INTRODUCTION TO STATISTICAL MACHINE LEARNING
This course is an introduction to concepts, methods, and best practices in statistical machine learning. Topics covered include regularized regression, classification, kernels, dimension reduction, clustering, trees, and ensemble learning. Emphasis will be placed on applied data analysis and computation. Recommended Prerequisite(s): STAT 411 and CAAM 335 or CMOR 302 or MATH 354 or MATH 355 . Mutually Exclusive: Cannot register for STAT 413 if student has credit for ELEC 478 .
Prerequisites & course information
Short Title: INTRO TO STAT MACHINE LEARNING Department: Statistics Grade Mode: Standard Letter Course Type: Lecture Credit Hours: 3 Restrictions: Enrollment is limited to Undergraduate, Undergraduate Professional or Visiting Undergraduate level students. Course Level: Undergraduate Upper-Level Prerequisite(s): STAT 410 and ( STAT 405 or CAAM 210 or CMOR 220 or COMP 140 or COMP 130)
Sources
- Course catalogue ↗2026–2027