This course introduces students to machine learning (ML) methods with a focus on applications in economics. Topics include supervised and unsupervised learning, causal inference, text analysis and forecasting using modern ML tools. Students will gain hands-on experience working with economic data in Python/R and learn how to apply ML techniques for both prediction and policy analysis. Prior knowledge of econometrics is required; no machine learning background is assumed.
5 units · Letter (ABCD/NP)
This course introduces students to machine learning (ML) methods with a focus on applications in economics. Topics include supervised and unsupervised learning, causal inference, text analysis and forecasting using modern ML tools. Students will gain hands-on experience working with economic data in Python/R and learn how to apply ML techniques for both prediction and policy analysis. Prior knowledge of econometrics is required; no machine learning background is assumed.
Offered in Autumn 2026 at Stanford University.