| Fall 2020 | CSE 103 (remote) | Probability and statistics for computer scientists |
| Fall 2020 | CSE 291 (remote) | Probabilistic approaches to unsupervised learning |
| Spring 2021 | CSE 101 (remote) | Algorithms |
| Spring 2021 | CSE 291 (remote) | Continual learning |
Webpages of some courses from previous years:
| CSE 101 | Algorithms |
| CSE 103 | Probability and statistics |
| CSE 151 | Machine learning |
| CSE 250B | Machine learning |
| CSE 254 | Seminar: inference in graphical models |
| CSE 254 | Seminar: embeddings |
| CSE 254 | Seminar: deep learning |
| CSE 254 | Seminar: neurally-inspired unsupervised learning |
| CSE 254 | Seminar: deep unsupervised learning |
| CSE 291 | Probabilistic AI |
| CSE 291 | Learning theory I (supervised learning) |
| CSE 291 | Topics in unsupervised learning |
| CSE 291 | Bayesian methods |
| CSE 291 | Geometric algorithms |
| CSE 291 | Topics in learning theory |
| CSE 291 | Distances, similarities, and embeddings |