CS208: Applied Privacy for Data Science A graduate course giving an overview of the risks of private data leakage in data science applications and a firm foundation in how to measure and protect against these risks using the framework of differential privacy, together with a hands-on examination of how to build algorithms and software to preserve privacy, including a review of the deployed solutions in industry and government. Co-taught with Salil Vadhan.
Syllabi to recent versions of previous classes that I have taught:
PS 172: Strategies in Conflict An advanced undergraduate class in game theory with a focus on models relevant for international relations. The first half covers repeated games, incomplete information, tournaments, while the second half focuses on evolutionary game theory.
PS 309: Quantitative Political Analysis Fast paced introductory statistical analysis class for social scientists, covering probability and hypothesis testing through to multivariate linear regression. Emphasis on data immersion and applications of statistical techniques to social science questions in real data.
PS 497: Statistical Analysis of Political Data: Political Violence Follow on undergradute statistical analysis class, on generalizations of the linear model including Poisson and Logit and Splines. Substantive focus on models of political violence and state failure, with a strong emphasis on theory testing and building models to bridge qualitative theory and quantitative implications.