CAUSALab's annual summer courses on causal inference are returning June 2025. Information regarding upcoming course offerings and registration will be ...

This accompanying tutorial introduces key concepts in machine learning-based causal inference, and can be used as both lecture notes and as programming examples ...

This course aims to define causation in biomedical research, describe methods to make causal inferences in epidemiology and health services research.

Explore causal inference methods for determining cause-and-effect relationships. Learn to apply statistical techniques to identify causality in data.

Our introduction to causal inference course is a five-day in-person training event. It is not possible to attend remotely. The course includes of a mix of ...

This course includes five days of interactive sessions and engaging speakers to provide key fundamental principles underlying a broad array of techniques.

In this short course we will give a first introduction to causal thinking and its applications to problems from different scientific disciplines.

This course covers the latest developments in causal inference methods and gives practical explanations about applying these methods to real research questions.

Week 1 An Introduction to Causal Inference: This 5-day course introduces concepts and methods for causal inference from observational data.

This course will cover some of the most popular techniques for estimating causal effects with observational data.