Applied Causal Inference Methods in Data Science.

Catalog description

This course equips participants with practical tools to estimate causal effects in real-world settings. After building a solid formal foundation, students will learn to design experiments, leverage natural experiments, and analyze observational data using modern causal inference methods. Ideal for those who want to move beyond predictive analytics in order to answer causal questions in their work.