Machine Learning for Data Science

CT Score

1500

#0 of 0 in DSCI

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DSCI 301 or STAT 310 or STAT 280 or STAT 305 or ELEC 303 or PSYC 339 or SOCI 382 or SOSC 302 or BIOE 439 or ECON 307 Description: 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→DSCI 303→unlocks 7 courses

7 mapped courses list DSCI 303 as a prerequisite. See on the map →

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