CSE 290PData Privacy Via Machine Learning, and Back
Helps students achieve both expository knowledge and expertise in the field of data privacy. Focuses on fundamental techniques used in designing privacy-preserving, machine-learning systems in both academia and in the industry. Students are expected to read and understand recent research papers in the topic. (Formerly Computer Science 290P.)
Prerequisite(s): CSE 201 and CSE 242 or equivalent. Enrollment is restricted to graduate students.
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When it runs
Winter 2027Open Winter 2027
| Section | Type | When | Where | Instructor | Seats |
|---|---|---|---|---|---|
| 01 | Lecture | TBA | TBD In Person | M. Lesani | Open 0/20 |
Who teaches it
| Instructor | Rating | Difficulty | Would take again | Reviews |
|---|---|---|---|---|
| Mohsen Lesani | 4.4 / 5 | 3.0 / 5 | 100% | 5 |
From RateMyProfessors, which is student-submitted and not a survey. Small review counts move a long way on one bad quarter.
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