CS 3780

Last Updated

  • Schedule of Classes - September 22, 2025 1:06PM EDT

CS 3780
Introduction to Machine Learning

Course information provided by the 2025-2026 Catalog.

The course provides an introduction to machine learning, focusing on supervised learning and its theoretical foundations. Topics include regularized linear models, boosting, kernels, deep networks, generative models, online learning, and ethical questions arising in ML applications.


Prerequisites probability theory (e.g. BTRY 3080, CS 2800, ECON 3130, ENGRD 2700, MATH 4710) and linear algebra (e.g. MATH 2210, MATH 2310, MATH 2940), single-variable calculus (e.g. MATH 1110, MATH 1920) and programming proficiency (e.g. CS 2110).

Forbidden Overlaps CS 3780, CS 5780, ECE 3200, ECE 5420, ORIE 3741, ORIE 5741, STSCI 3740, STSCI 5740

Fees 30. course fee.

Distribution Requirements (OPHLS-AG), (SDS-AS)

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

View Enrollment Information

Syllabi: none

  •   Regular Academic Session.  Choose one lecture and one project. Combined with: CS 5780

  • 4 Credits Opt NoAud

  •  5196 CS 3780   LEC 001

  •  
    • TR
    • Jan 20 - May 5, 2026

    • Gangavarapu, T

      Sridharan, K

  • Instruction Mode: In Person

    Enrollment limited to: Computer Science students. All others should add themselves to the waitlist in January during add/drop.

  •  5895 CS 3780   PRJ 601

  •  
    • Jan 20 - May 5, 2026

    • Gangavarapu, T

      Sridharan, K

  • Instruction Mode: In Person