WCOMS4775-1: Causal Inference for Fall 2021

Days and Time

Mondays and Wednesdays 4:10 PM-5:25 PM

Location

825 MUDD

Allowed For:

  • Undergraduate
  • Masters
  • Professional
  • PhD
  • Undergraduate
  • Masters
  • Professional
  • PhD

Prerequisites:

None

Notes:

None

Instructor:

Bareinboim, Elias

Description

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.