CS 4782

Last Updated

  • Schedule of Classes - October 15, 2026 7:07PM EDT

CS 4782
Introduction to Deep Learning

Course information provided by the 2026-2027 Catalog.

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.


Prerequisites CS 2110; CS 3780 or ECE 4200 or STSCI 3740; CS 1110 or CS 1112; or equivalents.

Enrollment Information Enrollment limited to: Computer Science majors.

Last 4 Terms Offered 2026SP, 2025SP, 2024SP

Learning Outcomes

  • Demonstrate the ability to perform neural network training and inference.
  • Identify the correct neural network architecture choices for a given data modality.
  • Implement a working deep learning pipeline for vision and language tasks.

View Enrollment Information

Syllabi: none

  •   Regular Academic Session.  Choose one lecture and one project. Combined with: CS 5782

  • 4 Credits Opt NoAud

  •  7192 CS 4782   LEC 001

  •  
    • TR
    • Jan 25 - May 11, 2027

    • Ma, W

      Sun, J

  • Instruction Mode: In Person

    For Bowers Computer and Information Science (CIS) Course Enrollment Help, please see: https://tdx.cornell.edu/TDClient/193/Portal/Home/

  •  7193 CS 4782   PRJ 601

  •  
    • Jan 25 - May 11, 2027

    • Ma, W

      Sun, J

  • Instruction Mode: In Person