Parsons School of Design: Art, Media & Technology

Non-Liberal Arts

Undergraduate Course

Graduate Course

Degree Students

Currents: Physicality of ML

Fall 2022

Taught By: Shirley Leung

Section: A

CRN: 4333

Credits: 3

The Physicality of Machine Learning focuses on utilizing the systematic study of algorithms and turning them into a functioning model that can be implemented and actualized in the “real” – physical world. This course will be focusing on introducing students to different types of machine learning models, learning various algorithms and models that can uncover complex patterns, utilizing ready-made software, and learning how to implement them into a physical production method. Students will work in a variety of media depending on their own backgrounds and interests. In this course, students will learn how to interact with text, images, and 3D-based machine learning models and subsequently bring these created work into the physical world.

Open to: All University graduate students, and undergraduate juniors and seniors. Some seats have been reserved for MFA Design & Technology students.

College: Parsons School of Design (PS)

Department: Art, Media & Technology (PSAM)

Campus: New York City (GV)

Course Format: Studio (S)

Modality: In-Person

Max Enrollment: 18

Add/Drop Deadline: September 12, 2022 (Monday)

Online Withdrawal Deadline: December 18, 2022 (Sunday)

Seats Available: Yes

Status: Closed*

* Status information is updated every few minutes. The status of this course may have changed since the last update. Open seats may have restrictions that will prevent some students from registering. Updated: 9:56pm EST 12/3/2022

Meeting Info:

Days: Wednesday

Times: 7:00pm - 9:40pm

Building: 6 East 16th Street

Room: 1208

Date Range: 8/31/2022 - 12/7/2022