Machine Learning in Social Science Research: Methods and Applications

This course introduces participants to core machine learning algorithms and their growing relevance for addressing complex societal challenges through social science research.

Emphasizing both theoretical foundations and hands-on practice, the course enables participants to apply machine learning techniques to real-world social data, particularly in policy-related contexts. Through interactive lectures, empirical case studies, and coding labs, participants will learn how to design, implement, and evaluate machine learning models with a focus on policy analysis and ethical considerations. This interdisciplinary course fills a critical gap in social science education by equipping researchers with practical tools for predictive modeling and critical thinking for validation and interpretation, fostering impactful, data-driven policy research.