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CSE 5709: Machine Learning for Data Science
An introduction to the techniques of machine learning, including models for both supervised and unsupervised learning, and related optimization techniques, covering topics such as regression, neural networks, clustering, model evaluation and selection, and implementation of learning algorithms from first principles.
- Credits
- 3
- Offered
- Fall 2026
- Campuses
- Storrs
- Requirements
- GRAD 5100; Open to graduate students in the M.S. in Data Science program. Recommended preparation: Python programming, multivariable calculus, linear algebra, introductory statistics.
Fall 2026 sections
Taught by Joseph Johnson.
| Section | Type | Meets | Instructor | Campus | Room | Seats |
|---|---|---|---|---|---|---|
| 001 | LEC | 2:00PM - 3:15PM / TuTh | Joseph Johnson | Storrs | FSB 103 | 55 of 70 open |
| 002 | LEC | TBA | Joseph Johnson | Storrs | Online | 0 of 30 open |
Seats as of Nov 12, 2026. HuskyScheduler shows live seats when you search.
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