DSCI 303: MACHINE LEARNING FOR DS
Spring 2025 · Section 001 · CRN 26888
This course is a practical introduction to machine learning, emphasizing when and how to apply techniques and how to interpret results. Topics covered include regression, classification, dimension reduction, clustering, decision trees, ensemble learning, and neural networks. Recommended Prerequisite(s): STAT 315 or DSCI 101 or COMP 140 and DSCI 302 (may be taken concurrently) or COMP 330 or COMP 430 Mutually Exclusive: Cannot register for DSCI 303 if student has credit for ELEC 478/ELEC 578.
- Credits
- 3
- Instructors
- Akane Sano