PUBPOL 5390
Foundations of Machine Learning for Public Policy
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)
Topics
- 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.
Official roster learning outcomes
Prerequisites & course information
PUBPOL 5301 and PUBPOL 5302.
Sources
- Course catalogue ↗2026-2027