Fall 2023: Causality and Machine Learning

Fall 2023: Causality and Machine Learning

Course No:
EECS 598-009
Credit Hours:
3 credits
Instructor:
Maggie Makar
Prerequisites:
Familiarity with statistics, probability and machine learning. Knowledge of python.

This course introduces the fundamental concepts of causality, and causal inference using machine learning models. Topics will include:counterfactuals (potential outcomes and graphs), identification and estimation of conditional average treatment effects from randomized control trials and observational data, as well as causal inference under hidden confounding and limited overlap. 

More info (pdf)