": "4b1ce0a4"
     },
     {
       "cell_type": "markdown",
@@ -125,7 +125,7 @@
         "> -   Remember to use f-strings for easy string formatting\n",
         "> -   Make sure to include the parentheses around the year"
       ],
-      "id": "c246d5af-9401-4aec-8926-67d137740963"
+      "id": "a283e900-67dc-44ac-a919-a0c6d0a73b22"
     },
     {
       "cell_type": "code",
@@ -139,7 +139,7 @@
         "# \"Return by Alan Wake (2023)\"\n",
         "# YOUR CODE BELOW"
       ],
-      "id": "e4f854c5"
+      "id": "5c1b4229"
     },
     {
       "cell_type": "code",
@@ -151,7 +151,7 @@
         "assert get_book_info(\"1984\", \"George Orwell\", 1949) == \"1984 by George Orwell (1949)\"\n",
         "print(\"Great job! Your book information function works as expected!\")"
       ],
-      "id": "2e526c98"
+      "id": "d522fbba"
     },
     {
       "cell_type": "markdown",
@@ -162,7 +162,7 @@
         "Functions can contain any code we’ve learned before, including if\n",
         "statements. This is useful for making decisions within our functions:"
       ],
-      "id": "ba46e971-91fb-4715-bb00-c3a7bb27c89f"
+      "id": "247c679e-d918-4dfd-a73d-b3335b3d9d36"
     },
     {
       "cell_type": "code",
@@ -189,7 +189,7 @@
         "print(\"The book is available:\", is_book_available(3, False))\n",
         "print(\"The book is available:\", is_book_available(0, False))"
       ],
-      "id": "8be69093"
+      "id": "ad235a8e"
     },
     {
       "cell_type": "markdown",
@@ -213,7 +213,7 @@
         "`rating`. If the rating is greater than 3, it should return `True`,\n",
         "otherwise it should return `False`."
       ],
-      "id": "7d1b8fd8-9d0c-4f23-a1ad-0f8c9d4f8232"
+      "id": "1c19faa2-c6e3-4cca-b86e-eaa92ace0cd9"
     },
     {
       "cell_type": "code",
@@ -223,7 +223,7 @@
       "source": [
         "# YOUR CODE BELOW"
       ],
-      "id": "92240082"
+      "id": "77a53ee7"
     },
     {
       "cell_type": "code",
@@ -236,7 +236,7 @@
         "assert is_popular(2) == False, \"A rating of 3 or lower is not popular\"\n",
         "print(\"Excellent! Your popular book function works correctly!\")"
       ],
-      "id": "436bd743"
+      "id": "8611f535"
     },
     {
       "cell_type": "markdown",
@@ -259,7 +259,7 @@
         "-   They have borrowed less than 3 books AND\n",
         "-   They have no overdue books"
       ],
-      "id": "99642e97-880f-45ee-a390-b1b4a7654929"
+      "id": "03b371ff-0b03-4c54-a36d-8d516ed7143f"
     },
     {
       "cell_type": "code",
@@ -269,7 +269,7 @@
       "source": [
         "# YOUR CODE BELOW"
       ],
-      "id": "a81c039f"
+      "id": "8df74ab9"
     },
     {
       "cell_type": "code",
@@ -283,7 +283,7 @@
         "assert can_borrow_book(True, 1, True) == False, \"Should not allow with overdue books\"\n",
         "print(\"Excellent! Your borrowing function works as it should!\")"
       ],
-      "id": "e4d1b1f6"
+      "id": "cbe1e8fa"
     },
     {
       "cell_type": "markdown",
@@ -295,7 +295,7 @@
         "makes them more flexible, as we don’t have to specify all parameters\n",
         "every time we call the function."
       ],
-      "id": "fe369376-cef3-483b-a914-13f6c15c8bc8"
+      "id": "8a04bf61-cbce-4b5b-b9ec-9d1e5edfe527"
     },
     {
       "cell_type": "code",
@@ -321,7 +321,7 @@
         "# Using custom rate\n",
         "print(f\"The fine for 5 days overdue with a custom rate is {calculate_fine(5, 1.00)}\")"
       ],
-      "id": "66c3c585"
+      "id": "00e50be3"
     },
     {
       "cell_type": "markdown",
@@ -342,7 +342,7 @@
         "-   For reference books:\n",
         "    `2 * (times_borrowed / (days_since_last_borrow + 1))`"
       ],
-      "id": "9d090f86-4cd2-4b7a-9741-a5f9c2184ae6"
+      "id": "550fe425-22a2-49c6-8a11-8790b33cf99d"
     },
     {
       "cell_type": "code",
@@ -352,7 +352,7 @@
       "source": [
         "# YOUR CODE BELOW"
       ],
-      "id": "26089a5b"
+      "id": "34810d8e"
     },
     {
       "cell_type": "code",
@@ -365,7 +365,7 @@
         "assert calculate_cache_priority(10, 5, True) == 2*(10/(5+1)), \"Check your reference book calculation\"\n",
         "print(\"Great! Your cache priority function works and calculates correctly!\")"
       ],
-      "id": "f56addaf"
+      "id": "af090058"
     },
     {
       "cell_type": "markdown",
@@ -377,7 +377,7 @@
         "regular functions **stand alone**, methods are **always associated with\n",
         "a specific object or data type**. Let’s explore this with some examples:"
       ],
-      "id": "49c3a5db-2067-462c-9b35-6bda9c42fd99"
+      "id": "4f98d3e0-e4d2-4fbb-901a-f468d2d5c9ec"
     },
     {
       "cell_type": "code",
@@ -399,7 +399,7 @@
         "print(book_title.title())  # Outputs: \"The Great Gatsby\"\n",
         "print(book_title.upper())  # Outputs: \"THE GREAT GATSBY\""
       ],
-      "id": "a3f3d9db"
+      "id": "841058cd"
     },
     {
       "cell_type": "code",
@@ -423,7 +423,7 @@
         "books.sort()          # Sorts the list alphabetically\n",
         "print(\"Books after sorting:\", books)"
       ],
-      "id": "fca70d80"
+      "id": "a01e3033"
     },
     {
       "cell_type": "markdown",
@@ -452,7 +452,7 @@
         "> -   `.lower()` - Converts to lowercase\n",
         "> -   `.upper()` - Converts to uppercase"
       ],
-      "id": "62de1c20-7eb8-4563-b939-73aea89e7043"
+      "id": "a38a2e01-6781-4d7e-a652-2622bba430b7"
     },
     {
       "cell_type": "code",
@@ -462,7 +462,7 @@
       "source": [
         "# YOUR CODE BELOW"
       ],
-      "id": "c987c064"
+      "id": "ad35a649"
     },
     {
       "cell_type": "code",
@@ -475,7 +475,7 @@
         "assert format_book_title(\"dune\") == \"Dune\", \"Check your capitalization\"\n",
         "print(\"Excellent! Your title formatting function works correctly!\")"
       ],
-      "id": "b35a3b3a"
+      "id": "383d57e0"
     },
     {
       "cell_type": "markdown",
@@ -532,7 +532,7 @@
         "*In the next tutorial, we’ll take a look on how to import packages and\n",
         "libraries to extend our functionality!*"
       ],
-      "id": "f80716c8-a1fd-4da6-8afb-daae4df94948"
+      "id": "b4d59097-1b6d-4e05-81b0-a6c0f8bd69b3"
     }
   ],
   "nbformat": 4,
diff --git a/part-03/tutorial-08-functions.pdf b/part-03/tutorial-08-functions.pdf
index d29c5c1fa1b8a2a26e84984798ded160b19a3bbc..ff72dd87262ebf111facf6bfc9fa735efed6bed1 100644
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diff --git a/part-03/tutorial-09-packages.html b/part-03/tutorial-09-packages.html
index 9f0bc84..81857fe 100644
--- a/part-03/tutorial-09-packages.html
+++ b/part-03/tutorial-09-packages.html
@@ -113,9 +113,7 @@
       
-        
+        
         
       
    
+
+      
+  
+        
  • 
+      
     
+            
+ 03 Caching
+          
+            
+           
+      
    
+      
   
    • 
@@ -282,7 +315,7 @@ 
    On this page
    
 
 
    
 
-
    
+
    
 
    
 
    Tutorial III.III - Package Management
    
 
    Programming: Everyday Decision-Making Algorithms
    
@@ -363,12 +396,12 @@ 
    In more detail
    
 
    
 
    Section 1 - Using Standard Libraries
    
 
    Before we start using packages, let’s take a look at Python’s standard libraries. Python comes with a set of standard libraries that are always available. You can use these libraries by simply importing them. For example, the math library provides mathematical functions like sqrt and sin and the random library provides functions to generate random numbers. You can import these libraries using the following syntax:
    
-
    
+
    
 
    import math
 import random
    
 
    
 
    You can then use the functions provided by these libraries by calling them with the library name as a prefix. For example, the following code calculates the square root of 16.
    
-
    
+
    
 
    a_square_root = math.sqrt(16)
 print(f"The square root of 16 is {a_square_root}!")
    
 
    
@@ -376,46 +409,46 @@ 
    Section 1 - Using Standard Libraries
    
 
    
 
    
 
    The following code generates a random number between 0 and 1.
    
-
    
+
    
 
    a_random_number = random.random()
 print(f"A random number is {a_random_number}!")
    
 
    
-
    A random number is 0.463644880286867!
    
+
    A random number is 0.12309236184936656!
    
 
    
 
    
 
    We can also use the library to choose a random element from a list. For example, the following code chooses a random element from the list ['book1', 'book2', 'book3']. Try it out by executing the cell multiple times.
    
-
    
+
    
 
    random_choice = random.choice(['book1', 'book2', 'book3'])
 print(f"We chose {random_choice}!")
    
 
    
-
    We chose book1!
    
+
    We chose book3!
    
 
    
 
    
 
    Sometimes, we only need one function from a library. In this case, we can use the from keyword to import only the specific function we need. For example, the following code imports only the randint function from the random library and uses it to generate a random integer between 1 and 10.
    
-
    
+
    
 
    from random import randint
 a_random_integer = randint(1, 10)
 print(f"A random integer between 1 and 10 is {a_random_integer}!")
    
 
    
-
    A random integer between 1 and 10 is 10!
    
+
    A random integer between 1 and 10 is 1!
    
 
    
 
    
 
    Other times, we might need to work with a library that has a rather long name. In this case, we can use the as keyword to give the library a shorter name. For example, the following code imports the random library and gives it the shorter name rd.
    
-
    
+
    
 
    import random as rd
 a_random_integer = rd.randint(1, 100)
 print(f"Now, a random integer between 1 and 100 is {a_random_integer}!")
    
 
    
-
    Now, a random integer between 1 and 100 is 79!
    
+
    Now, a random integer between 1 and 100 is 51!
    
 
    
 
    
 
    
 
    Exercise 1.1 - Use the math library
    
 
    Use the math library to calculate the square root of 256. Call the result square_root.
    
-
    
+
    
 
    # YOUR CODE BELOW
    
 
    
-
    
+
    
 
    
 Code
 
    assert square_root == 16
@@ -426,7 +459,7 @@ 
    Exerci
 
    
 
    Exercise 1.2 - Use the random library
    
 
    Use the random library to generate a random number between 1 and 25. Call the result random_number.
    
-
    
+
    
 
    
 Code
 
    assert random_number >= 1 and random_number <= 25
@@ -478,7 +511,7 @@ 
    Exercise 3.1
 
    Let’s practice by installing pandas, a popular package for data analysis. Execute the following command in your terminal and make sure you are not in the python shell.
    
 
    conda install pandas
    
 
    You can test if the installation was successful by running the following code.
    
-
    
+
    
 
    
 Code
 
    # Test your answer
diff --git a/part-03/tutorial-09-packages.ipynb b/part-03/tutorial-09-packages.ipynb
index 930a1f9..4361e34 100644
--- a/part-03/tutorial-09-packages.ipynb
+++ b/part-03/tutorial-09-packages.ipynb
@@ -76,7 +76,7 @@
         "generate random numbers. You can import these libraries using the\n",
         "following syntax:"
       ],
-      "id": "2db5a99c-b151-4385-8fe5-688750cf2182"
+      "id": "ac26e5a1-9c23-4e32-a020-a3a5d94690fc"
     },
     {
       "cell_type": "code",
@@ -87,7 +87,7 @@
         "import math\n",
         "import random"
       ],
-      "id": "b1f91f4e"
+      "id": "2de08d32"
     },
     {
       "cell_type": "markdown",
@@ -97,7 +97,7 @@
         "them with the library name as a prefix. For example, the following code\n",
         "calculates the square root of 16."
       ],
-      "id": "48212139-25a3-4738-a4b0-29f2b8ee9bca"
+      "id": "7578474d-cae6-49e7-bb45-5f0b9cc0e283"
     },
     {
       "cell_type": "code",
@@ -116,7 +116,7 @@
         "a_square_root = math.sqrt(16)\n",
         "print(f\"The square root of 16 is {a_square_root}!\")"
       ],
-      "id": "c56adbb0"
+      "id": "7d861483"
     },
     {
       "cell_type": "markdown",
@@ -124,7 +124,7 @@
       "source": [
         "The following code generates a random number between 0 and 1."
       ],
-      "id": "26dbbcf7-56b0-4ae2-acf9-0d5a2c46b987"
+      "id": "84c27451-5698-4e08-b220-8278cc1e3013"
     },
     {
       "cell_type": "code",
@@ -135,7 +135,7 @@
           "output_type": "stream",
           "name": "stdout",
           "text": [
-            "A random number is 0.6462513182080769!"
+            "A random number is 0.2212890385369538!"
           ]
         }
       ],
@@ -143,7 +143,7 @@
         "a_random_number = random.random()\n",
         "print(f\"A random number is {a_random_number}!\")"
       ],
-      "id": "a1518d42"
+      "id": "7865d339"
     },
     {
       "cell_type": "markdown",
@@ -154,7 +154,7 @@
         "`['book1', 'book2', 'book3']`. Try it out by executing the cell multiple\n",
         "times."
       ],
-      "id": "03e23fd8-40fd-4847-b385-0c00aa79bb73"
+      "id": "50dc4808-5018-47a2-9cdf-fb8b1fb70593"
     },
     {
       "cell_type": "code",
@@ -165,7 +165,7 @@
           "output_type": "stream",
           "name": "stdout",
           "text": [
-            "We chose book3!"
+            "We chose book1!"
           ]
         }
       ],
@@ -173,7 +173,7 @@
         "random_choice = random.choice(['book1', 'book2', 'book3'])\n",
         "print(f\"We chose {random_choice}!\")"
       ],
-      "id": "bb2d88fc"
+      "id": "d29acc5f"
     },
     {
       "cell_type": "markdown",
@@ -185,7 +185,7 @@
         "the `random` library and uses it to generate a random integer between 1\n",
         "and 10."
       ],
-      "id": "5b3b56ac-267e-4163-8838-30cfdebe854e"
+      "id": "aafc2c30-0fa3-41f7-a6c3-0f6e38ac48f2"
     },
     {
       "cell_type": "code",
@@ -196,7 +196,7 @@
           "output_type": "stream",
           "name": "stdout",
           "text": [
-            "A random integer between 1 and 10 is 2!"
+            "A random integer between 1 and 10 is 10!"
           ]
         }
       ],
@@ -205,7 +205,7 @@
         "a_random_integer = randint(1, 10)\n",
         "print(f\"A random integer between 1 and 10 is {a_random_integer}!\")"
       ],
-      "id": "a3d63b7f"
+      "id": "8dcad78d"
     },
     {
       "cell_type": "markdown",
@@ -216,7 +216,7 @@
         "shorter name. For example, the following code imports the `random`\n",
         "library and gives it the shorter name `rd`."
       ],
-      "id": "a0060fed-0ea6-4158-8a77-447afcfd8c73"
+      "id": "71ec50e7-a03d-4e93-b96f-2aa96a030ad0"
     },
     {
       "cell_type": "code",
@@ -227,7 +227,7 @@
           "output_type": "stream",
           "name": "stdout",
           "text": [
-            "Now, a random integer between 1 and 100 is 78!"
+            "Now, a random integer between 1 and 100 is 21!"
           ]
         }
       ],
@@ -236,7 +236,7 @@
         "a_random_integer = rd.randint(1, 100)\n",
         "print(f\"Now, a random integer between 1 and 100 is {a_random_integer}!\")"
       ],
-      "id": "19ec3879"
+      "id": "6361b46d"
     },
     {
       "cell_type": "markdown",
@@ -247,7 +247,7 @@
         "Use the `math` library to calculate the square root of 256. Call the\n",
         "result `square_root`."
       ],
-      "id": "d0de0055-b72e-4d5c-9da4-c22cdce15b9b"
+      "id": "b3aebced-0571-4115-9c33-8b900daca4d7"
     },
     {
       "cell_type": "code",
@@ -257,7 +257,7 @@
       "source": [
         "# YOUR CODE BELOW"
       ],
-      "id": "8dc5df65"
+      "id": "7d733299"
     },
     {
       "cell_type": "code",
@@ -268,7 +268,7 @@
         "assert square_root == 16\n",
         "print(f\"Great job! The square root of 256 is {square_root}!\")"
       ],
-      "id": "39edfe71"
+      "id": "6fb3bd3b"
     },
     {
       "cell_type": "markdown",
@@ -279,7 +279,7 @@
         "Use the `random` library to generate a random number between 1 and 25.\n",
         "Call the result `random_number`."
       ],
-      "id": "0f9454f7-a998-4692-ab48-851aa2ec94b4"
+      "id": "8fbf3a9f-0ccf-43e6-9968-976fa5d1578a"
     },
     {
       "cell_type": "code",
@@ -290,7 +290,7 @@
         "assert random_number >= 1 and random_number <= 25\n",
         "print(f\"Good! You generated a random integer {random_number} between 1 and 25!\")"
       ],
-      "id": "bdef7d6f"
+      "id": "dfb3b33a"
     },
     {
       "cell_type": "markdown",
@@ -354,7 +354,7 @@
         "You can test if the installation was successful by running the following\n",
         "code."
       ],
-      "id": "4a118614-c896-43ae-aee2-c2b8ef87a19f"
+      "id": "93a331f0-d0f1-4691-b2bb-0191c57e06c1"
     },
     {
       "cell_type": "code",
@@ -369,7 +369,7 @@
         "except ImportError:\n",
         "    print(\"pandas was not installed correctly\")"
       ],
-      "id": "5e8deeba"
+      "id": "7bfffa7d"
     },
     {
       "cell_type": "markdown",
@@ -451,7 +451,7 @@
         "*That’s it for this week! Next week, we’ll take a look at how to read\n",
         "and write files in Python and work with tabular data!*"
       ],
-      "id": "982e860b-f2f5-481c-9981-4a574809e8da"
+      "id": "9587d4ea-b30b-4fe8-9411-aa9a1cecfdfb"
     }
   ],
   "nbformat": 4,
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diff --git a/search.json b/search.json
index 60808cb..839257e 100644
--- a/search.json
+++ b/search.json
@@ -4,84 +4,128 @@
     "href": "part-03/tutorial-09-packages.html",
     "title": "Tutorial III.III - Package Management",
     "section": "",
-    "text": "Welcome to this guided tutorial on understanding packages and package management in Python! We’ll explore this concept through the lens of library management - how libraries organize, maintain, and share their resources.\nThink of Python as your local library’s main building. Just like a library has:\n\nA main collection (Python’s standard library)\nDifferent sections (third-party packages)\nA catalog system (pip package manager)\nMultiple branches (virtual environments)\n\n\n\nLet’s break this down:\n\nStandard Library: Like the core collection every library branch has:\n\nPython comes with essential tools built-in\nData structures (lists, dictionaries, etc.)\nMathematical functions (sin, cos, sqrt, etc.)\nRandom numbers (random, choice, etc.)\n\nThird-Party Packages: Similar to specialized sections in a library:\n\nData analysis packages (pandas, numpy) → Research section\nVisualization packages (matplotlib, seaborn) → Art books\nWeb frameworks (Django, Flask) → Technical manuals\nMachine learning packages (scikit-learn) → Advanced studies section\n\nPackage Manager (pip): Works like the library’s catalog:\n\nInstalling packages → Ordering new books\nUpdating packages → Replacing with newer editions\nUninstalling packages → Removing outdated books\nDependencies → “You must read Book A before Book B”\n\nVirtual Environments: Works like different library branches:\n\nEach branch can have its own collection of books (packages)\nDifferent editions of the same book (package versions)\nSpecialized sections for different purposes (project-specific dependencies)\n\n\nThe best part? Most Python packages are free to use, thanks to the open-source community!\n\n\n\n\n\n\nNote\n\n\n\nWhile we’ll practice some commands here, you’ll typically manage packages in your terminal or IDE."
+    "text": "Welcome to this guided tutorial on understanding packages and package management in Python! We’ll explore this concept through the lens of library management - how libraries organize, maintain, and share their resources.\nThink of Python as your local library’s main building. Just like a library has:\n\nA main collection (Python’s standard library)\nDifferent sections (third-party packages)\nA catalog system (pip package manager)\nMultiple branches (virtual environments)\n\n\n\nLet’s break this down:\n\nStandard Library: Like the core collection every library branch has:\n\nPython comes with essential tools built-in\nData structures (lists, dictionaries, etc.)\nMathematical functions (sin, cos, sqrt, etc.)\nRandom numbers (random, choice, etc.)\n\nThird-Party Packages: Similar to specialized sections in a library:\n\nData analysis packages (pandas, numpy) → Research section\nVisualization packages (matplotlib, seaborn) → Art books\nWeb frameworks (Django, Flask) → Technical manuals\nMachine learning packages (scikit-learn) → Advanced studies section\n\nPackage Manager (pip): Works like the library’s catalog:\n\nInstalling packages → Ordering new books\nUpdating packages → Replacing with newer editions\nUninstalling packages → Removing outdated books\nDependencies → “You must read Book A before Book B”\n\nVirtual Environments: Works like different library branches:\n\nEach branch can have its own collection of books (packages)\nDifferent editions of the same book (package versions)\nSpecialized sections for different purposes (project-specific dependencies)\n\n\nThe best part? Most Python packages are free to use, thanks to the open-source community!\n\n\n\n\n\n\nNote\n\n\n\nWhile we’ll practice some commands here, you’ll typically manage packages in your terminal or IDE.",
+    "crumbs": [
+      "03 Caching",
+      "09 - Packages"
+    ]
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     "href": "part-03/tutorial-09-packages.html#in-more-detail",
     "title": "Tutorial III.III - Package Management",
     "section": "",
-    "text": "Let’s break this down:\n\nStandard Library: Like the core collection every library branch has:\n\nPython comes with essential tools built-in\nData structures (lists, dictionaries, etc.)\nMathematical functions (sin, cos, sqrt, etc.)\nRandom numbers (random, choice, etc.)\n\nThird-Party Packages: Similar to specialized sections in a library:\n\nData analysis packages (pandas, numpy) → Research section\nVisualization packages (matplotlib, seaborn) → Art books\nWeb frameworks (Django, Flask) → Technical manuals\nMachine learning packages (scikit-learn) → Advanced studies section\n\nPackage Manager (pip): Works like the library’s catalog:\n\nInstalling packages → Ordering new books\nUpdating packages → Replacing with newer editions\nUninstalling packages → Removing outdated books\nDependencies → “You must read Book A before Book B”\n\nVirtual Environments: Works like different library branches:\n\nEach branch can have its own collection of books (packages)\nDifferent editions of the same book (package versions)\nSpecialized sections for different purposes (project-specific dependencies)\n\n\nThe best part? Most Python packages are free to use, thanks to the open-source community!\n\n\n\n\n\n\nNote\n\n\n\nWhile we’ll practice some commands here, you’ll typically manage packages in your terminal or IDE."
+    "text": "Let’s break this down:\n\nStandard Library: Like the core collection every library branch has:\n\nPython comes with essential tools built-in\nData structures (lists, dictionaries, etc.)\nMathematical functions (sin, cos, sqrt, etc.)\nRandom numbers (random, choice, etc.)\n\nThird-Party Packages: Similar to specialized sections in a library:\n\nData analysis packages (pandas, numpy) → Research section\nVisualization packages (matplotlib, seaborn) → Art books\nWeb frameworks (Django, Flask) → Technical manuals\nMachine learning packages (scikit-learn) → Advanced studies section\n\nPackage Manager (pip): Works like the library’s catalog:\n\nInstalling packages → Ordering new books\nUpdating packages → Replacing with newer editions\nUninstalling packages → Removing outdated books\nDependencies → “You must read Book A before Book B”\n\nVirtual Environments: Works like different library branches:\n\nEach branch can have its own collection of books (packages)\nDifferent editions of the same book (package versions)\nSpecialized sections for different purposes (project-specific dependencies)\n\n\nThe best part? Most Python packages are free to use, thanks to the open-source community!\n\n\n\n\n\n\nNote\n\n\n\nWhile we’ll practice some commands here, you’ll typically manage packages in your terminal or IDE.",
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     "title": "Tutorial III.III - Package Management",
     "section": "Exercise 1.1 - Use the math library",
-    "text": "Exercise 1.1 - Use the math library\nUse the math library to calculate the square root of 256. Call the result square_root.\n\n# YOUR CODE BELOW\n\n\n\nCode\nassert square_root == 16\nprint(f\"Great job! The square root of 256 is {square_root}!\")"
+    "text": "Exercise 1.1 - Use the math library\nUse the math library to calculate the square root of 256. Call the result square_root.\n\n# YOUR CODE BELOW\n\n\n\nCode\nassert square_root == 16\nprint(f\"Great job! The square root of 256 is {square_root}!\")",
+    "crumbs": [
+      "03 Caching",
+      "09 - Packages"
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     "title": "Tutorial III.III - Package Management",
     "section": "Exercise 1.2 - Use the random library",
-    "text": "Exercise 1.2 - Use the random library\nUse the random library to generate a random number between 1 and 25. Call the result random_number.\n\n\nCode\nassert random_number >= 1 and random_number <= 25\nprint(f\"Good! You generated a random integer {random_number} between 1 and 25!\")"
+    "text": "Exercise 1.2 - Use the random library\nUse the random library to generate a random number between 1 and 25. Call the result random_number.\n\n\nCode\nassert random_number >= 1 and random_number <= 25\nprint(f\"Good! You generated a random integer {random_number} between 1 and 25!\")",
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+      "03 Caching",
+      "09 - Packages"
+    ]
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     "title": "Tutorial III.III - Package Management",
     "section": "Exercise 2.1 - Check your package manager version",
-    "text": "Exercise 2.1 - Check your package manager version\nLet’s start by checking which version of conda we have installed. We do so by running the following command in our terminal. Make sure, you are not working with python yet in the terminal, as this command is not available in the python shell. To open a new terminal in VS Code, you can press ctrl + shift + p and then type Terminal: Create new terminal. Then, run the following command:\nconda info"
+    "text": "Exercise 2.1 - Check your package manager version\nLet’s start by checking which version of conda we have installed. We do so by running the following command in our terminal. Make sure, you are not working with python yet in the terminal, as this command is not available in the python shell. To open a new terminal in VS Code, you can press ctrl + shift + p and then type Terminal: Create new terminal. Then, run the following command:\nconda info",
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+      "03 Caching",
+      "09 - Packages"
+    ]
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     "href": "part-03/tutorial-09-packages.html#exercise-3.1---install-pandas",
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     "section": "Exercise 3.1 - Install pandas",
-    "text": "Exercise 3.1 - Install pandas\nLet’s practice by installing pandas, a popular package for data analysis. Execute the following command in your terminal and make sure you are not in the python shell.\nconda install pandas\nYou can test if the installation was successful by running the following code.\n\n\nCode\n# Test your answer\ntry:\n    import pandas\n    print(\"pandas installed successfully!\")\nexcept ImportError:\n    print(\"pandas was not installed correctly\")"
+    "text": "Exercise 3.1 - Install pandas\nLet’s practice by installing pandas, a popular package for data analysis. Execute the following command in your terminal and make sure you are not in the python shell.\nconda install pandas\nYou can test if the installation was successful by running the following code.\n\n\nCode\n# Test your answer\ntry:\n    import pandas\n    print(\"pandas installed successfully!\")\nexcept ImportError:\n    print(\"pandas was not installed correctly\")",
+    "crumbs": [
+      "03 Caching",
+      "09 - Packages"
+    ]
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-    "text": "Throughout our previous tutorials, we’ve explored fundamental programming concepts through the lens of everyday decision-making. Now, let’s connect these concepts to another important algorithmic idea: caching.\nThe concepts we’ve learned map directly to caching principles:\n\nVariables → Like cache entries (storing specific pieces of information)\nComparisons → Like cache eviction policies (what we keep/remove)\nLists → Like cache storage (what we remember)\nLoops → Like cache maintenance (how we update our knowledge)\n\n\n\n\n\n\n\nWhat is Caching?\n\n\n\nRemember today’s lecture. Think of caching for example like your brain’s short-term memory. When you frequently need certain information (like your friend’s phone number), you keep it readily available instead of looking it up each time."
+    "text": "Throughout our previous tutorials, we’ve explored fundamental programming concepts through the lens of everyday decision-making. Now, let’s connect these concepts to another important algorithmic idea: caching.\nThe concepts we’ve learned map directly to caching principles:\n\nVariables → Like cache entries (storing specific pieces of information)\nComparisons → Like cache eviction policies (what we keep/remove)\nLists → Like cache storage (what we remember)\nLoops → Like cache maintenance (how we update our knowledge)\n\n\n\n\n\n\n\nWhat is Caching?\n\n\n\nRemember today’s lecture. Think of caching for example like your brain’s short-term memory. When you frequently need certain information (like your friend’s phone number), you keep it readily available instead of looking it up each time.",
+    "crumbs": [
+      "03 Caching",
+      "07 - Recap"
+    ]
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     "href": "part-03/tutorial-07-recap.html#exercise-1.1-create-a-simple-cache-system-for-your-favorite-restaurant-orders",
     "title": "Tutorial III.I - Caching and Recap",
     "section": "Exercise 1.1: Create a simple cache system for your favorite restaurant orders",
-    "text": "Exercise 1.1: Create a simple cache system for your favorite restaurant orders\n\nCreate a variable last_meal for the last meal you ordered (as a string)\nStore its price in a variable price (as a float)\nWhether you would order it again in a variable would_order_again (as a boolean)\nHow many times you’ve ordered it in the last month in a variable num_orders (as an integer)\n\n\n# YOUR CODE BELOW\n\n\n\nCode\n# Assertions to verify your solution\nassert isinstance(last_meal, str), \"last_meal should be a string\"\nassert isinstance(price, float), \"price should be a float\"\nassert isinstance(would_order_again, bool), \"would_order_again should be a boolean\"\nassert isinstance(num_orders, int), \"num_orders should be an integer\"\nprint(f\"Last meal: {last_meal}, price: {price}, would order again: {would_order_again}, number of orders in the last month: {num_orders}\")"
+    "text": "Exercise 1.1: Create a simple cache system for your favorite restaurant orders\n\nCreate a variable last_meal for the last meal you ordered (as a string)\nStore its price in a variable price (as a float)\nWhether you would order it again in a variable would_order_again (as a boolean)\nHow many times you’ve ordered it in the last month in a variable num_orders (as an integer)\n\n\n# YOUR CODE BELOW\n\n\n\nCode\n# Assertions to verify your solution\nassert isinstance(last_meal, str), \"last_meal should be a string\"\nassert isinstance(price, float), \"price should be a float\"\nassert isinstance(would_order_again, bool), \"would_order_again should be a boolean\"\nassert isinstance(num_orders, int), \"num_orders should be an integer\"\nprint(f\"Last meal: {last_meal}, price: {price}, would order again: {would_order_again}, number of orders in the last month: {num_orders}\")",
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+      "03 Caching",
+      "07 - Recap"
+    ]
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     "title": "Tutorial III.I - Caching and Recap",
     "section": "Exercise 2.1: Create a decision system for your favorite song",
-    "text": "Exercise 2.1: Create a decision system for your favorite song\n\nWrite a small decision system for your cached favorite song favorite_song\nUse at least two conditions based on the song’s play count and last played time (play_count and last_played_minutes_ago)\nYou can set the parameters for the conditions yourself\nSave the result of the decision in a variable should_evict\nPrint the result of whether we should evict the song or not\n\n\n# YOUR CODE BELOW\n\n\n\nCode\n# Assertions to verify your solution\nassert isinstance(favorite_song, str), \"favorite_song should be a string\"\nassert isinstance(play_count, int), \"play_count should be an integer\"\nassert isinstance(last_played_minutes_ago, int), \"last_played_minutes_ago should be an integer\"\nassert isinstance(should_evict, bool), \"should_evict should be a boolean\"\nprint(f\"Favorite song: {favorite_song}, play count: {play_count}, last played minutes ago: {last_played_minutes_ago}, should evict: {should_evict}\")"
+    "text": "Exercise 2.1: Create a decision system for your favorite song\n\nWrite a small decision system for your cached favorite song favorite_song\nUse at least two conditions based on the song’s play count and last played time (play_count and last_played_minutes_ago)\nYou can set the parameters for the conditions yourself\nSave the result of the decision in a variable should_evict\nPrint the result of whether we should evict the song or not\n\n\n# YOUR CODE BELOW\n\n\n\nCode\n# Assertions to verify your solution\nassert isinstance(favorite_song, str), \"favorite_song should be a string\"\nassert isinstance(play_count, int), \"play_count should be an integer\"\nassert isinstance(last_played_minutes_ago, int), \"last_played_minutes_ago should be an integer\"\nassert isinstance(should_evict, bool), \"should_evict should be a boolean\"\nprint(f\"Favorite song: {favorite_song}, play count: {play_count}, last played minutes ago: {last_played_minutes_ago}, should evict: {should_evict}\")",
+    "crumbs": [
+      "03 Caching",
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+    ]
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     "title": "Tutorial III.I - Caching and Recap",
     "section": "Exercise 3.1: Create a shopping cart cache",
-    "text": "Exercise 3.1: Create a shopping cart cache\n\nMake a list shopping_cart of five recently viewed items in your shopping cart\nCreate tuples for the item details (name and price) and add them to the list\nEnsure that the name is a string and the price is a float\n\n\n\n\n\n\n\nTip\n\n\n\nFirst, create a list. Inside the list, the entries should be tuples of the item name and price.\n\n\n\n# YOUR CODE BELOW\n\n\n\nCode\n# Assertions to verify your solution\nassert len(shopping_cart) == 5, \"shopping_cart should have 5 items\"\nassert isinstance(shopping_cart, list), \"shopping_cart should be a list\"\nassert all(isinstance(item, tuple) for item in shopping_cart), \"All items in shopping_cart should be tuples\"\nassert all(isinstance(item[0], str) and isinstance(item[1], (int, float)) for item in shopping_cart), \"All items in shopping_cart should be tuples with a string and a number\"\nprint(\"Great job! Your shopping cart is ready.\")"
+    "text": "Exercise 3.1: Create a shopping cart cache\n\nMake a list shopping_cart of five recently viewed items in your shopping cart\nCreate tuples for the item details (name and price) and add them to the list\nEnsure that the name is a string and the price is a float\n\n\n\n\n\n\n\nTip\n\n\n\nFirst, create a list. Inside the list, the entries should be tuples of the item name and price.\n\n\n\n# YOUR CODE BELOW\n\n\n\nCode\n# Assertions to verify your solution\nassert len(shopping_cart) == 5, \"shopping_cart should have 5 items\"\nassert isinstance(shopping_cart, list), \"shopping_cart should be a list\"\nassert all(isinstance(item, tuple) for item in shopping_cart), \"All items in shopping_cart should be tuples\"\nassert all(isinstance(item[0], str) and isinstance(item[1], (int, float)) for item in shopping_cart), \"All items in shopping_cart should be tuples with a string and a number\"\nprint(\"Great job! Your shopping cart is ready.\")",
+    "crumbs": [
+      "03 Caching",
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     "title": "Tutorial III.I - Caching and Recap",
     "section": "Exercise 4.1: Clean up a browser history cache",
-    "text": "Exercise 4.1: Clean up a browser history cache\n\nWrite a loop to remove sites with low visit counts\nIf the site has been visited less than 6 times, remove it from the cache\nPrint the browser history after cleanup\n\n\n\n\n\n\n\nTip\n\n\n\nBe careful with the loop. You need to iterate over the list and remove items from it. If you remove items directly from the list while iterating over it, you won’t get the correct answer, as the list will change size while you iterate over it. Thus, you first need to create a list of items to keep and at the end replace the old list with the new one.\n\n\n\nbrowser_history = [\n    (\"google.com\", 10), \n    (\"youtube.de\", 5), \n    (\"amazon.de\", 1), \n    (\"netflix.de\", 2), \n    (\"github.com\", 15)\n]\n# YOUR CODE BELOW\n\n\n\nCode\n# Assertions to verify your solution\nassert len(browser_history) == 2, \"browser_history should have 2 items\"\nassert isinstance(browser_history, list), \"browser_history should be a list\"\nassert all(isinstance(item, tuple) for item in browser_history), \"All items in browser_history should be tuples\""
+    "text": "Exercise 4.1: Clean up a browser history cache\n\nWrite a loop to remove sites with low visit counts\nIf the site has been visited less than 6 times, remove it from the cache\nPrint the browser history after cleanup\n\n\n\n\n\n\n\nTip\n\n\n\nBe careful with the loop. You need to iterate over the list and remove items from it. If you remove items directly from the list while iterating over it, you won’t get the correct answer, as the list will change size while you iterate over it. Thus, you first need to create a list of items to keep and at the end replace the old list with the new one.\n\n\n\nbrowser_history = [\n    (\"google.com\", 10), \n    (\"youtube.de\", 5), \n    (\"amazon.de\", 1), \n    (\"netflix.de\", 2), \n    (\"github.com\", 15)\n]\n# YOUR CODE BELOW\n\n\n\nCode\n# Assertions to verify your solution\nassert len(browser_history) == 2, \"browser_history should have 2 items\"\nassert isinstance(browser_history, list), \"browser_history should be a list\"\nassert all(isinstance(item, tuple) for item in browser_history), \"All items in browser_history should be tuples\"",
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     "title": "Tutorial II.III - Explore and Exploit",
     "section": "",
-    "text": "Introduction\nWelcome to the final tutorial of Part II! We’ll tie together everything we’ve learned so far - variables, lists, conditions, and loops - to tackle a classic explore-exploit problem: the one-armed bandit (slot machine). This is a perfect example of balancing exploration (trying different strategies) with exploitation (sticking to what works).\n\n\nSection 1 - Setting Up Our Casino\nFirst, let’s create a simple slot machine simulator using what we learned about variables and lists. In order to do this, we’ll need to import the random module, which we can do using the import statement. Don’t worry about the details of this statement for now - we’ll cover it in more detail in a future tutorial.\n\nimport random\n\n# Initial setup\nmoney = 100 # Starting money\nbet = 10 # How much we bet each time\npayouts = [0, 5, 10, 20, 50] # Different possible wins\n\nprint(\"Possible outcomes:\")\nfor payout in payouts:\n    print(f\"🎰 Win ${payout}\")\n\nPossible outcomes:\n🎰 Win $0\n🎰 Win $5\n🎰 Win $10\n🎰 Win $20\n🎰 Win $50\n\n\nIn this setup, we’re creating a simple slot machine where: - You start with $100 - Each play costs $10 - There are 5 possible payouts: $0 (loss), $5 (small win), $10 (break even), $20 (good win), and $50 (jackpot) - The random.choice() function simulates pulling the lever by randomly selecting one of these payouts\n\n\n\n\n\n\nNote\n\n\n\nIn real slot machines, the probabilities of different payouts aren’t equal. Higher payouts are much less likely to occur than lower ones. Our simplified version gives each payout an equal chance.\n\n\nTo simulate playing the slot machine once, we can start as follows:\n\n# Simulate playing the slot machine once\nwin = random.choice(payouts)\nmoney += win\nprint(f\"You bet ${bet}\")\nprint(f\"You won ${win}!\")\nprint(f\"Your new balance is ${money}\")\n\nYou bet $10\nYou won $5!\nYour new balance is $105\n\n\n\n\n\n\n\n\nTip\n\n\n\n+= is a shorthand for “add and assign”. So money += 10 is equivalent to money = money + 10. This also works for other arithmetic operations, like -=, *=, and /=.\n\n\n\n\nExercise 1.1 - Multiple Attempts\nNow let’s use a loop to play multiple times and track our results. Write a loop that:\n\nPlays the slot machine 10 times\nSubtracts the bet amount each time\nAdds a random payout\nStores the results in a list\n\n\nmoney = 100 # Reset our money\nbet = 10 # How much we bet each time\nresults = [] # List to store how much money we have after each play\n\n# YOUR CODE BELOW\n\n\n\nCode\n# Check your results\nassert len(results) == 10, \"You should have 10 results in your list\"\nassert all(isinstance(x, (int, float)) for x in results), \"All results should be numbers\"\nprint(f\"You played the slot machine {len(results)} times\")\nprint(f\"Your final balance is ${results[-1]}\")\nprint(f\"Unfortunately, the payout rates are not realistic here...\")\n\n\n\n\n\n\n\n\nTip\n\n\n\nUse the append() method to add an element to a list. For example, results.append(money) will add the current value of money to the results list.\n\n\n\n\nExercise 1.2 - Playing with a Budget\nNow let’s simulate playing the slot machine multiple times with a budget. We’ll use a while loop to play until we run out of money. This is more realistic than playing a fixed number of times, as real players need to stop when they’re out of money!\nThe machine_payout_rate represents how generous the machine is:\n\nThe function random.random() generates a random number between 0 and 1.\nA rate of 2.0 means you get back exactly what you bet (on average)\nOur rate of 1.5 means you could win up to 1.5 times your bet but on average you’ll get back 0.75 times your bet\n\n# Compute the payout for the current play\nmachine_payout_rate = 1.5\npayout = random.random() * machine_payout_rate * bet\nUse a while loop to play the slot machine until you run out of money, and store the amount of money you have after each play in the results list. Further, print out the amount of money you have after each play with a formatted string.\n\nimport random\n\nmachine_payout_rate = 1.5 # Payout rate for the machine\nbet = 10 # Bet size\nmoney = 100 # Our starting money\nresults = [] # Store results of each play here\n\n# YOUR CODE BELOW \n\n\n\nCode\n# Check your results\nassert len(results) > 0, \"You should have at least one result\"\nassert all(isinstance(x, (int, float)) for x in results), \"All results should be numbers\"\nassert results[-1] <= bet, \"Should stop playing when money is less than bet amount\"\nassert all(abs(results[i] - results[i-1]) <= bet * machine_payout_rate for i in range(1, len(results))), \"Each play should not change money by more than maximum possible payout\"\nprint(f\"You played the slot machine {len(results)} times\")\n\n\n\n\nSection 2 - Nested Loops\nNow let’s use nested loops to try different slot machines with different payout rates. This is where exploration comes in! Nested loops are a way to repeat a loop multiple times, and we can use them to try different options. It’s essentially a loop inside another loop.\n\n\n\n\n\n\nTip\n\n\n\nNested loops are like a clock: the outer loop is like the hour hand (moves slowly), and the inner loop is like the minute hand (completes a full cycle for each move of the hour hand).\n\n\nFor example, for machine in range(3) will run a loop 3 times. We can use nested loops to try all combinations of two different options.\n\nfor machine in range(3):\n    for payout in range(4):\n        print(f\"Machine Nr. {machine}, Payout Nr. {payout}\")\n\nMachine Nr. 0, Payout Nr. 0\nMachine Nr. 0, Payout Nr. 1\nMachine Nr. 0, Payout Nr. 2\nMachine Nr. 0, Payout Nr. 3\nMachine Nr. 1, Payout Nr. 0\nMachine Nr. 1, Payout Nr. 1\nMachine Nr. 1, Payout Nr. 2\nMachine Nr. 1, Payout Nr. 3\nMachine Nr. 2, Payout Nr. 0\nMachine Nr. 2, Payout Nr. 1\nMachine Nr. 2, Payout Nr. 2\nMachine Nr. 2, Payout Nr. 3\n\n\n\n\nExercise 2.1 - Simulating Multiple Machines\nThe setup is the same as in Exercise 1.2, but we’re now comparing three different machines, each with its own payout rate. Use a while loop for each machine and a for loop to try all machines. As the bank always wins, we’re not interested in the results for each machine, but rather in the number of times we can play each machine before we run out of money.\nStore the number of plays in a list called plays with three elements, one for each machine. The goal is to find out which machine lets us play the longest with our budget. This is a common exploration strategy: try each option several times to understand its characteristics.\n\nimport random\n# Different machines might have different payout rates\nmachine_1_payout_rate = 1.2\nmachine_2_payout_rate = 1.5\nmachine_3_payout_rate = 1.8\n\nbet = 10 # Bet size at each play\nbudget = 100 # Our starting money for each machine!\nplays = [0, 0, 0] # List to store number of plays for each machine\n\n# YOUR CODE BELOW\n\n\n\nCode\n# Check your results\nassert len(plays) == 3, \"Should have results for three machines\"\nassert all(isinstance(x, int) and x >= 0 for x in plays), \"Number of plays should be non-negative integers\"\nassert all(x <= budget/bet * 6 for x in plays), \"Number of plays seems unreasonably high given budget\"\nprint(f\"You played the slot machine {plays[0]} times on machine 1\")\nprint(f\"You played the slot machine {plays[1]} times on machine 2\")\nprint(f\"You played the slot machine {plays[2]} times on machine 3\")\n\n\n\n\nExercise 2.2 - Exploring the Machines\nNow let’s find out which machine is the best and which one is the worst by comparing the number of plays for each machine. Store the index of the best machine in best_machine and the index of the worst machine in worst_machine. You can use the max(plays) function to find the maximum number of plays in the plays list and the plays.index(max(plays)) function to find the index of the maximum number of plays.\n\n# YOUR CODE BELOW\n\n\n\nCode\n# Check your results\nassert isinstance(best_machine, int) and 0 <= best_machine <= 2, \"Best machine should be 0, 1, or 2\"\nassert isinstance(worst_machine, int) and 0 <= worst_machine <= 2, \"Worst machine should be 0, 1, or 2\"\nassert best_machine != worst_machine, \"Best and worst machine cannot be the same\"\nprint(f\"The best machine is machine {best_machine}\")\nprint(f\"The worst machine is machine {worst_machine}\")\n\n\n\n\nConclusion\nExcellent work! You’ve successfully combined multiple programming concepts to tackle a real explore-exploit problem:\n\nVariables and types for tracking money and bets\nLists for storing payouts and results\nLoops (including nested loops) for testing different machines\nConditions for finding the best machine\n\nThis is a simplified version of how casinos and gambling companies might analyze their games, though in reality, they use much more sophisticated algorithms! Remember though, that the casino always wins!\n\n\nSolutions\nYou will likely find solutions to most exercises online. However, we strongly encourage you to work on these exercises independently without searching explicitly for the exact answers to the exercises. Understanding someone else’s solution is very different from developing your own. Use the lecture notes and try to solve the exercises on your own. This approach will significantly enhance your learning and problem-solving skills.\nRemember, the goal is not just to complete the exercises, but to understand the concepts and improve your programming abilities. If you encounter difficulties, review the lecture materials, experiment with different approaches, and don’t hesitate to ask for clarification during class discussions.\nLater, you will find the solutions to these exercises online in the associated GitHub repository, but we will also quickly go over them next week. To access the solutions, click on the Github button on the lower right and search for the folder with today’s lecture and tutorial. Alternatively, you can ask ChatGPT or Claude to explain them to you. But please remember, the goal is not just to complete the exercises, but to understand the concepts and improve your programming abilities.\n\nThat’s it for part II! Next week, we’ll learn about functions and how to use them to make our code more efficient and reusable.",
+    "text": "Introduction\nWelcome to the final tutorial of Part II! We’ll tie together everything we’ve learned so far - variables, lists, conditions, and loops - to tackle a classic explore-exploit problem: the one-armed bandit (slot machine). This is a perfect example of balancing exploration (trying different strategies) with exploitation (sticking to what works).\n\n\nSection 1 - Setting Up Our Casino\nFirst, let’s create a simple slot machine simulator using what we learned about variables and lists. In order to do this, we’ll need to import the random module, which we can do using the import statement. Don’t worry about the details of this statement for now - we’ll cover it in more detail in a future tutorial.\n\nimport random\n\n# Initial setup\nmoney = 100 # Starting money\nbet = 10 # How much we bet each time\npayouts = [0, 5, 10, 20, 50] # Different possible wins\n\nprint(\"Possible outcomes:\")\nfor payout in payouts:\n    print(f\"🎰 Win ${payout}\")\n\nPossible outcomes:\n🎰 Win $0\n🎰 Win $5\n🎰 Win $10\n🎰 Win $20\n🎰 Win $50\n\n\nIn this setup, we’re creating a simple slot machine where: - You start with $100 - Each play costs $10 - There are 5 possible payouts: $0 (loss), $5 (small win), $10 (break even), $20 (good win), and $50 (jackpot) - The random.choice() function simulates pulling the lever by randomly selecting one of these payouts\n\n\n\n\n\n\nNote\n\n\n\nIn real slot machines, the probabilities of different payouts aren’t equal. Higher payouts are much less likely to occur than lower ones. Our simplified version gives each payout an equal chance.\n\n\nTo simulate playing the slot machine once, we can start as follows:\n\n# Simulate playing the slot machine once\nwin = random.choice(payouts)\nmoney += win\nprint(f\"You bet ${bet}\")\nprint(f\"You won ${win}!\")\nprint(f\"Your new balance is ${money}\")\n\nYou bet $10\nYou won $0!\nYour new balance is $100\n\n\n\n\n\n\n\n\nTip\n\n\n\n+= is a shorthand for “add and assign”. So money += 10 is equivalent to money = money + 10. This also works for other arithmetic operations, like -=, *=, and /=.\n\n\n\n\nExercise 1.1 - Multiple Attempts\nNow let’s use a loop to play multiple times and track our results. Write a loop that:\n\nPlays the slot machine 10 times\nSubtracts the bet amount each time\nAdds a random payout\nStores the results in a list\n\n\nmoney = 100 # Reset our money\nbet = 10 # How much we bet each time\nresults = [] # List to store how much money we have after each play\n\n# YOUR CODE BELOW\n\n\n\nCode\n# Check your results\nassert len(results) == 10, \"You should have 10 results in your list\"\nassert all(isinstance(x, (int, float)) for x in results), \"All results should be numbers\"\nprint(f\"You played the slot machine {len(results)} times\")\nprint(f\"Your final balance is ${results[-1]}\")\nprint(f\"Unfortunately, the payout rates are not realistic here...\")\n\n\n\n\n\n\n\n\nTip\n\n\n\nUse the append() method to add an element to a list. For example, results.append(money) will add the current value of money to the results list.\n\n\n\n\nExercise 1.2 - Playing with a Budget\nNow let’s simulate playing the slot machine multiple times with a budget. We’ll use a while loop to play until we run out of money. This is more realistic than playing a fixed number of times, as real players need to stop when they’re out of money!\nThe machine_payout_rate represents how generous the machine is:\n\nThe function random.random() generates a random number between 0 and 1.\nA rate of 2.0 means you get back exactly what you bet (on average)\nOur rate of 1.5 means you could win up to 1.5 times your bet but on average you’ll get back 0.75 times your bet\n\n# Compute the payout for the current play\nmachine_payout_rate = 1.5\npayout = random.random() * machine_payout_rate * bet\nUse a while loop to play the slot machine until you run out of money, and store the amount of money you have after each play in the results list. Further, print out the amount of money you have after each play with a formatted string.\n\nimport random\n\nmachine_payout_rate = 1.5 # Payout rate for the machine\nbet = 10 # Bet size\nmoney = 100 # Our starting money\nresults = [] # Store results of each play here\n\n# YOUR CODE BELOW \n\n\n\nCode\n# Check your results\nassert len(results) > 0, \"You should have at least one result\"\nassert all(isinstance(x, (int, float)) for x in results), \"All results should be numbers\"\nassert results[-1] <= bet, \"Should stop playing when money is less than bet amount\"\nassert all(abs(results[i] - results[i-1]) <= bet * machine_payout_rate for i in range(1, len(results))), \"Each play should not change money by more than maximum possible payout\"\nprint(f\"You played the slot machine {len(results)} times\")\n\n\n\n\nSection 2 - Nested Loops\nNow let’s use nested loops to try different slot machines with different payout rates. This is where exploration comes in! Nested loops are a way to repeat a loop multiple times, and we can use them to try different options. It’s essentially a loop inside another loop.\n\n\n\n\n\n\nTip\n\n\n\nNested loops are like a clock: the outer loop is like the hour hand (moves slowly), and the inner loop is like the minute hand (completes a full cycle for each move of the hour hand).\n\n\nFor example, for machine in range(3) will run a loop 3 times. We can use nested loops to try all combinations of two different options.\n\nfor machine in range(3):\n    for payout in range(4):\n        print(f\"Machine Nr. {machine}, Payout Nr. {payout}\")\n\nMachine Nr. 0, Payout Nr. 0\nMachine Nr. 0, Payout Nr. 1\nMachine Nr. 0, Payout Nr. 2\nMachine Nr. 0, Payout Nr. 3\nMachine Nr. 1, Payout Nr. 0\nMachine Nr. 1, Payout Nr. 1\nMachine Nr. 1, Payout Nr. 2\nMachine Nr. 1, Payout Nr. 3\nMachine Nr. 2, Payout Nr. 0\nMachine Nr. 2, Payout Nr. 1\nMachine Nr. 2, Payout Nr. 2\nMachine Nr. 2, Payout Nr. 3\n\n\n\n\nExercise 2.1 - Simulating Multiple Machines\nThe setup is the same as in Exercise 1.2, but we’re now comparing three different machines, each with its own payout rate. Use a while loop for each machine and a for loop to try all machines. As the bank always wins, we’re not interested in the results for each machine, but rather in the number of times we can play each machine before we run out of money.\nStore the number of plays in a list called plays with three elements, one for each machine. The goal is to find out which machine lets us play the longest with our budget. This is a common exploration strategy: try each option several times to understand its characteristics.\n\nimport random\n# Different machines might have different payout rates\nmachine_1_payout_rate = 1.2\nmachine_2_payout_rate = 1.5\nmachine_3_payout_rate = 1.8\n\nbet = 10 # Bet size at each play\nbudget = 100 # Our starting money for each machine!\nplays = [0, 0, 0] # List to store number of plays for each machine\n\n# YOUR CODE BELOW\n\n\n\nCode\n# Check your results\nassert len(plays) == 3, \"Should have results for three machines\"\nassert all(isinstance(x, int) and x >= 0 for x in plays), \"Number of plays should be non-negative integers\"\nassert all(x <= budget/bet * 6 for x in plays), \"Number of plays seems unreasonably high given budget\"\nprint(f\"You played the slot machine {plays[0]} times on machine 1\")\nprint(f\"You played the slot machine {plays[1]} times on machine 2\")\nprint(f\"You played the slot machine {plays[2]} times on machine 3\")\n\n\n\n\nExercise 2.2 - Exploring the Machines\nNow let’s find out which machine is the best and which one is the worst by comparing the number of plays for each machine. Store the index of the best machine in best_machine and the index of the worst machine in worst_machine. You can use the max(plays) function to find the maximum number of plays in the plays list and the plays.index(max(plays)) function to find the index of the maximum number of plays.\n\n# YOUR CODE BELOW\n\n\n\nCode\n# Check your results\nassert isinstance(best_machine, int) and 0 <= best_machine <= 2, \"Best machine should be 0, 1, or 2\"\nassert isinstance(worst_machine, int) and 0 <= worst_machine <= 2, \"Worst machine should be 0, 1, or 2\"\nassert best_machine != worst_machine, \"Best and worst machine cannot be the same\"\nprint(f\"The best machine is machine {best_machine}\")\nprint(f\"The worst machine is machine {worst_machine}\")\n\n\n\n\nConclusion\nExcellent work! You’ve successfully combined multiple programming concepts to tackle a real explore-exploit problem:\n\nVariables and types for tracking money and bets\nLists for storing payouts and results\nLoops (including nested loops) for testing different machines\nConditions for finding the best machine\n\nThis is a simplified version of how casinos and gambling companies might analyze their games, though in reality, they use much more sophisticated algorithms! Remember though, that the casino always wins!\n\n\nSolutions\nYou will likely find solutions to most exercises online. However, we strongly encourage you to work on these exercises independently without searching explicitly for the exact answers to the exercises. Understanding someone else’s solution is very different from developing your own. Use the lecture notes and try to solve the exercises on your own. This approach will significantly enhance your learning and problem-solving skills.\nRemember, the goal is not just to complete the exercises, but to understand the concepts and improve your programming abilities. If you encounter difficulties, review the lecture materials, experiment with different approaches, and don’t hesitate to ask for clarification during class discussions.\nLater, you will find the solutions to these exercises online in the associated GitHub repository, but we will also quickly go over them next week. To access the solutions, click on the Github button on the lower right and search for the folder with today’s lecture and tutorial. Alternatively, you can ask ChatGPT or Claude to explain them to you. But please remember, the goal is not just to complete the exercises, but to understand the concepts and improve your programming abilities.\n\nThat’s it for part II! Next week, we’ll learn about functions and how to use them to make our code more efficient and reusable.",
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-    "text": "By the end of this lecture, you will be able to:\n\n\n\nExplain the fundamental concepts of caching and its importance\nCompare different cache replacement strategies\nIdentify caching principles in everyday life\nApply caching concepts to personal productivity\nUnderstand the relationship between caching and attention management"
+    "text": "By the end of this lecture, you will be able to:\n\n\n\nExplain the fundamental concepts of caching and its importance\nCompare different cache replacement strategies\nIdentify caching principles in everyday life\nApply caching concepts to personal productivity\nUnderstand the relationship between caching and attention management",
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-    "text": "Caching: Making the most of limited resources\n\n\nIn the practical use of our intellect, forgetting is as important a function as remembering. – [William James]\n\n\n\n\nToday’s lecture is on caching.\nThe discussed topics are highly relevant for everything that has to do with computers and data.\nOn top of that, caching is another very important concept for our everyday decision-making."
+    "text": "Caching: Making the most of limited resources\n\n\nIn the practical use of our intellect, forgetting is as important a function as remembering. – [William James]\n\n\n\n\nToday’s lecture is on caching.\nThe discussed topics are highly relevant for everything that has to do with computers and data.\nOn top of that, caching is another very important concept for our everyday decision-making.",
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     "title": "Lecture III - Caching",
     "section": "Let’s approach the topic using an everyday decision-making situation",
-    "text": "Let’s approach the topic using an everyday decision-making situation\n\n\n\n\n\n\n\n\nWe have a problem: Our cupboard.\nIt’s time to put things in order."
+    "text": "Let’s approach the topic using an everyday decision-making situation\n\n\n\n\n\n\n\n\nWe have a problem: Our cupboard.\nIt’s time to put things in order.",
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     "section": "Question: What could we do?",
-    "text": "Question: What could we do?\n\n\n\n\n\n\n\n\nBetter organization\nClearing out things we no longer need\nNow we have two problems:\n\nStoring?\nClearing out?"
+    "text": "Question: What could we do?\n\n\n\n\n\n\n\n\nBetter organization\nClearing out things we no longer need\nNow we have two problems:\n\nStoring?\nClearing out?",
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     "section": "Storing",
-    "text": "Storing\n\n\n\n\n\n\n\nHow to bring order to storage?\n\nSubdivide storage\nEfficient sorting\nIncrease capacity"
+    "text": "Storing\n\n\n\n\n\n\n\nHow to bring order to storage?\n\nSubdivide storage\nEfficient sorting\nIncrease capacity",
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     "title": "Lecture III - Caching",
     "section": "Subdivide storage and efficient sorting outcome",
-    "text": "Subdivide storage and efficient sorting outcome\n\n\n\n\n\n\n\n\nTime investment can improve storing.\nThat is a difficult trade-off in itself.\nNontheless: Each storage has a limited capacity."
+    "text": "Subdivide storage and efficient sorting outcome\n\n\n\n\n\n\n\n\nTime investment can improve storing.\nThat is a difficult trade-off in itself.\nNontheless: Each storage has a limited capacity.",
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     "title": "Lecture III - Caching",
     "section": "Question: What do we do, when the storage is full?",
-    "text": "Question: What do we do, when the storage is full?\n\n\nWe could increase the capacity"
+    "text": "Question: What do we do, when the storage is full?\n\n\nWe could increase the capacity",
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     "section": "But…",
-    "text": "But…\n\n\n\n\n\n\n\n\nIncrease capacity is costly.\nThere is a trade-off between size and speed.\nSooner or later, every storage will fill up if not cleared out."
+    "text": "But…\n\n\n\n\n\n\n\n\nIncrease capacity is costly.\nThere is a trade-off between size and speed.\nSooner or later, every storage will fill up if not cleared out.",
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     "title": "Lecture III - Caching",
     "section": "Question: What types of storages can you imagine that are affected by this?",
-    "text": "Question: What types of storages can you imagine that are affected by this?\n\n\nOur cupboard\nOur computer (hard drive, RAM, cache, …)\nOur brain?!"
+    "text": "Question: What types of storages can you imagine that are affected by this?\n\n\nOur cupboard\nOur computer (hard drive, RAM, cache, …)\nOur brain?!",
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     "title": "Lecture III - Caching",
     "section": "Question: What is the impact of a full storage?",
-    "text": "Question: What is the impact of a full storage?\n\n\n\n\n\n\n\n\nAccess speed drops significantly\nProcessing time increases\nOverall performance decreases"
+    "text": "Question: What is the impact of a full storage?\n\n\n\n\n\n\n\n\nAccess speed drops significantly\nProcessing time increases\nOverall performance decreases",
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     "title": "Lecture III - Caching",
     "section": "Now we see, why clearing out is so important",
-    "text": "Now we see, why clearing out is so important\n\n\nAnd that goes for our cupboard as well as for computers and other storages…\nBut what stays and what goes?"
+    "text": "Now we see, why clearing out is so important\n\n\nAnd that goes for our cupboard as well as for computers and other storages…\nBut what stays and what goes?",
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     "title": "Lecture III - Caching",
     "section": "Question: What replacement/eviction policies can you imagine?",
-    "text": "Question: What replacement/eviction policies can you imagine?\n\n\nRandom Eviction\nFirst-In, First-Out (FIFO)\nLeast Recently Used (LRU)"
+    "text": "Question: What replacement/eviction policies can you imagine?\n\n\nRandom Eviction\nFirst-In, First-Out (FIFO)\nLeast Recently Used (LRU)",
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     "title": "Lecture III - Caching",
     "section": "Once again, we can learn a lot from the computer sciences.",
-    "text": "Once again, we can learn a lot from the computer sciences.\n\nThe evolution of computer memory\n\n\n\nIn the 1950s, computer science faced the same question…\n…and has faced it repeatedly since then.\nProcessors have become faster and faster (Moore’s Law).\nThe demands on memory also grew."
+    "text": "Once again, we can learn a lot from the computer sciences.\n\nThe evolution of computer memory\n\n\n\nIn the 1950s, computer science faced the same question…\n…and has faced it repeatedly since then.\nProcessors have become faster and faster (Moore’s Law).\nThe demands on memory also grew.",
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     "section": "CPU",
-    "text": "CPU\n\n\nThe processor (CPU, Central Processing Unit) is central to a computer and is often referred to as the “brain” of the system.\nIt executes instructions and performs calculations, to process data and run programs."
+    "text": "CPU\n\n\nThe processor (CPU, Central Processing Unit) is central to a computer and is often referred to as the “brain” of the system.\nIt executes instructions and performs calculations, to process data and run programs.",
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     "section": "Problem: Access Time",
-    "text": "Problem: Access Time\n\n\n\n\n\n\n\nflowchart LR\n    subgraph Memory\n    A[\"Input Data\"]\n    end\n    \n    subgraph CPU\n    B[\"Processing Data\"]\n    end\n    \n    subgraph Memory\n    C[\"Output Data\"]\n    end\n    \n    A --> B --> C\n    \n    style Memory fill:white,stroke:#01579B,stroke-width:4px\n    style CPU fill:white,stroke:#01579B,stroke-width:4px\n    style Memory fill:white,stroke:#01579B,stroke-width:4px\n    style A fill:white\n    style B fill:white\n    style C fill:white\n\n\n\n\n\n\n\nProblem: No matter how much faster the processor gets, if input data isn’t available fast enough or can’t be stored quickly enough, the system won’t become faster overall.\nQuestion: What is the solution?"
+    "text": "Problem: Access Time\n\n\n\n\n\n\n\nflowchart LR\n    subgraph Memory\n    A[\"Input Data\"]\n    end\n    \n    subgraph CPU\n    B[\"Processing Data\"]\n    end\n    \n    subgraph Memory\n    C[\"Output Data\"]\n    end\n    \n    A --> B --> C\n    \n    style Memory fill:white,stroke:#01579B,stroke-width:4px\n    style CPU fill:white,stroke:#01579B,stroke-width:4px\n    style Memory fill:white,stroke:#01579B,stroke-width:4px\n    style A fill:white\n    style B fill:white\n    style C fill:white\n\n\n\n\n\n\n\nProblem: No matter how much faster the processor gets, if input data isn’t available fast enough or can’t be stored quickly enough, the system won’t become faster overall.\nQuestion: What is the solution?",
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     "section": "Cache",
-    "text": "Cache\n\nHierarchical memory pyramid for efficient data management\n\n\n\nL1 Cache, directly on CPU, very fast access time.\nL2 Cache, between L1 and main memory.\nRAM memory.\nMass Storage (hard drive).\nThe whole memory system works like a library.\nFind an explanation here."
+    "text": "Cache\n\nHierarchical memory pyramid for efficient data management\n\n\n\nL1 Cache, directly on CPU, very fast access time.\nL2 Cache, between L1 and main memory.\nRAM memory.\nMass Storage (hard drive).\nThe whole memory system works like a library.\nFind an explanation here.",
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     "section": "Cache - Size and Speed trade-off",
-    "text": "Cache - Size and Speed trade-off\n\n\nRegisters are 10 million times faster than the hard drive!"
+    "text": "Cache - Size and Speed trade-off\n\n\nRegisters are 10 million times faster than the hard drive!",
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     "section": "Library Principle",
-    "text": "Library Principle\n\n\n\n\n\n\n\n\nLibrary storage (5 million books, Mass Storage)\nSubject locations (100K books, RAM)\nDesk (5 borrowed books, L2)\nShort-term memory (L1)"
+    "text": "Library Principle\n\n\n\n\n\n\n\n\nLibrary storage (5 million books, Mass Storage)\nSubject locations (100K books, RAM)\nDesk (5 borrowed books, L2)\nShort-term memory (L1)",
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     "section": "Library Principle",
-    "text": "Library Principle\n\n\n\n\n\n\n\n\nL1 and L2 cache only contain most necessary data.\nThe same should apply to your desk.\nTherefore, both must be cleared regularly."
+    "text": "Library Principle\n\n\n\n\n\n\n\n\nL1 and L2 cache only contain most necessary data.\nThe same should apply to your desk.\nTherefore, both must be cleared regularly.",
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     "section": "How to clear up?",
-    "text": "How to clear up?\n\n\nOptimal: Clairvoyance\n\nStore everything in the cache that will be needed\nDelete everything from the cache that won’t be needed\n\nQuestion: What is the problem with this strategy?\nOptimal strategy not achievable in reality"
+    "text": "How to clear up?\n\n\nOptimal: Clairvoyance\n\nStore everything in the cache that will be needed\nDelete everything from the cache that won’t be needed\n\nQuestion: What is the problem with this strategy?\nOptimal strategy not achievable in reality",
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     "section": "Realisable strategies?",
-    "text": "Realisable strategies?\n\n\nLeast recently used is the dominant strategy.\nEvicts the least recently accessed item from the cache when space is needed.\nLeads to much better performance on average than, for example, random eviction.\nQuestion: Why do you think least recently used is the better strategy?"
+    "text": "Realisable strategies?\n\n\nLeast recently used is the dominant strategy.\nEvicts the least recently accessed item from the cache when space is needed.\nLeads to much better performance on average than, for example, random eviction.\nQuestion: Why do you think least recently used is the better strategy?",
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     "section": "Managerial and personal insights:",
-    "text": "Managerial and personal insights:\n\n\nLet go of things you haven’t used in ages\nKeep things where they are used\nBoth have been proven to contribute to a significant increase in productivity"
+    "text": "Managerial and personal insights:\n\n\nLet go of things you haven’t used in ages\nKeep things where they are used\nBoth have been proven to contribute to a significant increase in productivity",
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     "section": "Keeping things where they are used…",
-    "text": "Keeping things where they are used…\n\n\nMight be optimal, in a mathematical sense"
+    "text": "Keeping things where they are used…\n\n\nMight be optimal, in a mathematical sense",
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     "title": "Lecture III - Caching",
     "section": "The strong limitations of caches make them a “security risk”.",
-    "text": "The strong limitations of caches make them a “security risk”.\n\n\nDenial-of-Service Attacks (DoS) attacks.\n\nCache Flooding\nCache Poisoning\n\nOverload a system with excessive requests or data.\nCausing it to slow down or crash.\nThe system is forced to evict important data."
+    "text": "The strong limitations of caches make them a “security risk”.\n\n\nDenial-of-Service Attacks (DoS) attacks.\n\nCache Flooding\nCache Poisoning\n\nOverload a system with excessive requests or data.\nCausing it to slow down or crash.\nThe system is forced to evict important data.",
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     "title": "Lecture III - Caching",
     "section": "Question: Why are the findings about cache so important for humans?",
-    "text": "Question: Why are the findings about cache so important for humans?\n\n\nYour Brain is a Cache, Not a Database -[Joe Chrysler]"
+    "text": "Question: Why are the findings about cache so important for humans?\n\n\nYour Brain is a Cache, Not a Database -[Joe Chrysler]",
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     "section": "Our brain has similar weaknesses",
-    "text": "Our brain has similar weaknesses\n\nProductivity and creativity are negatively affected by:\n\n\n\nOverload (too much)\nExhaustion (too long)\nContext switching (interruption of “flow”, 23 minutes to get back on track)\nDistraction (Cache Flooding)\nFake News (Cache Poisoning)\n\n\n\nThis can lead to burnout."
+    "text": "Our brain has similar weaknesses\n\nProductivity and creativity are negatively affected by:\n\n\n\nOverload (too much)\nExhaustion (too long)\nContext switching (interruption of “flow”, 23 minutes to get back on track)\nDistraction (Cache Flooding)\nFake News (Cache Poisoning)\n\n\n\nThis can lead to burnout.",
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     "title": "Lecture III - Caching",
     "section": "Question: What do you think should we do about it?",
-    "text": "Question: What do you think should we do about it?"
+    "text": "Question: What do you think should we do about it?",
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     "title": "Lecture III - Caching",
     "section": "Stolen Focus: Why You Can’t Pay Attention - Key Insights I",
-    "text": "Stolen Focus: Why You Can’t Pay Attention - Key Insights I\n\nMain Idea:\n\n\n\nModern life is eroding our ability to concentrate and engage deeply, with societal factors affecting personal focus.\nThe reason for that has much to do with the way our brain works and how we interact with technology."
+    "text": "Stolen Focus: Why You Can’t Pay Attention - Key Insights I\n\nMain Idea:\n\n\n\nModern life is eroding our ability to concentrate and engage deeply, with societal factors affecting personal focus.\nThe reason for that has much to do with the way our brain works and how we interact with technology.",
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     "section": "Stolen Focus: Why You Can’t Pay Attention - Key Insights II",
-    "text": "Stolen Focus: Why You Can’t Pay Attention - Key Insights II\n\nKey Causes of Attention Loss:\n\n\n\nTechnology & Social Media: Designed to capture and keep attention, leading to fragmented focus.\nConstant Interruptions: Notifications and multitasking disrupt deep work and concentration.\nEnvironmental & Lifestyle Factors: Poor sleep, stress, and diet impact cognitive function."
+    "text": "Stolen Focus: Why You Can’t Pay Attention - Key Insights II\n\nKey Causes of Attention Loss:\n\n\n\nTechnology & Social Media: Designed to capture and keep attention, leading to fragmented focus.\nConstant Interruptions: Notifications and multitasking disrupt deep work and concentration.\nEnvironmental & Lifestyle Factors: Poor sleep, stress, and diet impact cognitive function.",
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     "section": "Stolen Focus: Why You Can’t Pay Attention - Key Insights III",
-    "text": "Stolen Focus: Why You Can’t Pay Attention - Key Insights III\n\nConsequences:\n\n\n\nReduced ability to think critically and creatively.\nDifficulty sustaining attention on meaningful tasks."
+    "text": "Stolen Focus: Why You Can’t Pay Attention - Key Insights III\n\nConsequences:\n\n\n\nReduced ability to think critically and creatively.\nDifficulty sustaining attention on meaningful tasks.",
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     "section": "Stolen Focus: Why You Can’t Pay Attention - Key Insights IV",
-    "text": "Stolen Focus: Why You Can’t Pay Attention - Key Insights IV\n\nSolutions Suggested:\n\n\n\nLimit screen time and practice “monotasking.”\nPrioritize sleep, nutrition, and mindful habits."
+    "text": "Stolen Focus: Why You Can’t Pay Attention - Key Insights IV\n\nSolutions Suggested:\n\n\n\nLimit screen time and practice “monotasking.”\nPrioritize sleep, nutrition, and mindful habits.",
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     "section": "Stolen Focus: Why You Can’t Pay Attention - Key Insights V",
-    "text": "Stolen Focus: Why You Can’t Pay Attention - Key Insights V\n\n\n\nBut even better: read the book!"
+    "text": "Stolen Focus: Why You Can’t Pay Attention - Key Insights V\n\n\n\nBut even better: read the book!",
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     "title": "Lecture III - Caching",
     "section": "Stolen Focus: Why You Can’t Pay Attention - Book",
-    "text": "Stolen Focus: Why You Can’t Pay Attention - Book"
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-    "text": "Mitigation\n\n\nDistraction can hardly be avoided in today’s world but can be mitigated.\nThis is particularly important for managers.\nThis lecture is designed to raise your awareness of what you can do to keep your brain working efficiently."
+    "text": "Mitigation\n\n\nDistraction can hardly be avoided in today’s world but can be mitigated.\nThis is particularly important for managers.\nThis lecture is designed to raise your awareness of what you can do to keep your brain working efficiently.",
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     "section": "Awareness I",
-    "text": "Awareness I\n\nTrain awareness\n\n\n\nSpotlight – immediate goals – Focus\nStarlight – medium-term goals – Wishes\nDaylight – long-term goals – Values"
+    "text": "Awareness I\n\nTrain awareness\n\n\n\nSpotlight – immediate goals – Focus\nStarlight – medium-term goals – Wishes\nDaylight – long-term goals – Values",
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     "section": "Awareness II",
-    "text": "Awareness II\n\nPrioritization\n\n\n\nPrioritization\nStructure (Schedule)\nBreaks\nEnable flow (dedicated workspace, manage notifications, clear communication)\nMeditation & exercise"
+    "text": "Awareness II\n\nPrioritization\n\n\n\nPrioritization\nStructure (Schedule)\nBreaks\nEnable flow (dedicated workspace, manage notifications, clear communication)\nMeditation & exercise",
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     "section": "Key Takeaways",
-    "text": "Key Takeaways\n\n\nCaching is a universal concept that applies to computers, organizations, and human cognition\nEfficient cache management requires strategic decisions about what to keep and what to remove\nLRU (Least Recently Used) is often the most practical replacement strategy\nOur brain’s limitations are similar to computer caches\nManaging our attention and focus requires understanding these limitations"
+    "text": "Key Takeaways\n\n\nCaching is a universal concept that applies to computers, organizations, and human cognition\nEfficient cache management requires strategic decisions about what to keep and what to remove\nLRU (Least Recently Used) is often the most practical replacement strategy\nOur brain’s limitations are similar to computer caches\nManaging our attention and focus requires understanding these limitations",
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-    "text": "Summary Quiz\nQuestion: Take a moment to reflect:\n\n\nWhat are the three main types of cache replacement strategies?\nHow does the library principle relate to computer memory hierarchy?\nWhat are two ways you can apply caching principles to improve your productivity?\nHow can understanding cache flooding help protect against information overload?"
+    "text": "Summary Quiz\nQuestion: Take a moment to reflect:\n\n\nWhat are the three main types of cache replacement strategies?\nHow does the library principle relate to computer memory hierarchy?\nWhat are two ways you can apply caching principles to improve your productivity?\nHow can understanding cache flooding help protect against information overload?",
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     "section": "Interesting literature to start",
-    "text": "Interesting literature to start\n\nChristian, B., & Griffiths, T. (2016). Algorithms to live by: the computer science of human decisions. First international edition. New York, Henry Holt and Company.1\nFerguson, T.S. (1989) ‘Who solved the secretary problem?’, Statistical Science, 4(3). doi:10.1214/ss/1177012493."
+    "text": "Interesting literature to start\n\nChristian, B., & Griffiths, T. (2016). Algorithms to live by: the computer science of human decisions. First international edition. New York, Henry Holt and Company.1\nFerguson, T.S. (1989) ‘Who solved the secretary problem?’, Statistical Science, 4(3). doi:10.1214/ss/1177012493.",
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     "section": "Books on Programming",
-    "text": "Books on Programming\n\nDowney, A. B. (2024). Think Python: How to think like a computer scientist (Third edition). O’Reilly. Here\nElter, S. (2021). Schrödinger programmiert Python: Das etwas andere Fachbuch (1. Auflage). Rheinwerk Verlag.\n\n. . .\n\n\n\n\n\n\nNote\n\n\n\nThink Python is a great book to start with. It’s available online for free. Schrödinger Programmiert Python is a great alternative for German students, as it is a very playful introduction to programming with lots of examples."
+    "text": "Books on Programming\n\nDowney, A. B. (2024). Think Python: How to think like a computer scientist (Third edition). O’Reilly. Here\nElter, S. (2021). Schrödinger programmiert Python: Das etwas andere Fachbuch (1. Auflage). Rheinwerk Verlag.\n\n. . .\n\n\n\n\n\n\nNote\n\n\n\nThink Python is a great book to start with. It’s available online for free. Schrödinger Programmiert Python is a great alternative for German students, as it is a very playful introduction to programming with lots of examples.",
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     "section": "More Literature",
-    "text": "More Literature\nFor more interesting literature, take a look at the literature list of this course."
+    "text": "More Literature\nFor more interesting literature, take a look at the literature list of this course.",
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-    "text": "Footnotes\n\n\nThe main inspiration for this lecture. Nils and I have read it and discussed it in depth, always wanting to translate it into a course.↩︎"
+    "text": "Footnotes\n\n\nThe main inspiration for this lecture. Nils and I have read it and discussed it in depth, always wanting to translate it into a course.↩︎",
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@@ -3067,48 +3279,76 @@
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     "section": "",
-    "text": "Imagine you’re a librarian who needs to organize and retrieve books efficiently. Instead of explaining every step of finding a book each time, wouldn’t it be nice to have a set of standard procedures? In programming, these procedures are called functions! They help us organize our code into reusable blocks, just like having standard procedures in a library.\nThis tutorial will teach you about functions using a library management system and a coffee machine as an example. We’ll create functions to help us manage books, track their popularity, and implement a simple caching system.\n\n\n\n\n\n\nReal-World Example\n\n\n\nThink of a function like a coffee machine:\n\nInput (parameters) → Coffee beans, water, settings\nProcess → Internal brewing steps\nOutput (return value) → Your finished coffee"
+    "text": "Imagine you’re a librarian who needs to organize and retrieve books efficiently. Instead of explaining every step of finding a book each time, wouldn’t it be nice to have a set of standard procedures? In programming, these procedures are called functions! They help us organize our code into reusable blocks, just like having standard procedures in a library.\nThis tutorial will teach you about functions using a library management system and a coffee machine as an example. We’ll create functions to help us manage books, track their popularity, and implement a simple caching system.\n\n\n\n\n\n\nReal-World Example\n\n\n\nThink of a function like a coffee machine:\n\nInput (parameters) → Coffee beans, water, settings\nProcess → Internal brewing steps\nOutput (return value) → Your finished coffee",
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     "title": "Tutorial III.II - Functions",
     "section": "Exercise 1.1 - Create a Book Information Function",
-    "text": "Exercise 1.1 - Create a Book Information Function\nCreate a function called get_book_info that takes three parameters: title, author, and year. It should return a formatted string with the book’s information.\n\n\n\n\n\n\nBefore You Start\n\n\n\nCommon mistakes to avoid:\n\nDon’t forget the spaces in the formatting\nRemember to use f-strings for easy string formatting\nMake sure to include the parentheses around the year\n\n\n\n\n# If you call the function like this:\n# get_book_info(\"Return\", \"Alan Wake\", 2023)\n# it should return the string:\n# \"Return by Alan Wake (2023)\"\n# YOUR CODE BELOW\n\n\n\nCode\n# Assertions to verify your solution\nassert get_book_info(\"1984\", \"George Orwell\", 1949) == \"1984 by George Orwell (1949)\"\nprint(\"Great job! Your book information function works as expected!\")"
+    "text": "Exercise 1.1 - Create a Book Information Function\nCreate a function called get_book_info that takes three parameters: title, author, and year. It should return a formatted string with the book’s information.\n\n\n\n\n\n\nBefore You Start\n\n\n\nCommon mistakes to avoid:\n\nDon’t forget the spaces in the formatting\nRemember to use f-strings for easy string formatting\nMake sure to include the parentheses around the year\n\n\n\n\n# If you call the function like this:\n# get_book_info(\"Return\", \"Alan Wake\", 2023)\n# it should return the string:\n# \"Return by Alan Wake (2023)\"\n# YOUR CODE BELOW\n\n\n\nCode\n# Assertions to verify your solution\nassert get_book_info(\"1984\", \"George Orwell\", 1949) == \"1984 by George Orwell (1949)\"\nprint(\"Great job! Your book information function works as expected!\")",
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-    "text": "Common Pitfall\nWhen using multiple conditions, be careful with the order of operations. Consider using parentheses to make your logic clear:\nif (copies_available > 0) and (not on_hold):  # More readable than the code above"
+    "text": "Common Pitfall\nWhen using multiple conditions, be careful with the order of operations. Consider using parentheses to make your logic clear:\nif (copies_available > 0) and (not on_hold):  # More readable than the code above",
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     "title": "Tutorial III.II - Functions",
     "section": "Exercise 2.1 - Create a Function to Check if a Book is Popular",
-    "text": "Exercise 2.1 - Create a Function to Check if a Book is Popular\nCreate a function called is_popular that takes a single parameter rating. If the rating is greater than 3, it should return True, otherwise it should return False.\n\n# YOUR CODE BELOW\n\n\n\nCode\n# Assertions to verify your solution\nassert is_popular(4) == True, \"A rating of 4 or higher is considered popular\"\nassert is_popular(2) == False, \"A rating of 3 or lower is not popular\"\nprint(\"Excellent! Your popular book function works correctly!\")"
+    "text": "Exercise 2.1 - Create a Function to Check if a Book is Popular\nCreate a function called is_popular that takes a single parameter rating. If the rating is greater than 3, it should return True, otherwise it should return False.\n\n# YOUR CODE BELOW\n\n\n\nCode\n# Assertions to verify your solution\nassert is_popular(4) == True, \"A rating of 4 or higher is considered popular\"\nassert is_popular(2) == False, \"A rating of 3 or lower is not popular\"\nprint(\"Excellent! Your popular book function works correctly!\")",
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     "section": "Exercise 2.2 - Create a Book Access Function",
-    "text": "Exercise 2.2 - Create a Book Access Function\nMany libraries have borrowing policies that depend on multiple factors. Let’s implement a realistic borrowing policy function that a library might use. Create a function called can_borrow_book that takes three parameters:\n\nis_member: boolean indicating if the person is a library member\nbooks_borrowed: number of books currently borrowed\nhas_overdue: boolean indicating if they have overdue books\n\nThe function should return True only if:\n\nThey are a member AND\nThey have borrowed less than 3 books AND\nThey have no overdue books\n\n\n# YOUR CODE BELOW\n\n\n\nCode\n# Assertions to verify your solution\nassert can_borrow_book(True, 2, False) == True \"Should allow borrowing\"\nassert can_borrow_book(True, 3, False) == False, \"Should not allow more than 3 books\"\nassert can_borrow_book(True, 1, True) == False, \"Should not allow with overdue books\"\nprint(\"Excellent! Your borrowing function works as it should!\")"
+    "text": "Exercise 2.2 - Create a Book Access Function\nMany libraries have borrowing policies that depend on multiple factors. Let’s implement a realistic borrowing policy function that a library might use. Create a function called can_borrow_book that takes three parameters:\n\nis_member: boolean indicating if the person is a library member\nbooks_borrowed: number of books currently borrowed\nhas_overdue: boolean indicating if they have overdue books\n\nThe function should return True only if:\n\nThey are a member AND\nThey have borrowed less than 3 books AND\nThey have no overdue books\n\n\n# YOUR CODE BELOW\n\n\n\nCode\n# Assertions to verify your solution\nassert can_borrow_book(True, 2, False) == True \"Should allow borrowing\"\nassert can_borrow_book(True, 3, False) == False, \"Should not allow more than 3 books\"\nassert can_borrow_book(True, 1, True) == False, \"Should not allow with overdue books\"\nprint(\"Excellent! Your borrowing function works as it should!\")",
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     "title": "Tutorial III.II - Functions",
     "section": "Exercise 3.1 - Create a Cache Priority Function",
-    "text": "Exercise 3.1 - Create a Cache Priority Function\nCreate a function called calculate_cache_priority that helps decide if a book should be kept in the easily accessible section. It should take:\n\ntimes_borrowed: How many times the book was borrowed\ndays_since_last_borrow: Days since last borrowed\nis_reference: Whether it’s a reference book (default: False)\n\nReturn a priority score calculated as:\n\nFor regular books: times_borrowed / (days_since_last_borrow + 1)\nFor reference books: 2 * (times_borrowed / (days_since_last_borrow + 1))\n\n\n# YOUR CODE BELOW\n\n\n\nCode\n# Test your answer\nassert calculate_cache_priority(10, 5) == 10/(5+1), \"Check your regular book calculation\"\nassert calculate_cache_priority(10, 5, True) == 2*(10/(5+1)), \"Check your reference book calculation\"\nprint(\"Great! Your cache priority function works and calculates correctly!\")"
+    "text": "Exercise 3.1 - Create a Cache Priority Function\nCreate a function called calculate_cache_priority that helps decide if a book should be kept in the easily accessible section. It should take:\n\ntimes_borrowed: How many times the book was borrowed\ndays_since_last_borrow: Days since last borrowed\nis_reference: Whether it’s a reference book (default: False)\n\nReturn a priority score calculated as:\n\nFor regular books: times_borrowed / (days_since_last_borrow + 1)\nFor reference books: 2 * (times_borrowed / (days_since_last_borrow + 1))\n\n\n# YOUR CODE BELOW\n\n\n\nCode\n# Test your answer\nassert calculate_cache_priority(10, 5) == 10/(5+1), \"Check your regular book calculation\"\nassert calculate_cache_priority(10, 5, True) == 2*(10/(5+1)), \"Check your reference book calculation\"\nprint(\"Great! Your cache priority function works and calculates correctly!\")",
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     "title": "Tutorial III.II - Functions",
     "section": "Exercise 4.1 - Working with String Methods and Functions",
-    "text": "Exercise 4.1 - Working with String Methods and Functions\nCreate a function called format_book_title that takes a book title as input and:\n\nCapitalizes the first letter of each word\nRemoves any extra whitespace\nReturns the formatted title\n\n\n\n\n\n\n\nCommon String Methods\n\n\n\n\n.strip() - Removes whitespace from start and end\n.title() - Capitalizes first letter of each word\n.lower() - Converts to lowercase\n.upper() - Converts to uppercase\n\n\n\n\n# YOUR CODE BELOW\n\n\n\nCode\n# Test your answer\nassert format_book_title(\"  the hitchhikers guide  \") == \"The Hitchhikers Guide\", \"Check your whitespace removal\"\nassert format_book_title(\"dune\") == \"Dune\", \"Check your capitalization\"\nprint(\"Excellent! Your title formatting function works correctly!\")"
+    "text": "Exercise 4.1 - Working with String Methods and Functions\nCreate a function called format_book_title that takes a book title as input and:\n\nCapitalizes the first letter of each word\nRemoves any extra whitespace\nReturns the formatted title\n\n\n\n\n\n\n\nCommon String Methods\n\n\n\n\n.strip() - Removes whitespace from start and end\n.title() - Capitalizes first letter of each word\n.lower() - Converts to lowercase\n.upper() - Converts to uppercase\n\n\n\n\n# YOUR CODE BELOW\n\n\n\nCode\n# Test your answer\nassert format_book_title(\"  the hitchhikers guide  \") == \"The Hitchhikers Guide\", \"Check your whitespace removal\"\nassert format_book_title(\"dune\") == \"Dune\", \"Check your capitalization\"\nprint(\"Excellent! Your title formatting function works correctly!\")",
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 ]
\ No newline at end of file