COMS E4775
Causal Inference
Causal Inference theory and applications. The theoretical topics include the 3-layer causal hierarchy, causal bayesian networks, structural learning, the identification problem and the do-calculus, linear identifiability, bounding, and counterfactual analysis. The applied part includes intersection with statistics, the empirical-data sciences (social and health), and AI and ML.
Topics
- the 3-layer causal hierarchy
- causal bayesian networks
- structural learning
- the identification problem and the do-calculus
- linear identifiability
- bounding
- and counterfactual analysis
Topics explicitly listed in official catalogue description
Prerequisites & course information
Prerequisites: (COMS4711W) and
Sources
- Course catalogue ↗2026-2027