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data-md-component=navigation > <div class=md-sidebar__scrollwrap > <div class=md-sidebar__inner > <nav class="md-nav md-nav--primary" data-md-level=0 > <label class="md-nav__title md-nav__title--site" for=__drawer > <a href=index.html  title="Practical Data Science" class="md-nav__button md-logo"> <img src="_static/mids_logo.svg" alt=" logo" width=48  height=48 > </a> <a href=index.html  title="Practical Data Science">Practical Data Science</a> </label> <ul class=md-nav__list > <li class=md-nav__item > <input class="md-toggle md-nav__toggle" data-md-toggle=toc  type=checkbox  id=__toc > <label class="md-nav__link md-nav__link--active" for=__toc > Class Schedule </label> <a href="#" class="md-nav__link md-nav__link--active">Class Schedule</a> <nav class="md-nav md-nav--secondary"> <label class=md-nav__title  for=__toc >"Contents"</label> <ul class=md-nav__list  data-md-scrollfix=""> <li class=md-nav__item ><a href="#class-schedule--page-root" class=md-nav__link >Class Schedule</a><nav class=md-nav > <ul class=md-nav__list > <li class=md-nav__item ><a href="#office-hours-and-links" class=md-nav__link >Office Hours and Links</a> <li class=md-nav__item ><a href="#class-time" class=md-nav__link >Class Time</a> </ul> </nav> </ul> </nav> <li class=md-nav__item > <a href=autograder_guidelines.html  class=md-nav__link >Autograder Guidelines</a> <li class=md-nav__item > <a href=not_a_mids_student.html  class=md-nav__link >Not a MIDS Student?</a> </ul> </nav> </div> </div> </div> <div class="md-sidebar md-sidebar--secondary" data-md-component=toc > <div class=md-sidebar__scrollwrap > <div class=md-sidebar__inner > <nav class="md-nav md-nav--secondary"> <label class=md-nav__title  for=__toc >"Contents"</label> <ul class=md-nav__list  data-md-scrollfix=""> <li class=md-nav__item ><a href="#class-schedule--page-root" class=md-nav__link >Class Schedule</a><nav class=md-nav > <ul class=md-nav__list > <li class=md-nav__item ><a href="#office-hours-and-links" class=md-nav__link >Office Hours and Links</a> <li class=md-nav__item ><a href="#class-time" class=md-nav__link >Class Time</a> </ul> </nav> </ul> </nav> </div> </div> </div> <div class=md-content > <article class="md-content__inner md-typeset" role=main > <section id=class-schedule > <h1 id=class-schedule--page-root >Class Schedule<a class=headerlink  href="#class-schedule--page-root" title="Permalink to this headline">¶</a></h1> <section id=office-hours-and-links > <h2 id=office-hours-and-links >Office Hours and Links<a class=headerlink  href="#office-hours-and-links" title="Permalink to this headline">¶</a></h2> <p><a class="reference external" href="https://duke.zoom.us/my/nickeubank">Nick</a> : Thursday 10 am - 11 am</p> <p><a class="reference external" href="https://duke.zoom.us/j/6897746818">Pomelo</a> Tuesday, 5pm - 6pm</p> <p><a class="reference external" href="https://duke.zoom.us/j/7110197485">Suzy</a>: Wednesday, 12 pm - 1pm</p> </section> <section id=class-time > <h2 id=class-time >Class Time<a class=headerlink  href="#class-time" title="Permalink to this headline">¶</a></h2> <p>Class will be Tuesdays and Thursdays from 1:25pm-2:40pm (EDT).</p> <table> <colgroup> <col style="width: 18%"/> <col style="width: 35%"/> <col style="width: 41%"/> <col style="width: 6%"/> <thead> <tr class=row-odd ><th class=head ><p>Date, Rm</p> <th class=head ><p>Topic</p> <th class=head ><p>Do Before Class</p> <th class=head ><p>In-Class Exercise</p> <tr class=row-even ><td><p>Tues, Aug 29</p> <td><ul class=simple > <li><p>Class Introduction</p> <li><p>Welcome to VS Code</p> </ul> <td><ul class=simple > <li><p><strong>SETUP 1:</strong> <a class="reference external" href="https://nickeubank.github.io/practicaldatascience_book/notebooks/PDS_not_yet_in_coursera/00_setup_env/setup_python.html">Installing Python and miniconda</a></p> <li><p><strong>SETUP 2:</strong> <a class="reference external" href="https://nickeubank.github.io/practicaldatascience_book/notebooks/PDS_not_yet_in_coursera/00_setup_env/setup_vscode.html">Installing and Configuring VS Code</a></p> <li><p><a class="reference external" href="https://nickeubank.github.io/practicaldatascience_book/notebooks/PDS_not_yet_in_coursera/99_advice/llms.html">chatGPT and You</a></p> </ul> <td> <tr class=row-odd ><td><p>Thurs, Aug 31</p> <td><ul class=simple > <li><p>Command Line Basics</p> </ul> <td><ul class=simple > <li><p><strong>SETUP 3:</strong> <a class="reference external" href="https://nickeubank.github.io/practicaldatascience_book/notebooks/PDS_not_yet_in_coursera/00_setup_env/setup_augmented_commandline.html">Setup Augmented Command Line</a></p> <li><p><a class="reference external" href="https://nickeubank.github.io/practicaldatascience_book/notebooks/PDS_not_yet_in_coursera/10_commandline/commandline_part1.html">Command Line Basics</a></p> <li><p><a class="reference external" href="https://github.com/nickeubank/practicaldatascience/raw/master/syllabus/Syllabus_PracticalDataScience.pdf">Read and sign syllabus</a></p> <li><p><a class="reference external" href="https://uma.pop.umn.edu/usa/user/new">Register with IPUMS</a></p> <li><p><a class="reference external" href="https://www.datacamp.com/home">Register for DataCamp</a></p> </ul> <td><ul class=simple > <li><p><a class="reference internal" href="exercises/Exercise_CommandLine_1_Basics.html"><span class=doc >Ex</span></a></p> </ul> <tr class=row-even ><td><p>Fri, Sep 1</p> <td><p><strong>SOFTWARE INSTALL DAY</strong></p> <td><p>A day of trouble shooting install issues</p> <td> <tr class=row-odd ><td><p>Tues, Sep 5</p> <td><ul class=simple > <li><p>Advanced Command Line</p> <li><p>Git</p> <li><p>Packages</p> </ul> <td><ul class=simple > <li><p><a class="reference external" href="https://nickeubank.github.io/practicaldatascience_book/notebooks/PDS_not_yet_in_coursera/10_commandline/commandline_part2.html">Advanced Command Line</a></p> <li><p><a class="reference external" href="https://nickeubank.github.io/practicaldatascience_book/notebooks/class_2/week_4/30_managing_python_packages.html">Python packages</a></p> <li><p><a class="reference internal" href=git_and_github.html ><span class=doc >Git and Github</span></a></p> <li><p><a class="reference external" href="https://learngitbranching.js.org/">Visualize Git Branches</a></p> </ul> <td><ul class=simple > <li><p><a class="reference internal" href="exercises/Exercise_CommandLine_2_Advanced.html"><span class=doc >Ex 1</span></a></p> <li><p><a class="reference internal" href="exercises/Exercise_git.html"><span class=doc >Ex 2</span></a></p> </ul> <tr class=row-even ><td><p>Thurs, Sep 7</p> <td><ul class=simple > <li><p>Git Continued</p> <li><p>Jupyter</p> </ul> <td><ul class=simple > <li><p>Oopsie Resource: <a class="reference external" href="https://ohshitgit.com/">Oh 💩, Git!</a></p> <li><p><a class="reference external" href="https://xkcd.com/1597/">The secret of git</a></p> <li><p><strong>SETUP 4:</strong> <a class="reference external" href="https://nickeubank.github.io/practicaldatascience_book/notebooks/PDS_not_yet_in_coursera/00_setup_env/jupyter_in_vscode.html">Jupyter in VS Code</a></p> <li><p><strong>OPTIONAL SETUP:</strong> <a class="reference external" href="https://nickeubank.github.io/practicaldatascience_book/notebooks/PDS_not_yet_in_coursera/00_setup_env/jupyter_r_notebooks.html">R Jupyter Notebooks</a></p> </ul> <td><ul class=simple > <li><p><a class="reference internal" href="exercises/Exercise_jupytervscode.html"><span class=doc >Ex 1</span></a></p> <li><p><a class="reference internal" href="exercises/Exercise_git_2.html"><span class=doc >Ex 2</span></a></p> </ul> <tr class=row-odd ><td><p>Tues, Sep 12</p> <td><ul class=simple > <li><p>Python Debugger</p> <li><p>R / Python Differences</p> <li><p>Packages</p> </ul> <td><ul class=simple > <li><p><a class="reference external" href="https://www.youtube.com/watch?v=JD8BrXXNtjA">What are Tracebacks?</a></p> <li><p><a class="reference external" href="https://nickeubank.github.io/practicaldatascience_book/notebooks/PDS_not_yet_in_coursera/20_programming_concepts/10_debugging_principles.html">Debugging Tools</a></p> <li><p><a class="reference external" href="https://nickeubank.github.io/practicaldatascience_book/notebooks/PDS_not_yet_in_coursera/20_programming_concepts/20_debugging_in_vscode.html">Python Debugger in VS Code</a></p> <li><p><a class="reference external" href="https://nickeubank.github.io/practicaldatascience_book/notebooks/PDS_not_yet_in_coursera/20_programming_concepts/vars_v_objects.html">variables v objects</a></p> <li><p><a class="reference external" href="https://nickeubank.github.io/practicaldatascience_book/notebooks/PDS_not_yet_in_coursera/20_programming_concepts/python_v_r.html">Python v. R</a></p> </ul> <td><ul class=simple > <li><p><a class="reference internal" href="exercises/Exercise_debugger.html"><span class=doc >Ex 1</span></a></p> <li><p><a class="reference internal" href="exercises/Exercise_variables_v_objects.html"><span class=doc >Ex 2</span></a></p> </ul> <tr class=row-even ><td><p>Thurs, Sep 14</p> <td><ul class=simple > <li><p>Numpy Basics</p> </ul> <td><ul class=simple > <li><p><a class="reference external" href="https://nickeubank.github.io/practicaldatascience_book/notebooks/class_2/week_2/10_why_numpy.html">Why numpy? through Vector Subsetting Recap, SKIP Speed/Ease of Use Tradeoff and Vectorization</a></p> </ul> <td><ul class=simple > <li><p><a class="reference internal" href="exercises/Exercise_numpy_vectors.html"><span class=doc >Ex 1</span></a></p> </ul> <tr class=row-odd ><td><p>Tues, Sep 19</p> <td><ul class=simple > <li><p>Numpy Arrays</p> </ul> <td><p><strong>More Numpy Concepts:</strong></p> <ul class=simple > <li><p><a class="reference external" href="https://nickeubank.github.io/practicaldatascience_book/notebooks/class_2/week_3/10_views_and_copies.html">Views and Copies</a></p> <li><p><a class="reference external" href="https://nickeubank.github.io/practicaldatascience_book/notebooks/class_2/week_3/11_when_do_I_get_a_view.html">When Do I Get a View</a></p> <li><p><a class="reference external" href="https://nickeubank.github.io/practicaldatascience_book/notebooks/class_2/week_3/13_objects_and_variables.html">Variables, Objects, and Numpy</a></p> <li><p><a class="reference external" href="https://nickeubank.github.io/practicaldatascience_book/notebooks/class_2/week_3/12_views_and_copies_recap.html">Views and Copies Recap</a></p> <li><p><a class="reference external" href="https://nickeubank.github.io/practicaldatascience_book/notebooks/PDS_not_yet_in_coursera/20_programming_concepts/ints_and_floats.html">Numbers in Computer</a></p> </ul> <p><strong>Matrices:</strong></p> <ul class=simple > <li><p><a class="reference external" href="https://nickeubank.github.io/practicaldatascience_book/notebooks/class_2/week_3/00_welcome_to_week_3.html">Matrices — From Welcome through Review of Matrices</a> (<em>see navigation bar on left</em>)</p> </ul> <p><strong>ND Arrays:</strong></p> <ul class=simple > <li><p><a class="reference external" href="https://nickeubank.github.io/practicaldatascience_book/notebooks/class_2/week_3/40_nd_arrays.html">Arrays — From Welcome through Color Images as Arrays</a> (<em>see navigation bar on left</em>)</p> </ul> <td><ul class=simple > <li><p><a class="reference internal" href="exercises/Exercise_numpy_viewcopies.html"><span class=doc >Link</span></a></p> </ul> <tr class=row-even ><td><p>Thurs, Sep 21</p> <td><ul class=simple > <li><p>Pandas: Series</p> </ul> <td><ul class=simple > <li><p><a class="reference external" href="https://nickeubank.github.io/practicaldatascience_book/notebooks/class_2/week_4/10_speed_and_ease_of_use.html">Speed / Ease of Use Tradeoff</a></p> <li><p><a class="reference external" href="https://nickeubank.github.io/practicaldatascience_book/notebooks/class_2/week_4/11_vectorization.html">Vectorization</a></p> <li><p><a class="reference external" href="https://nickeubank.github.io/practicaldatascience_book/notebooks/class_3/week_2/00_intro_to_pandas.html">Pandas: From Working with Tabular Data through Subsetting and Indexing with Single Square Brackets</a></p> </ul> <td><ul class=simple > <li><p><a class="reference internal" href="exercises/Exercise_series.html"><span class=doc >Link</span></a></p> </ul> <tr class=row-odd ><td><p>Tues, Sep 26</p> <td><ul class=simple > <li><p>Pandas: DataFrames</p> </ul> <td><ul class=simple > <li><p><a class="reference external" href="https://nickeubank.github.io/practicaldatascience_book/notebooks/class_3/week_2/30_pandas_dataframes.html">Pandas DataFrames</a></p> <li><p><a class="reference external" href="https://nickeubank.github.io/practicaldatascience_book/notebooks/class_3/week_2/35_pandas_dataframe_gotchas.html">Pandas DataFrame Gotchas</a></p> <li><p><a class="reference external" href="https://nickeubank.github.io/practicaldatascience_book/notebooks/class_3/week_2/50_pandas_pyarrow.html">PyArrow Backend</a></p> </ul> <td><ul class=simple > <li><p><a class="reference internal" href="exercises/Exercise_dataframes.html"><span class=doc >Link</span></a></p> </ul> <tr class=row-even ><td><p>Thurs, Sep 28</p> <td><ul class=simple > <li><p>Pandas: Indices &amp; Missing</p> </ul> <td><ul class=simple > <li><p>WM pp 136-142 (Indices, Section 5.2 up to MultiIndexes)</p> <li><p><a class="reference external" href="https://jakevdp.github.io/PythonDataScienceHandbook/03.04-missing-values.html">Handling Missing Data</a></p> <li><p><a class="reference external" href="https://nickeubank.github.io/practicaldatascience_book/notebooks/class_3/week_3/10_views_and_copies_numpy_review.html">Views and Copies in Pandas through the View/Copy Headache without CoW</a></p> <li><p><a class="reference external" href="https://nickeubank.github.io/practicaldatascience_book/notebooks/class_3/week_2/50_pandas_pyarrow.html">If you didn’t read Tuesday: PyArrow Backend</a></p> </ul> <td><ul class=simple > <li><p><a class="reference internal" href="exercises/Exercise_indices.html"><span class=doc >Link 1</span></a></p> <li><p><a class="reference internal" href="exercises/Exercise_missing.html"><span class=doc >Link 2</span></a></p> </ul> <tr class=row-odd ><td><p>Tues, Oct 3</p> <td><ul class=simple > <li><p>Pandas: Cleaning</p> <li><p>Tracebacks</p> </ul> <td><ul class=simple > <li><p><a class="reference external" href="https://nickeubank.github.io/practicaldatascience_book/notebooks/class_3/week_3/00_plaintext_files.html">Reading and Writing Data (plaintext AND binary)</a></p> <li><p><a class="reference external" href="https://nickeubank.github.io/practicaldatascience_book/notebooks/class_3/week_3/20_cleaning_identifying.html">Data Cleaning (through the missing data subsection on left side bar)</a></p> <li><p><a class="reference external" href="https://realpython.com/python-data-types/#strings">Python Strings (string section only!)</a></p> </ul> <td><ul class=simple > <li><p><a class="reference internal" href="exercises/Exercise_cleaning.html"><span class=doc >Link</span></a></p> </ul> <tr class=row-even ><td><p>Thurs, Oct 5</p> <td><ul class=simple > <li><p>Merging</p> </ul> <td><ul class=simple > <li><p><a class="reference external" href="https://nickeubank.github.io/practicaldatascience_book/notebooks/class_3/week_4/00_intro_to_querying_data.html">Data Manipulations, Concatenating and Merging (NOT grouping or querying subsections on left navigation)</a></p> </ul> <td><ul class=simple > <li><p><a class="reference internal" href="exercises/Exercise_merging.html"><span class=doc >Link</span></a></p> </ul> <tr class=row-odd ><td><p>Tues, Oct 10</p> <td><ul class=simple > <li><p>Plotting</p> </ul> <td><ul class=simple > <li><p><a class="reference external" href="https://nickeubank.github.io/practicaldatascience_book/notebooks/class_5/week_2/10_plotting_in_python.html">Plotting in Python through seaborn and Grammer of Graphics</a></p> </ul> <td><ul class=simple > <li><p><a class="reference internal" href="exercises/Exercise_plotting_part1.html"><span class=doc >Link</span></a></p> </ul> <tr class=row-even ><td><p>Thurs, Oct 12</p> <td><p><strong>FALL BREAK</strong></p> <td> <td> <tr class=row-odd ><td><p>Tues, Oct 17</p> <td><p><strong>FALL BREAK</strong></p> <td> <td> <tr class=row-even ><td><p>Thurs, Oct 19</p> <td><ul class=simple > <li><p>Plotting</p> </ul> <td><ul class=simple > <li><p><a class="reference external" href="https://nickeubank.github.io/practicaldatascience_book/notebooks/class_5/week_5/45_plotting_with_matplotlib.html">Matplotlib</a></p> <li><p><a class="reference external" href="https://nickeubank.github.io/practicaldatascience_book/notebooks/class_5/week_5/46_making_plots_pretty.html">Making Pretty Plots</a></p> <li><p><a class="reference external" href="https://seaborn.pydata.org/generated/seaborn.objects.Plot.on.html">Convert seaborn.objects to matplotlib axes</a></p> </ul> <td><ul class=simple > <li><p><a class="reference internal" href="exercises/Exercise_plotting_part2.html"><span class=doc >Link</span></a></p> </ul> <tr class=row-odd ><td><p>Tues, Oct 24</p> <td><ul class=simple > <li><p>Big Data: What is it, how do I work with it?</p> </ul> <td><ul class=simple > <li><p><a class="reference external" href="https://nickeubank.github.io/practicaldatascience_book/notebooks/PDS_not_yet_in_coursera/30_big_data/10_big_data_what_is_it.html">What is Big Data?</a></p> <li><p><a class="reference external" href="https://nickeubank.github.io/practicaldatascience_book/notebooks/PDS_not_yet_in_coursera/30_big_data/20_big_data_strategies.html">Strategies for Big Data</a></p> <li><p>Download the dataset linked at the top of the linked exercise before class.</p> <li><p><a class="reference external" href="https://nickeubank.github.io/practicaldatascience_book/notebooks/PDS_not_yet_in_coursera/30_big_data/30_parquet.html">Parquet Format</a></p> </ul> <td><ul class=simple > <li><p><a class="reference internal" href="exercises/Exercise_bigdata.html"><span class=doc >Ex</span></a></p> </ul> <tr class=row-even ><td><p>Thurs, Oct 26</p> <td><ul class=simple > <li><p>Defensive Programming</p> <li><p>Workflow</p> <li><p>Backwards Design</p> <li><p>Getting Help Online</p> </ul> <td><ul class=simple > <li><p><a class="reference external" href="https://nickeubank.github.io/practicaldatascience_book/notebooks/PDS_not_yet_in_coursera/20_programming_concepts/workflow.html">Workflow Management</a></p> <li><p><a class="reference external" href="https://nickeubank.github.io/practicaldatascience_book/notebooks/PDS_not_yet_in_coursera/20_programming_concepts/backwards_design.html">Backwards Design</a></p> <li><p><a class="reference external" href="https://nickeubank.github.io/practicaldatascience_book/notebooks/PDS_not_yet_in_coursera/20_programming_concepts/getting_help.html">Getting Help</a></p> <li><p><a class="reference external" href="https://github.com/nickeubank/practicaldatascience/blob/master/opioid_project/PDS_ProjectSummary.pdf">Opioid Project</a></p> </ul> <td> <tr class=row-odd ><td><p>Tues, Oct 31</p> <td><ul class=simple > <li><p>Defensive Programming</p> <li><p>Groupby / Split-Apply-Combine</p> </ul> <td><ul class=simple > <li><p><a class="reference external" href="https://nickeubank.github.io/practicaldatascience_book/notebooks/PDS_not_yet_in_coursera/20_programming_concepts/defensive_programming.html">Defensive Programming</a></p> <li><p><a class="reference external" href="https://nickeubank.github.io/practicaldatascience_book/notebooks/PDS_not_yet_in_coursera/20_programming_concepts/iceberg_principle.html">Iceberg Principle</a></p> <li><p><a class="reference external" href="https://nickeubank.github.io/practicaldatascience_book/notebooks/class_3/week_4/20_grouping.html">Groupby</a></p> <li><p>WM pp Chpt 10, 10.1, 10.2, 10.3</p> </ul> <td><ul class=simple > <li><p><a class="reference internal" href="exercises/Exercise_groupby.html"><span class=doc >Link</span></a></p> </ul> <tr class=row-even ><td><p>Thurs, Nov 2</p> <td><ul class=simple > <li><p>Pandas: Reshaping</p> <li><p>Pandas: Categoricals</p> </ul> <td><ul class=simple > <li><p>WM 8.3</p> <li><p><a class="reference external" href="https://pandas.pydata.org/pandas-docs/stable/user_guide/reshaping.html">Pandas reshaping (with pics!)</a></p> <li><p><a class="reference external" href="http://vita.had.co.nz/papers/tidy-data.html">What is goal of reshaping?</a></p> <li><p>Categoricals: WM 12.1</p> </ul> <td><ul class=simple > <li><p><a class="reference internal" href="exercises/Exercise_reshaping.html"><span class=doc >Link</span></a></p> </ul> <tr class=row-odd ><td><p>Tues, Nov 7</p> <td><ul class=simple > <li><p>Speed and Performance in Python</p> </ul> <td><ul class=simple > <li><p><a class="reference external" href="https://nickeubank.github.io/practicaldatascience_book/notebooks/class_2/week_4/10_speed_and_ease_of_use.html">Understanding Performance</a></p> <li><p><a class="reference external" href="https://nickeubank.github.io/practicaldatascience_book/notebooks/PDS_not_yet_in_coursera/30_big_data/50_performance_solutions.html">Improving Performance</a></p> <li><p><a class="reference external" href="https://nickeubank.github.io/practicaldatascience_book/notebooks/PDS_not_yet_in_coursera/object_vectors.html">Object dtypes</a></p> <li><p><a class="reference external" href="https://nickeubank.github.io/practicaldatascience_book/notebooks/PDS_not_yet_in_coursera/20_programming_concepts/pr_review.html">Code Reviews</a></p> <li><p><strong>Project Strategy Plan Due</strong></p> </ul> <td> <tr class=row-even ><td><p>Thurs, Nov 9</p> <td><ul class=simple > <li><p>Statistics with statsmodels</p> </ul> <td><ul class=simple > <li><p>WM, 3rd Edition, Chapter 12, 12.1, 12.2, 12.3 (Patsy and statsmodels, not scikit-learn)</p> <li><p><a class="reference external" href="https://www.statsmodels.org/stable/regression.html">Skim “Linear Models”</a></p> <li><p><a class="reference external" href="https://www.statsmodels.org/stable/discretemod.html">Skim “Discrete Dep Var Models”</a></p> <li><p><a class="reference external" href="https://www.statsmodels.org/stable/examples/notebooks/generated/regression_diagnostics.html">Regression Diagnostics</a></p> <li><p><a class="reference external" href="https://www.statsmodels.org/stable/examples/notebooks/generated/regression_plots.html">Regression Plots</a></p> <li><p><a class="reference external" href="https://patsy.readthedocs.io/en/latest/R-comparison.html">Patsy: Differences from R</a></p> </ul> <td><ul class=simple > <li><p><a class="reference internal" href="exercises/Exercise_statsmodels.html"><span class=doc >Link</span></a></p> </ul> <tr class=row-odd ><td><p>Tues, Nov 14</p> <td><ul class=simple > <li><p>Machine Learning with sckikit-learn</p> </ul> <td><ul class=simple > <li><p>JVP Chapter 5 up to “Hyperparameters and Model Validation” Section (pp 331 - 359)</p> </ul> <td> <tr class=row-even ><td><p>Thurs, Nov 16</p> <td><ul class=simple > <li><p>Defining Your Own Estimators</p> <li><p>Regex</p> </ul> <td><ul class=simple > <li><p>Review linear regression as matrix manipulations. <a class="reference external" href="https://www.stat.purdue.edu/~boli/stat512/lectures/topic3.pdf">Here’s a nice review.</a></p> <li><p><a class="reference external" href="https://realpython.com/python3-object-oriented-programming/">Review how to define classes</a></p> <li><p><a class="reference external" href="https://nickeubank.github.io/practicaldatascience_book/notebooks/class_2/week_3/41_broadcasting.html#a-common-gotcha-narrow-matrices-v-1-dimensional-vectors">Broadcasting Gotchyas</a></p> </ul> <td> <tr class=row-odd ><td><p>Tues, Nov 21</p> <td><p>No Class</p> <td> <td> <tr class=row-even ><td><p>Thurs, Nov 23</p> <td><p>THANKSGIVING</p> <td> <td> <tr class=row-odd ><td><p>Tues, Nov 28</p> <td><ul class=simple > <li><p>Parallelism</p> <li><p>Distributed Computing</p> </ul> <td><ul class=simple > <li><p><a class="reference internal" href=parallelism.html ><span class=doc >Parallel Computing</span></a></p> <li><p><a class="reference internal" href=distributed_computing.html ><span class=doc >Distributed Computing with dask</span></a></p> </ul> <p>(Note reading includes a 45 minute video to watch) <strong>Optional:</strong> - <strong>Opioid Project Rough Draft Due</strong></p> <td> <tr class=row-even ><td><p>Thurs, Nov 30</p> <td> <td> <td> <tr class=row-odd ><td><p>Wed Dec 13</p> <td> <td><p><strong>Final Project Report and Presentation Due</strong></p> <td> </table> </section> </section> </article> </div> </div> </main> </div> <footer class=md-footer > <div class=md-footer-nav > <nav class="md-footer-nav__inner md-grid"> <a href=index.html  title="Hello!" class="md-flex md-footer-nav__link md-footer-nav__link--prev" rel=prev > <div class="md-flex__cell md-flex__cell--shrink"> <i class="md-icon md-icon--arrow-back md-footer-nav__button"></i> </div> <div class="md-flex__cell md-flex__cell--stretch md-footer-nav__title"> <span class=md-flex__ellipsis > <span class=md-footer-nav__direction > "Previous" </span> Hello! </span> </div> </a> <a href=autograder_guidelines.html  title="Guidelines for Using the Gradescope Autograder" class="md-flex md-footer-nav__link 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class=md-nav > <ul class=md-nav__list > <li class=md-nav__item ><a href="#office-hours-and-links" class=md-nav__link >Office Hours and Links</a> <li class=md-nav__item ><a href="#class-time" class=md-nav__link >Class Time</a> </ul> </nav> </ul> </nav> <li class=md-nav__item > <a href=autograder_guidelines.html  class=md-nav__link >Autograder Guidelines</a> <li class=md-nav__item > <a href=not_a_mids_student.html  class=md-nav__link >Not a MIDS Student?</a> </ul> </nav> </div> </div> </div> <div class="md-sidebar md-sidebar--secondary" data-md-component=toc > <div class=md-sidebar__scrollwrap > <div class=md-sidebar__inner > <nav class="md-nav md-nav--secondary"> <label class=md-nav__title  for=__toc >"Contents"</label> <ul class=md-nav__list  data-md-scrollfix=""> <li class=md-nav__item ><a href="#class-schedule--page-root" class=md-nav__link >Class Schedule</a><nav class=md-nav > <ul class=md-nav__list > <li class=md-nav__item ><a href="#office-hours-and-links" class=md-nav__link >Office Hours and Links</a> <li class=md-nav__item ><a href="#class-time" class=md-nav__link >Class Time</a> </ul> </nav> </ul> </nav> </div> </div> </div> <div class=md-content > <article class="md-content__inner md-typeset" role=main > <section id=class-schedule > <h1 id=class-schedule--page-root >Class Schedule<a class=headerlink  href="#class-schedule--page-root" title="Permalink to this headline">¶</a></h1> <section id=office-hours-and-links > <h2 id=office-hours-and-links >Office Hours and Links<a class=headerlink  href="#office-hours-and-links" title="Permalink to this headline">¶</a></h2> <p><a class="reference external" href="https://duke.zoom.us/my/nickeubank">Nick</a> : Thursday 10 am - 11 am</p> <p><a class="reference external" href="https://duke.zoom.us/j/6897746818">Pomelo</a> Tuesday, 5pm - 6pm</p> <p><a class="reference external" href="https://duke.zoom.us/j/7110197485">Suzy</a>: Wednesday, 12 pm - 1pm</p> </section> <section id=class-time > <h2 id=class-time >Class Time<a class=headerlink  href="#class-time" title="Permalink to this headline">¶</a></h2> <p>Class will be Tuesdays and Thursdays from 1:25pm-2:40pm (EDT).</p> <table> <colgroup> <col style="width: 18%"/> <col style="width: 35%"/> <col style="width: 41%"/> <col style="width: 6%"/> <thead> <tr class=row-odd ><th class=head ><p>Date, Rm</p> <th class=head ><p>Topic</p> <th class=head ><p>Do Before Class</p> <th class=head ><p>In-Class Exercise</p> <tr class=row-even ><td><p>Tues, Aug 29</p> <td><ul class=simple > <li><p>Class Introduction</p> <li><p>Welcome to VS Code</p> </ul> <td><ul class=simple > <li><p><strong>SETUP 1:</strong> <a class="reference external" href="https://nickeubank.github.io/practicaldatascience_book/notebooks/PDS_not_yet_in_coursera/00_setup_env/setup_python.html">Installing Python and miniconda</a></p> <li><p><strong>SETUP 2:</strong> <a class="reference external" href="https://nickeubank.github.io/practicaldatascience_book/notebooks/PDS_not_yet_in_coursera/00_setup_env/setup_vscode.html">Installing and Configuring VS Code</a></p> <li><p><a class="reference external" href="https://nickeubank.github.io/practicaldatascience_book/notebooks/PDS_not_yet_in_coursera/99_advice/llms.html">chatGPT and You</a></p> </ul> <td> <tr class=row-odd ><td><p>Thurs, Aug 31</p> <td><ul class=simple > <li><p>Command Line Basics</p> </ul> <td><ul class=simple > <li><p><strong>SETUP 3:</strong> <a class="reference external" href="https://nickeubank.github.io/practicaldatascience_book/notebooks/PDS_not_yet_in_coursera/00_setup_env/setup_augmented_commandline.html">Setup Augmented Command Line</a></p> <li><p><a class="reference external" href="https://nickeubank.github.io/practicaldatascience_book/notebooks/PDS_not_yet_in_coursera/10_commandline/commandline_part1.html">Command Line Basics</a></p> <li><p><a class="reference external" href="https://github.com/nickeubank/practicaldatascience/raw/master/syllabus/Syllabus_PracticalDataScience.pdf">Read and sign syllabus</a></p> <li><p><a class="reference external" href="https://uma.pop.umn.edu/usa/user/new">Register with IPUMS</a></p> <li><p><a class="reference external" href="https://www.datacamp.com/home">Register for DataCamp</a></p> </ul> <td><ul class=simple > <li><p><a class="reference internal" href="exercises/Exercise_CommandLine_1_Basics.html"><span class=doc >Ex</span></a></p> </ul> <tr class=row-even ><td><p>Fri, Sep 1</p> <td><p><strong>SOFTWARE INSTALL DAY</strong></p> <td><p>A day of trouble shooting install issues</p> <td> <tr class=row-odd ><td><p>Tues, Sep 5</p> <td><ul class=simple > <li><p>Advanced Command Line</p> <li><p>Git</p> <li><p>Packages</p> </ul> <td><ul class=simple > <li><p><a class="reference external" href="https://nickeubank.github.io/practicaldatascience_book/notebooks/PDS_not_yet_in_coursera/10_commandline/commandline_part2.html">Advanced Command Line</a></p> <li><p><a class="reference external" href="https://nickeubank.github.io/practicaldatascience_book/notebooks/class_2/week_4/30_managing_python_packages.html">Python packages</a></p> <li><p><a class="reference internal" href=git_and_github.html ><span class=doc >Git and Github</span></a></p> <li><p><a class="reference external" href="https://learngitbranching.js.org/">Visualize Git Branches</a></p> </ul> <td><ul class=simple > <li><p><a class="reference internal" href="exercises/Exercise_CommandLine_2_Advanced.html"><span class=doc >Ex 1</span></a></p> <li><p><a class="reference internal" href="exercises/Exercise_git.html"><span class=doc >Ex 2</span></a></p> </ul> <tr class=row-even ><td><p>Thurs, Sep 7</p> <td><ul class=simple > <li><p>Git Continued</p> <li><p>Jupyter</p> </ul> <td><ul class=simple > <li><p>Oopsie Resource: <a class="reference external" href="https://ohshitgit.com/">Oh 💩, Git!</a></p> <li><p><a class="reference external" href="https://xkcd.com/1597/">The secret of git</a></p> <li><p><strong>SETUP 4:</strong> <a class="reference external" href="https://nickeubank.github.io/practicaldatascience_book/notebooks/PDS_not_yet_in_coursera/00_setup_env/jupyter_in_vscode.html">Jupyter in VS Code</a></p> <li><p><strong>OPTIONAL SETUP:</strong> <a class="reference external" href="https://nickeubank.github.io/practicaldatascience_book/notebooks/PDS_not_yet_in_coursera/00_setup_env/jupyter_r_notebooks.html">R Jupyter Notebooks</a></p> </ul> <td><ul class=simple > <li><p><a class="reference internal" href="exercises/Exercise_jupytervscode.html"><span class=doc >Ex 1</span></a></p> <li><p><a class="reference internal" href="exercises/Exercise_git_2.html"><span class=doc >Ex 2</span></a></p> </ul> <tr class=row-odd ><td><p>Tues, Sep 12</p> <td><ul class=simple > <li><p>Python Debugger</p> <li><p>R / Python Differences</p> <li><p>Packages</p> </ul> <td><ul class=simple > <li><p><a class="reference external" href="https://www.youtube.com/watch?v=JD8BrXXNtjA">What are Tracebacks?</a></p> <li><p><a class="reference external" href="https://nickeubank.github.io/practicaldatascience_book/notebooks/PDS_not_yet_in_coursera/20_programming_concepts/10_debugging_principles.html">Debugging Tools</a></p> <li><p><a class="reference external" href="https://nickeubank.github.io/practicaldatascience_book/notebooks/PDS_not_yet_in_coursera/20_programming_concepts/20_debugging_in_vscode.html">Python Debugger in VS Code</a></p> <li><p><a class="reference external" href="https://nickeubank.github.io/practicaldatascience_book/notebooks/PDS_not_yet_in_coursera/20_programming_concepts/vars_v_objects.html">variables v objects</a></p> <li><p><a class="reference external" href="https://nickeubank.github.io/practicaldatascience_book/notebooks/PDS_not_yet_in_coursera/20_programming_concepts/python_v_r.html">Python v. R</a></p> </ul> <td><ul class=simple > <li><p><a class="reference internal" href="exercises/Exercise_debugger.html"><span class=doc >Ex 1</span></a></p> <li><p><a class="reference internal" href="exercises/Exercise_variables_v_objects.html"><span class=doc >Ex 2</span></a></p> </ul> <tr class=row-even ><td><p>Thurs, Sep 14</p> <td><ul class=simple > <li><p>Numpy Basics</p> </ul> <td><ul class=simple > <li><p><a class="reference external" href="https://nickeubank.github.io/practicaldatascience_book/notebooks/class_2/week_2/10_why_numpy.html">Why numpy? through Vector Subsetting Recap, SKIP Speed/Ease of Use Tradeoff and Vectorization</a></p> </ul> <td><ul class=simple > <li><p><a class="reference internal" href="exercises/Exercise_numpy_vectors.html"><span class=doc >Ex 1</span></a></p> </ul> <tr class=row-odd ><td><p>Tues, Sep 19</p> <td><ul class=simple > <li><p>Numpy Arrays</p> </ul> <td><p><strong>More Numpy Concepts:</strong></p> <ul class=simple > <li><p><a class="reference external" href="https://nickeubank.github.io/practicaldatascience_book/notebooks/class_2/week_3/10_views_and_copies.html">Views and Copies</a></p> <li><p><a class="reference external" href="https://nickeubank.github.io/practicaldatascience_book/notebooks/class_2/week_3/11_when_do_I_get_a_view.html">When Do I Get a View</a></p> <li><p><a class="reference external" href="https://nickeubank.github.io/practicaldatascience_book/notebooks/class_2/week_3/13_objects_and_variables.html">Variables, Objects, and Numpy</a></p> <li><p><a class="reference external" href="https://nickeubank.github.io/practicaldatascience_book/notebooks/class_2/week_3/12_views_and_copies_recap.html">Views and Copies Recap</a></p> <li><p><a class="reference external" href="https://nickeubank.github.io/practicaldatascience_book/notebooks/PDS_not_yet_in_coursera/20_programming_concepts/ints_and_floats.html">Numbers in Computer</a></p> </ul> <p><strong>Matrices:</strong></p> <ul class=simple > <li><p><a class="reference external" href="https://nickeubank.github.io/practicaldatascience_book/notebooks/class_2/week_3/00_welcome_to_week_3.html">Matrices — From Welcome through Review of Matrices</a> (<em>see navigation bar on left</em>)</p> </ul> <p><strong>ND Arrays:</strong></p> <ul class=simple > <li><p><a class="reference external" href="https://nickeubank.github.io/practicaldatascience_book/notebooks/class_2/week_3/40_nd_arrays.html">Arrays — From Welcome through Color Images as Arrays</a> (<em>see navigation bar on left</em>)</p> </ul> <td><ul class=simple > <li><p><a class="reference internal" href="exercises/Exercise_numpy_viewcopies.html"><span class=doc >Link</span></a></p> </ul> <tr class=row-even ><td><p>Thurs, Sep 21</p> <td><ul class=simple > <li><p>Pandas: Series</p> </ul> <td><ul class=simple > <li><p><a class="reference external" href="https://nickeubank.github.io/practicaldatascience_book/notebooks/class_2/week_4/10_speed_and_ease_of_use.html">Speed / Ease of Use Tradeoff</a></p> <li><p><a class="reference external" href="https://nickeubank.github.io/practicaldatascience_book/notebooks/class_2/week_4/11_vectorization.html">Vectorization</a></p> <li><p><a class="reference external" href="https://nickeubank.github.io/practicaldatascience_book/notebooks/class_3/week_2/00_intro_to_pandas.html">Pandas: From Working with Tabular Data through Subsetting and Indexing with Single Square Brackets</a></p> </ul> <td><ul class=simple > <li><p><a class="reference internal" href="exercises/Exercise_series.html"><span class=doc >Link</span></a></p> </ul> <tr class=row-odd ><td><p>Tues, Sep 26</p> <td><ul class=simple > <li><p>Pandas: DataFrames</p> </ul> <td><ul class=simple > <li><p><a class="reference external" href="https://nickeubank.github.io/practicaldatascience_book/notebooks/class_3/week_2/30_pandas_dataframes.html">Pandas DataFrames</a></p> <li><p><a class="reference external" href="https://nickeubank.github.io/practicaldatascience_book/notebooks/class_3/week_2/35_pandas_dataframe_gotchas.html">Pandas DataFrame Gotchas</a></p> <li><p><a class="reference external" href="https://nickeubank.github.io/practicaldatascience_book/notebooks/class_3/week_2/50_pandas_pyarrow.html">PyArrow Backend</a></p> </ul> <td><ul class=simple > <li><p><a class="reference internal" href="exercises/Exercise_dataframes.html"><span class=doc >Link</span></a></p> </ul> <tr class=row-even ><td><p>Thurs, Sep 28</p> <td><ul class=simple > <li><p>Pandas: Indices &amp; Missing</p> </ul> <td><ul class=simple > <li><p>WM pp 136-142 (Indices, Section 5.2 up to MultiIndexes)</p> <li><p><a class="reference external" href="https://jakevdp.github.io/PythonDataScienceHandbook/03.04-missing-values.html">Handling Missing Data</a></p> <li><p><a class="reference external" href="https://nickeubank.github.io/practicaldatascience_book/notebooks/class_3/week_3/10_views_and_copies_numpy_review.html">Views and Copies in Pandas through the View/Copy Headache without CoW</a></p> <li><p><a class="reference external" href="https://nickeubank.github.io/practicaldatascience_book/notebooks/class_3/week_2/50_pandas_pyarrow.html">If you didn’t read Tuesday: PyArrow Backend</a></p> </ul> <td><ul class=simple > <li><p><a class="reference internal" href="exercises/Exercise_indices.html"><span class=doc >Link 1</span></a></p> <li><p><a class="reference internal" href="exercises/Exercise_missing.html"><span class=doc >Link 2</span></a></p> </ul> <tr class=row-odd ><td><p>Tues, Oct 3</p> <td><ul class=simple > <li><p>Pandas: Cleaning</p> <li><p>Tracebacks</p> </ul> <td><ul class=simple > <li><p><a class="reference external" href="https://nickeubank.github.io/practicaldatascience_book/notebooks/class_3/week_3/00_plaintext_files.html">Reading and Writing Data (plaintext AND binary)</a></p> <li><p><a class="reference external" href="https://nickeubank.github.io/practicaldatascience_book/notebooks/class_3/week_3/20_cleaning_identifying.html">Data Cleaning (through the missing data subsection on left side bar)</a></p> <li><p><a class="reference external" href="https://realpython.com/python-data-types/#strings">Python Strings (string section only!)</a></p> </ul> <td><ul class=simple > <li><p><a class="reference internal" href="exercises/Exercise_cleaning.html"><span class=doc >Link</span></a></p> </ul> <tr class=row-even ><td><p>Thurs, Oct 5</p> <td><ul class=simple > <li><p>Merging</p> </ul> <td><ul class=simple > <li><p><a class="reference external" href="https://nickeubank.github.io/practicaldatascience_book/notebooks/class_3/week_4/00_intro_to_querying_data.html">Data Manipulations, Concatenating and Merging (NOT grouping or querying subsections on left navigation)</a></p> </ul> <td><ul class=simple > <li><p><a class="reference internal" href="exercises/Exercise_merging.html"><span class=doc >Link</span></a></p> </ul> <tr class=row-odd ><td><p>Tues, Oct 10</p> <td><ul class=simple > <li><p>Plotting</p> </ul> <td><ul class=simple > <li><p><a class="reference external" href="https://nickeubank.github.io/practicaldatascience_book/notebooks/class_5/week_2/10_plotting_in_python.html">Plotting in Python through seaborn and Grammer of Graphics</a></p> </ul> <td><ul class=simple > <li><p><a class="reference internal" href="exercises/Exercise_plotting_part1.html"><span class=doc >Link</span></a></p> </ul> <tr class=row-even ><td><p>Thurs, Oct 12</p> <td><p><strong>FALL BREAK</strong></p> <td> <td> <tr class=row-odd ><td><p>Tues, Oct 17</p> <td><p><strong>FALL BREAK</strong></p> <td> <td> <tr class=row-even ><td><p>Thurs, Oct 19</p> <td><ul class=simple > <li><p>Plotting</p> </ul> <td><ul class=simple > <li><p><a class="reference external" href="https://nickeubank.github.io/practicaldatascience_book/notebooks/class_5/week_5/45_plotting_with_matplotlib.html">Matplotlib</a></p> <li><p><a class="reference external" href="https://nickeubank.github.io/practicaldatascience_book/notebooks/class_5/week_5/46_making_plots_pretty.html">Making Pretty Plots</a></p> <li><p><a class="reference external" href="https://seaborn.pydata.org/generated/seaborn.objects.Plot.on.html">Convert seaborn.objects to matplotlib axes</a></p> </ul> <td><ul class=simple > <li><p><a class="reference internal" href="exercises/Exercise_plotting_part2.html"><span class=doc >Link</span></a></p> </ul> <tr class=row-odd ><td><p>Tues, Oct 24</p> <td><ul class=simple > <li><p>Big Data: What is it, how do I work with it?</p> </ul> <td><ul class=simple > <li><p><a class="reference external" href="https://nickeubank.github.io/practicaldatascience_book/notebooks/PDS_not_yet_in_coursera/30_big_data/10_big_data_what_is_it.html">What is Big Data?</a></p> <li><p><a class="reference external" href="https://nickeubank.github.io/practicaldatascience_book/notebooks/PDS_not_yet_in_coursera/30_big_data/20_big_data_strategies.html">Strategies for Big Data</a></p> <li><p>Download the dataset linked at the top of the linked exercise before class.</p> <li><p><a class="reference external" href="https://nickeubank.github.io/practicaldatascience_book/notebooks/PDS_not_yet_in_coursera/30_big_data/30_parquet.html">Parquet Format</a></p> </ul> <td><ul class=simple > <li><p><a class="reference internal" href="exercises/Exercise_bigdata.html"><span class=doc >Ex</span></a></p> </ul> <tr class=row-even ><td><p>Thurs, Oct 26</p> <td><ul class=simple > <li><p>Defensive Programming</p> <li><p>Workflow</p> <li><p>Backwards Design</p> <li><p>Getting Help Online</p> </ul> <td><ul class=simple > <li><p><a class="reference external" href="https://nickeubank.github.io/practicaldatascience_book/notebooks/PDS_not_yet_in_coursera/20_programming_concepts/workflow.html">Workflow Management</a></p> <li><p><a class="reference external" href="https://nickeubank.github.io/practicaldatascience_book/notebooks/PDS_not_yet_in_coursera/20_programming_concepts/backwards_design.html">Backwards Design</a></p> <li><p><a class="reference external" href="https://nickeubank.github.io/practicaldatascience_book/notebooks/PDS_not_yet_in_coursera/20_programming_concepts/getting_help.html">Getting Help</a></p> <li><p><a class="reference external" href="https://github.com/nickeubank/practicaldatascience/blob/master/opioid_project/PDS_ProjectSummary.pdf">Opioid Project</a></p> </ul> <td> <tr class=row-odd ><td><p>Tues, Oct 31</p> <td><ul class=simple > <li><p>Defensive Programming</p> <li><p>Groupby / Split-Apply-Combine</p> </ul> <td><ul class=simple > <li><p><a class="reference external" href="https://nickeubank.github.io/practicaldatascience_book/notebooks/PDS_not_yet_in_coursera/20_programming_concepts/defensive_programming.html">Defensive Programming</a></p> <li><p><a class="reference external" href="https://nickeubank.github.io/practicaldatascience_book/notebooks/PDS_not_yet_in_coursera/20_programming_concepts/iceberg_principle.html">Iceberg Principle</a></p> <li><p><a class="reference external" href="https://nickeubank.github.io/practicaldatascience_book/notebooks/class_3/week_4/20_grouping.html">Groupby</a></p> <li><p>WM pp Chpt 10, 10.1, 10.2, 10.3</p> </ul> <td><ul class=simple > <li><p><a class="reference internal" href="exercises/Exercise_groupby.html"><span class=doc >Link</span></a></p> </ul> <tr class=row-even ><td><p>Thurs, Nov 2</p> <td><ul class=simple > <li><p>Pandas: Reshaping</p> <li><p>Pandas: Categoricals</p> </ul> <td><ul class=simple > <li><p>WM 8.3</p> <li><p><a class="reference external" href="https://pandas.pydata.org/pandas-docs/stable/user_guide/reshaping.html">Pandas reshaping (with pics!)</a></p> <li><p><a class="reference external" href="http://vita.had.co.nz/papers/tidy-data.html">What is goal of reshaping?</a></p> <li><p>Categoricals: WM 12.1</p> </ul> <td><ul class=simple > <li><p><a class="reference internal" href="exercises/Exercise_reshaping.html"><span class=doc >Link</span></a></p> </ul> <tr class=row-odd ><td><p>Tues, Nov 7</p> <td><ul class=simple > <li><p>Speed and Performance in Python</p> </ul> <td><ul class=simple > <li><p><a class="reference external" href="https://nickeubank.github.io/practicaldatascience_book/notebooks/class_2/week_4/10_speed_and_ease_of_use.html">Understanding Performance</a></p> <li><p><a class="reference external" href="https://nickeubank.github.io/practicaldatascience_book/notebooks/PDS_not_yet_in_coursera/30_big_data/50_performance_solutions.html">Improving Performance</a></p> <li><p><a class="reference external" href="https://nickeubank.github.io/practicaldatascience_book/notebooks/PDS_not_yet_in_coursera/object_vectors.html">Object dtypes</a></p> <li><p><a class="reference external" href="https://nickeubank.github.io/practicaldatascience_book/notebooks/PDS_not_yet_in_coursera/20_programming_concepts/pr_review.html">Code Reviews</a></p> <li><p><strong>Project Strategy Plan Due</strong></p> </ul> <td> <tr class=row-even ><td><p>Thurs, Nov 9</p> <td><ul class=simple > <li><p>Statistics with statsmodels</p> </ul> <td><ul class=simple > <li><p>WM, 3rd Edition, Chapter 12, 12.1, 12.2, 12.3 (Patsy and statsmodels, not scikit-learn)</p> <li><p><a class="reference external" href="https://www.statsmodels.org/stable/regression.html">Skim “Linear Models”</a></p> <li><p><a class="reference external" href="https://www.statsmodels.org/stable/discretemod.html">Skim “Discrete Dep Var Models”</a></p> <li><p><a class="reference external" href="https://www.statsmodels.org/stable/examples/notebooks/generated/regression_diagnostics.html">Regression Diagnostics</a></p> <li><p><a class="reference external" href="https://www.statsmodels.org/stable/examples/notebooks/generated/regression_plots.html">Regression Plots</a></p> <li><p><a class="reference external" href="https://patsy.readthedocs.io/en/latest/R-comparison.html">Patsy: Differences from R</a></p> </ul> <td><ul class=simple > <li><p><a class="reference internal" href="exercises/Exercise_statsmodels.html"><span class=doc >Link</span></a></p> </ul> <tr class=row-odd ><td><p>Tues, Nov 14</p> <td><ul class=simple > <li><p>Machine Learning with sckikit-learn</p> </ul> <td><ul class=simple > <li><p>JVP Chapter 5 up to “Hyperparameters and Model Validation” Section (pp 331 - 359)</p> </ul> <td><ul class=simple > <li><p><a class="reference internal" href="exercises/Exercise_sklearn.html"><span class=doc >Link</span></a></p> </ul> <tr class=row-even ><td><p>Thurs, Nov 16</p> <td><ul class=simple > <li><p>Defining Your Own Estimators</p> <li><p>Regex</p> </ul> <td><ul class=simple > <li><p>Review linear regression as matrix manipulations. <a class="reference external" href="https://www.stat.purdue.edu/~boli/stat512/lectures/topic3.pdf">Here’s a nice review.</a></p> <li><p><a class="reference external" href="https://realpython.com/python3-object-oriented-programming/">Review how to define classes</a></p> <li><p><a class="reference external" href="https://nickeubank.github.io/practicaldatascience_book/notebooks/class_2/week_3/41_broadcasting.html#a-common-gotcha-narrow-matrices-v-1-dimensional-vectors">Broadcasting Gotchyas</a></p> </ul> <td> <tr class=row-odd ><td><p>Tues, Nov 21</p> <td><p>No Class</p> <td> <td> <tr class=row-even ><td><p>Thurs, Nov 23</p> <td><p>THANKSGIVING</p> <td> <td> <tr class=row-odd ><td><p>Tues, Nov 28</p> <td><ul class=simple > <li><p>Parallelism</p> <li><p>Distributed Computing</p> </ul> <td><ul class=simple > <li><p><a class="reference internal" href=parallelism.html ><span class=doc >Parallel Computing</span></a></p> <li><p><a class="reference internal" href=distributed_computing.html ><span class=doc >Distributed Computing with dask</span></a></p> </ul> <p>(Note reading includes a 45 minute video to watch) <strong>Optional:</strong> - <strong>Opioid Project Rough Draft Due</strong></p> <td> <tr class=row-even ><td><p>Thurs, Nov 30</p> <td> <td> <td> <tr class=row-odd ><td><p>Wed Dec 13</p> <td> <td><p><strong>Final Project Report and Presentation Due</strong></p> <td> </table> </section> </section> </article> </div> </div> </main> </div> <footer class=md-footer > <div class=md-footer-nav > <nav class="md-footer-nav__inner md-grid"> <a href=index.html  title="Hello!" class="md-flex md-footer-nav__link md-footer-nav__link--prev" rel=prev > <div class="md-flex__cell md-flex__cell--shrink"> <i class="md-icon md-icon--arrow-back md-footer-nav__button"></i> </div> <div class="md-flex__cell md-flex__cell--stretch md-footer-nav__title"> <span class=md-flex__ellipsis > <span class=md-footer-nav__direction > "Previous" </span> Hello! </span> </div> </a> <a href=autograder_guidelines.html  title="Guidelines for Using the Gradescope Autograder" class="md-flex md-footer-nav__link md-footer-nav__link--next" rel=next > <div class="md-flex__cell md-flex__cell--stretch md-footer-nav__title"><span class=md-flex__ellipsis > <span class=md-footer-nav__direction > "Next" </span> Guidelines for Using the Gradescope Autograder </span> </div> <div class="md-flex__cell md-flex__cell--shrink"><i class="md-icon md-icon--arrow-forward md-footer-nav__button"></i> </div> </a> </nav> </div> <div class="md-footer-meta md-typeset"> <div class="md-footer-meta__inner md-grid"> <div class=md-footer-copyright > <div class=md-footer-copyright__highlight > &#169; Copyright 2021, Nick Eubank. </div> Created using <a href="http://www.sphinx-doc.org/">Sphinx</a> 4.5.0. and <a href="https://github.com/bashtage/sphinx-material/">Material for Sphinx</a> </div> </div> </div> </footer> <script src="_static/javascripts/application.js"></script> <script>app.initialize({version: "1.0.4", url: {base: ".."}})</script>
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diff --git a/source/class_schedule.csv b/source/class_schedule.csv
index f8a0ce8..6a5d985 100644
--- a/source/class_schedule.csv
+++ b/source/class_schedule.csv
@@ -102,7 +102,7 @@
 - `Regression Diagnostics <https://www.statsmodels.org/stable/examples/notebooks/generated/regression_diagnostics.html>`_
 - `Regression Plots <https://www.statsmodels.org/stable/examples/notebooks/generated/regression_plots.html>`_
 - `Patsy: Differences from R <https://patsy.readthedocs.io/en/latest/R-comparison.html>`_",- `Link <exercises/Exercise_statsmodels.ipynb>`_
-"Tues, Nov 14",- Machine Learning with sckikit-learn,"- JVP Chapter 5 up to ""Hyperparameters and Model Validation"" Section (pp 331 - 359)",
+"Tues, Nov 14",- Machine Learning with sckikit-learn,"- JVP Chapter 5 up to ""Hyperparameters and Model Validation"" Section (pp 331 - 359)",- `Link <exercises/Exercise_sklearn.ipynb>`_
 "Thurs, Nov 16","- Defining Your Own Estimators
 - Regex","- Review linear regression as matrix manipulations. `Here's a nice review. <https://www.stat.purdue.edu/~boli/stat512/lectures/topic3.pdf>`_
 - `Review how to define classes <https://realpython.com/python3-object-oriented-programming/>`_
diff --git a/source/class_schedule_xlsx.xlsx b/source/class_schedule_xlsx.xlsx
index d635a6c..6e7ef28 100644
Binary files a/source/class_schedule_xlsx.xlsx and b/source/class_schedule_xlsx.xlsx differ

Date, Rm	Topic	Do Before Class	In-Class Exercise
Tues, Aug 29	Class Introduction Welcome to VS Code	SETUP 1: Installing Python and miniconda SETUP 2: Installing and Configuring VS Code chatGPT and You
Thurs, Aug 31	Command Line Basics	SETUP 3: Setup Augmented Command Line Command Line Basics Read and sign syllabus Register with IPUMS Register for DataCamp	Ex
Fri, Sep 1	SOFTWARE INSTALL DAY	A day of trouble shooting install issues
Tues, Sep 5	Advanced Command Line Git Packages	Advanced Command Line Python packages Git and Github Visualize Git Branches	Ex 1 Ex 2
Thurs, Sep 7	Git Continued Jupyter	Oopsie Resource: Oh 💩, Git! The secret of git SETUP 4: Jupyter in VS Code OPTIONAL SETUP: R Jupyter Notebooks	Ex 1 Ex 2
Tues, Sep 12	Python Debugger R / Python Differences Packages	What are Tracebacks? Debugging Tools Python Debugger in VS Code variables v objects Python v. R	Ex 1 Ex 2
Thurs, Sep 14	Numpy Basics	Why numpy? through Vector Subsetting Recap, SKIP Speed/Ease of Use Tradeoff and Vectorization	Ex 1
Tues, Sep 19	Numpy Arrays	More Numpy Concepts: Views and Copies When Do I Get a View Variables, Objects, and Numpy Views and Copies Recap Numbers in Computer Matrices: Matrices — From Welcome through Review of Matrices (see navigation bar on left) ND Arrays: Arrays — From Welcome through Color Images as Arrays (see navigation bar on left)	Link
Thurs, Sep 21	Pandas: Series	Speed / Ease of Use Tradeoff Vectorization Pandas: From Working with Tabular Data through Subsetting and Indexing with Single Square Brackets	Link
Tues, Sep 26	Pandas: DataFrames	Pandas DataFrames Pandas DataFrame Gotchas PyArrow Backend	Link
Thurs, Sep 28	Pandas: Indices & Missing	WM pp 136-142 (Indices, Section 5.2 up to MultiIndexes) Handling Missing Data Views and Copies in Pandas through the View/Copy Headache without CoW If you didn’t read Tuesday: PyArrow Backend	Link 1 Link 2
Tues, Oct 3	Pandas: Cleaning Tracebacks	Reading and Writing Data (plaintext AND binary) Data Cleaning (through the missing data subsection on left side bar) Python Strings (string section only!)	Link
Thurs, Oct 5	Merging	Data Manipulations, Concatenating and Merging (NOT grouping or querying subsections on left navigation)	Link
Tues, Oct 10	Plotting	Plotting in Python through seaborn and Grammer of Graphics	Link
Thurs, Oct 12	FALL BREAK
Tues, Oct 17	FALL BREAK
Thurs, Oct 19	Plotting	Matplotlib Making Pretty Plots Convert seaborn.objects to matplotlib axes	Link
Tues, Oct 24	Big Data: What is it, how do I work with it?	What is Big Data? Strategies for Big Data Download the dataset linked at the top of the linked exercise before class. Parquet Format	Ex
Thurs, Oct 26	Defensive Programming Workflow Backwards Design Getting Help Online	Workflow Management Backwards Design Getting Help Opioid Project
Tues, Oct 31	Defensive Programming Groupby / Split-Apply-Combine	Defensive Programming Iceberg Principle Groupby WM pp Chpt 10, 10.1, 10.2, 10.3	Link
Thurs, Nov 2	Pandas: Reshaping Pandas: Categoricals	WM 8.3 Pandas reshaping (with pics!) What is goal of reshaping? Categoricals: WM 12.1	Link
Tues, Nov 7	Speed and Performance in Python	Understanding Performance Improving Performance Object dtypes Code Reviews Project Strategy Plan Due
Thurs, Nov 9	Statistics with statsmodels	WM, 3rd Edition, Chapter 12, 12.1, 12.2, 12.3 (Patsy and statsmodels, not scikit-learn) Skim “Linear Models” Skim “Discrete Dep Var Models” Regression Diagnostics Regression Plots Patsy: Differences from R	Link
Tues, Nov 14	Machine Learning with sckikit-learn	JVP Chapter 5 up to “Hyperparameters and Model Validation” Section (pp 331 - 359)
Thurs, Nov 16	Defining Your Own Estimators Regex	Review linear regression as matrix manipulations. Here’s a nice review. Review how to define classes Broadcasting Gotchyas
Tues, Nov 21	No Class
Thurs, Nov 23	THANKSGIVING
Tues, Nov 28	Parallelism Distributed Computing	Parallel Computing Distributed Computing with dask (Note reading includes a 45 minute video to watch) Optional: - Opioid Project Rough Draft Due
Thurs, Nov 30
Wed Dec 13		Final Project Report and Presentation Due