Machine Learning and Algorithms for Computational Social Science

Catalog description

This courses teaches students both foundational and frontier algorithms and models used to analyze social science data. Analytical goals are data description, data reduction, and detection of relationships among variables, and ways to interpret those relationships in terms of underlying economic and social forces. The course teaches how estimated (i.e., “fit”) models can be used for prediction, forecasting, and possibly inference about cause and effect.