CS 1503 MATHEMATICAL FOUNDATIONS OF MACHINE LEARNING
This introductory course will cover the essential foundational ideas in probability and statistics. We will then discuss the standard applications of these foundational ideas to understand and analyze data, using computational methods, that all computer scientists should know.
Academic Career: Undergraduate
Course Component: Lecture
Grade Component: LG/SNC Elective Basis
Course Requirements: PREQ: (CS 0441 or CS 0406) and (MATH 0280 or MATH 1180 or MATH 1185); (MIN GRADE 'C' or Transfer FOR ALL COURSES LISTED)
Minimum Credits: 4
Maximum Credits: 4
Current Sections
Fall 2026
| Class No. | Days | Times | Room | Instructor(s) | TA(s) | Type |
|---|---|---|---|---|---|---|
| 29815 (1100) | TuTh | 1:00pm-2:15pm | PUBHL A719 | Patrick Skeba | Hang Zhang | LEC |
| 29818 (1100) | F | 10:00am-10:50am | IS 404 | Arun Lekshmi Narayanan | REC | |
| 29819 (1100) | F | 12:00pm-12:50pm | IS 411 | Arun Lekshmi Narayanan | REC | |
| 27562 (1200) | MW | 11:00am-12:15pm | WEB | Marina Barsky | LEC | |
| 27563 (1200) | F | 10:00am-10:50am | WWPH 3803 | Nitish Chandra | REC | |
| 27564 (1200) | F | 11:00am-11:50am | SENSQ 5313 | Nitish Chandra | REC | |
| 27565 (1250) | MW | 3:00pm-4:15pm | WEB | Marina Barsky | LEC | |
| 27566 (1250) | F | 1:00pm-1:50pm | IS 411 | Nitish Chandra | REC | |
| 27567 (1250) | F | 3:00pm-3:50pm | IS 305 | Nitish Chandra | REC |