PUBPOL 5390

Foundations of Machine Learning for Public Policy

Course Description

Course information provided by the 2026-2027 Catalog.

This course is designed for students interested in learning the foundations of machine learning. Our focus will be on applying these techniques to applications in specific policy related scenarios. We will cover the intuition of the theoretical underpinnings, with a focus on practical use of supervised learning tools. (MPA-DA, MPA-DATSCI)

Prerequisites PUPPOL 5301 and PUBPOL 5302 (or equivalent).

Program Requirements (MPA-DA, MPA-DATSCI)

Last 4 Terms Offered 2025FA

Learning Outcomes

• Describe the approaches and algorithms for various machine learning techniques.
• Understand the core concepts that guide machine learning approaches.
• Use Statistical programs (e.g. Stata, Python, R) to implement supervised learning techniques on actual data, and correctly use and interpret the results.
• Assess challenges in the use of ML techniques in Public Policy contexts.

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