CS 4782 — Introduction to Deep Learning
General Information
This class is an introductory course to deep learning. It covers the fundamental principles behind training and inference of deep networks, the specific architecture design choices applicable for different data modalities, discriminative and generative settings, and the ethical and societal implications of such models.
Full Cornell course description (SP26)
Credits: 4
Prerequisites and Enrollment
Prerequisites: CS 2110 or equivalent and CS 3780 or ECE 4200 or STSCI 3740 and CS 1110 or CS 1112.
Recorded Offerings
| Semester | Listed instructors | Course details |
|---|---|---|
| Spring 2026 | Kilian Weinberger, Wei-Chiu Ma | Roster / syllabus |
Workload and General Advice
Student contributions have not been added yet. Consult the offering’s syllabus for assignments and assessment details.
Student Experiences
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Course information checked against Cornell’s Spring and Fall 2026 rosters on September 18, 2026. The listed semesters are verified examples, not a complete offering history.