Course #
Section Number
Winter 2024
Data Analytics
Course Instructor

The objective of this course is to train students to be insightful users of modern machine-learning methods. The class covers regularization methods for regression and classification, as well as large-scale approaches to inference and testing. In order to have greater flexibility when analyzing datasets, both frequentist and Bayesian methods are investigated. This class is required for the Data Analytic specialization but is open to all students who have taken the Harris core statistics classes (or the equivalent) and have some exposure to programming.


Students are required to register for both a lecture (PPHA 30545) and a language-specific discussion (PPHA 30547 in R or PPHA 30548 in Python).

Quarter Title Instructor Day(s) Time(s) Syllabus
Winter 2024 Machine Learning for Public Policy Jeff Levy
Winter 2024 Machine Learning for Public Policy Chris Clapp