AI-Drive Causal Inference with Observational Data

1.5 units

This 1.5-credit course provides a hands-on introduction to AI-driven causal inference techniques with observational data. The focus is on leveraging machine learning methods for estimating causal effects, understanding treatment heterogeneity, and evaluating policy interventions. Students will gain practical experience through programming assignments and a final project applying causal inference methods to real-world datasets.