Data Science and Public Policy

Pre-req: SIPA IA6501 - Quant II or equivalent quantitative methods course. This course bridges the gap between data science and public policy by bringing together students from diverse academic backgrounds to address contemporary policy challenges using large-scale data. With the rapid growth of digital information and the increasing influence of machine learning and AI on public life, the ability to work across disciplines is becoming essential.

Students will examine real-world datasets on topics such as disinformation campaigns, privacy and surveillance, crime and recidivism, natural disasters, and the impact of generative AI. Through weekly presentations and a semester-long team project, students will gain practical experience applying data science methods to pressing policy issues while learning how to collaborate across fields.