— Statistical Learning II

Prerequisites & course information

This version has ended; see updated course, below. Course Description: Fundamental concepts and methods in statistical learning with emphasis on unsupervised learning. Principles, methodologies and applications of clustering methods, dimension reduction and manifold learning techniques, graphical models and latent variables modeling.. Learning Activities: Lecture 3 hour(s), Discussion 1 hour(s). Enrollment Restriction(s): Pass One restricted to Statistics majors. Grade Mode: Letter. STA 142B — Statistical Learning II (4 units) Course Description: Fundamental concepts and methods in statistical learning with emphasis on unsupervised learning. Principles, methodologies and applications of clustering methods, dimension reduction and manifold learning techniques, graphical models and latent variables modeling.. Prerequisite(s): STA 141A C- or better; ( STA 130A C- or better or STA 131A C- or better or MAT 135A C- or better); ( MAT 022A C- or better or MAT 027A C- or better or MAT 067 C- or better; STA 131A or MAT 135A preferred; MAT 167 recommended. Learning Activities: Lecture 3 hour(s), Discussion 1 hour(s). Enrollment Restriction(s): Pass One restricted to Statistics & Data Science majors and Statistics & Biostatistics graduate students. Grade Mode: Letter. This course version is effective from, and including: Winter Quarter 2027. Learning Activities: Lecture 3 hour(s), Discussion 1 hour(s). Enrollment Restriction(s): Pass One restricted to Statistics majors. Grade Mode: Letter. STA 142B — Statistical Learning II (4 units) Course Description: Fundamental concepts and methods in statistical learning with emphasis on unsupervised learning. Principles, methodologies and applications of clustering methods, dimension reduction and manifold learning techniques, graphical models and latent variables modeling.. Prerequisite(s): STA 141A C- or better; ( STA 130A C- or better or STA 131A C- or better or MAT 135A C- or better); ( MAT 022A C- or better or MAT 027A C- or better or MAT 067 C- or better; STA 131A or MAT 135A preferred; MAT 167 recommended. Learning Activities: Lecture 3 hour(s), Discussion 1 hour(s). Enrollment Restriction(s): Pass One restricted to Statistics & Data Science majors and Statistics & Biostatistics graduate students. Grade Mode: Letter. This course version is effective from, and including: Winter Quarter 2027.