— Statistical Learning I

Prerequisites & course information

This version has ended; see updated course, below. Course Description: Fundamental concepts and methods in statistical learning with emphasis on supervised learning. Principles, methodologies and applications of parametric and nonparametric regression, classification, resampling and model selection techniques. Learning Activities: Lecture 3 hour(s), Discussion 1 hour(s). Enrollment Restriction(s): Pass One restricted to Statistics majors. Credit Limitation(s): Only 2 units of credit for students who have previously taken ECS 171 . Grade Mode: Letter. STA 142A — Statistical Learning I (4 units) Course Description: Fundamental concepts and methods in statistical learning with emphasis on supervised learning. Principles, methodologies and applications of parametric and nonparametric regression, classification, resampling and model selection techniques. 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. Credit Limitation(s): Only 2 units of credit for students who have previously taken ECS 171 . 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. Credit Limitation(s): Only 2 units of credit for students who have previously taken ECS 171 . Grade Mode: Letter. STA 142A — Statistical Learning I (4 units) Course Description: Fundamental concepts and methods in statistical learning with emphasis on supervised learning. Principles, methodologies and applications of parametric and nonparametric regression, classification, resampling and model selection techniques. 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. Credit Limitation(s): Only 2 units of credit for students who have previously taken ECS 171 . Grade Mode: Letter. This course version is effective from, and including: Winter Quarter 2027.