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CSE 244AFoundations of Deep Learning

5 creditsGraduateStudent Option

Provides foundations of deep learning algorithms and principles. Topics include neural networks, deep learning principles, deep learning architectures such as convolutional neural networks and recurrent neural networks, autoencoders, generative adversarial networks, and reinforcement learning. (CSE 244A and CSE 244B formerly offered as one course, CSE 244.)

Prerequisites

Prerequisite(s): CSE 201 and familiarity with basic machine learning concepts. Enrollment is restricted to computer science and engineering graduate students.

Find a section and add it to your scheduleLive seat counts, time-conflict checks and the walk from your previous class.

When it runs

Winter 2027Open Winter 2027

SectionTypeWhenWhereInstructorSeats
01LectureAsynchronousY. ZhouOpen 0/42

Fall 2025Open Fall 2025

SectionTypeWhenWhereInstructorSeats
01Lecture
Tue Thu 3:20pm–4:55pm
Porter Acad 148Y. ZhouOpen 42/45

Who teaches it

InstructorRatingDifficultyWould take againReviews
Yuyin Zhou3.0 / 53.3 / 550%6

From RateMyProfessors, which is student-submitted and not a survey. Small review counts move a long way on one bad quarter.

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