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This course will introduce students to the subject of machine learning and its applications in the field of design, particularly for the semantic exploration of datasets. Students will gain a top-level understanding of the history and current state of machine learning, as well as an understanding of the frontiers of data organization for image, text, and audio. Additionally, this course will explore the philosophical and moral implications of emerging machine learning technologies and their impact on society at large. Valid outcomes from the course may be tools, products, or art, and may focus on practical or conceptual/critical applications. This is a hands on technical course using Python, Javascript, HTML, and CSS. Students will be expected to keep up with the technical demands independently.
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The class will be held Wednesdays from 7-9:40pm ET at this zoom link
The first half of the class on 1/27 will be a special joing session between classes, the link is here
There is a slack channel for the course which can be joined here. Given the asynchronous nature of this class across multiple time zones, this may be the best way to trouble shoot code issues and address questions.
Please note - course outline is subject to change during the semester. Please pay attention to emails and check the site regularly for updates.
| Week | Date | Topic |
|---|---|---|
| 1 | 1/20 | Introduction and overview, syllabus handed out. Intro to python |
| 2 | 1/27 | Combined special presentation - ML in Praxis. Python continued |
| 3 | 2/3 | Essentials of ML and exploring in N dimensions |
| 4 | 2/10 | Deep learning - history and current applications |
| 5 | 2/17 | Datasets and scraping |
| 6 | 2/24 | Class cancelled |
| 7 | 3/3 | Roll your own Neural Network |
| 8 | 3/10 | Feature extraction and exploration methodologies, introducing the midterm |
| 9 | 3/24 | One on one midterm review, midterm proposals due |
| 10 | 3/31 | Midterm presentations |
| 11 | 4/7 | Semantic organization and classification of text |
| 12 | 4/14 | Using WebGL for interactive web spaces |
| 13 | 4/21 | Creating user interfaces with React |
| 14 | 4/28 | Work session |
| 15 | 5/5 | Final presentations |
By the successful completion of this course, students will be able to:
- Create projects that use interactivity, machine learning, and code to creatively explore datasets
- Demonstrate a knowledge of the fundamentals of machine learning
- Develop two projects in machine learning using the provided resources
- Develop several visual & interactive projects
- Demonstrate the ability to research and learn unfamiliar technical topics
- Effectively debug and problem solve broken code
- Develop an understanding of the moral, ethical, and societal impacts of machine learning
- Project #1 (Midterm), Due 3/24
- Project #2 (Final), Due 5/5
Readings will be assigned and simple but graded responses will be required. This is part of your active participation grade.
There is no required textbook for this course. Readings will be assigned each week to be discussed in the following class. Recommended texts for interested students include:
- Shaw, Zed A. Learn Python 3 the Hard Way, Boston, 2017
- Rashid, Tariq. Make Your Own Neural Network. Lexington, Kentucky: 2019.
Coding is not something that can be entirely taught in the classroom. In this class, I will outline key concepts of how to use Python for machine learning and HTML/CSS/Javascript to build web applications, but the majority of the learning will occur outside of the classroom, as you write code. It is important that you write code and that you do it often. It is also important that you not be discouraged. Even the most experienced coders make mistakes. However, as you continue, you will get better at identify and debugging your errors. Persistence is crucial to success.
Aside from a decently fast computer (4 years old or younger is a good rule of thumb), no materials or supplies are necessary for this class.
I will hold office hours weekly on Monday evenings. You can sign up here
There are a number of free resources that are available to you to help you with material I will be covering in class:
If you are interested in a reference book for web development, I recommend SuperHi’s “Learn to Code Now”, which is explicitly written for people who work in the creative industry. It is available through their website as a print or digital copy, with a 20% discount for students.
The university also provides many resources to help students achieve academic and artistic excellence. These resources include:
- The University (and associated) Libraries
- The University Learning Center
- University Disabilities Service
In particular, the University Learning Center offers in-person coding assistance to those who need it.
In keeping with the university’s policy of providing equal access for students with disabilities, any student with a disability who needs academic accommodations is welcome to meet with us privately. All conversations will be kept confidential. Students requesting any accommodations will also need to contact Student Disability Service (SDS). SDS will conduct an intake and, if appropriate, the Director will provide an academic accommodation notification letter for you to bring to us. At that point, I will review the letter with you and discuss these accommodations in relation to this course.
This course borrows from many sources, but especially the following syllabi
The Making Center is a constellation of shops, labs, and open workspaces that are situated across the New School to help students express their ideas in a variety of materials and methods. We have resources to help support woodworking, metalworking, ceramics and pottery work, photography and film, textiles, printmaking, 3D printing, manual and CNC machining, and more. A staff of technicians and student workers provide expertise and maintain the different shops and labs. Safety is a primary concern, so each area has policies for access, training, and etiquette that students and faculty should be familiar with. Many areas require specific orientations or trainings before access is granted. Detailed information about the resources available, as well as schedules, trainings, and policies can be found at resources.parsons.edu.
Late work will be graded with a 5 point deduction for each day it is late.
- Attendance and participation 30%
- Midterm 30%
- Final 40%
- Total 100%
Grades
- (A) Work of exceptional quality, which often goes beyond the stated goals of the course
- (A-) Work of very high quality
- (B+) Work of high quality that indicates higher than average abilities
- (B) Very good work that satisfies the goals of the course
- (B-) Good work
- (C+) Above-average work
- (C ) Average work that indicates an understanding of the course material; passable Satisfactory completion of a course is considered to be a grade of C or higher.
- (C-) Passing work but below good academic standing
- (F) Failure, no credit
The grade of W may be issued by the Office of the Registrar to a student who officially withdraws from a course within the applicable deadline. There is no academic penalty, but the grade will appear on the student transcript. A grade of W may also be issued by an instructor to a graduate student (except at Parsons and Mannes) who has not completed course requirements nor arranged for an Incomplete.
The grade of Z is issued by an instructor to a student who has not attended or not completed all required work in a course but did not officially withdraw before the withdrawal deadline. It differs from an “F,” which would indicate that the student technically completed requirements but that the level of work did not qualify for a passing grade.
The grade of I, or temporary incomplete, may be granted to a student under unusual and extenuating circumstances, such as when the student’s academic life is interrupted by a medical or personal emergency. This mark is not given automatically but only upon the student’s request and at the discretion of the instructor. A Request for Incomplete form must be completed and signed by student and instructor. The time allowed for completion of the work and removal of the “I” mark will be set by the instructor with the following limitations:
Work must be completed no later than the seventh week of the following fall semester for spring or summer term incompletes and no later than the seventh week of the following spring semester for fall term incompletes. Grades of “I” not revised in the prescribed time will be recorded as a final grade of “WF” by the Office of the Registrar.
Students are responsible for all assignments, even if they are absent. Late assignments, failure to complete the assignments for class discussion and/or critique, and lack of preparedness for in-class discussions, presentations and/or critiques will jeopardize your successful completion of this course.
Class participation is an essential part of class and includes: keeping up with reading, assignments, projects, contributing meaningfully to class discussions, active participation in group work, and coming to class regularly and on time.
Parsons’ attendance guidelines were developed to encourage students’ success in all aspects of their academic programs. Full participation is essential to the successful completion of coursework and enhances the quality of the educational experience for all, particularly in courses where group work is integral; thus, Parsons promotes high levels of attendance. Students are expected to attend classes regularly and promptly and in compliance with the standards stated in this course syllabus.
While attendance is just one aspect of active participation, absence from a significant portion of class time may prevent the successful attainment of course objectives. A significant portion of class time is generally defined as the equivalent of three weeks, or 20%, of class time. Lateness or early departure from class may be recorded as one full absence. Students may be asked to withdraw from a course if habitual absenteeism or tardiness has a negative impact on the class environment.
Whether the course is a lecture, seminar or studio, faculty will assess each student’s performance against all of the assessment criteria in determining the student’s final grade.
Use of Canvas may be an important resource for this class. Students should check it for announcements before coming to class each week.
In rare instances, I may be delayed arriving to class. If I have not arrived by the time class is scheduled to start, you must wait a minimum of thirty minutes for our arrival. In the event that I will miss class entirely, a sign will be posted at the classroom indicating your assignment for the next class meeting.
The use of electronic devices (phones, tablets, laptops, cameras, etc.) is permitted when the device is being used in relation to the course's work. All other uses are prohibited in the classroom and devices should be turned off before class starts.
Compromising your academic integrity may lead to serious consequences, including (but not limited to) one or more of the following: failure of the assignment, failure of the course, academic warning, disciplinary probation, suspension from the university, or dismissal from the university.
Students are responsible for understanding the University’s policy on academic honesty and integrity and must make use of proper citations of sources for writing papers, creating, presenting, and performing their work, taking examinations, and doing research. It is the responsibility of students to learn the procedures specific to their discipline for correctly and appropriately differentiating their own work from that of others. The full text of the policy, including adjudication procedures, is found athttp://www.newschool.edu/policies/# Resources regarding what plagiarism is and how to avoid it can be found on the Learning Center’s website: http://www.newschool.edu/university-learning-center/student- resources/
The New School views “academic honesty and integrity” as the duty of every member of an academic community to claim authorship for his or her own work and only for that work, and to recognize the contributions of others accurately and completely. This obligation is fundamental to the integrity of intellectual debate, and creative and academic pursuits. Academic honesty and integrity includes accurate use of quotations, as well as appropriate and explicit citation of sources in instances of paraphrasing and describing ideas, or reporting on research findings or any aspect of the work of others (including that of faculty members and other students). Academic dishonesty results from infractions of this “accurate use”. The standards of academic honesty and integrity, and citation of sources, apply to all forms of academic work, including submissions of drafts of final papers or projects. All members of the University community are expected to conduct themselves in accord with the standards of academic honesty and integrity. Please see the complete policy in the Parsons Catalog.