◎ DSCI 425 - Supervised Learning

(3 credits)

An introduction to machine or statistical learning techniques, covering both supervised and unsupervised methods. Supervised methods for both predicting both numeric and categorical responses will be the focus. Unsupervised learning methods such as clustering, association rules, and dimension reduction methods will be briefly discussed. Prerequisites: DSCI 210 - Data Science, STAT 360 - Regression Analysis, and CMST 191 - Introduction to Public Speaking or CMST 192 - Introduction to Speech Communication, or instructor’s permission. Grade or P/NC. Offered alternate years.

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