Course overview
The aim of the course is to equip students with a comprehensive understanding of the principles, methods, and challenges associated with inferring causal relationships from observational and experimental data. Through theoretical exploration and practical application, this course will provide students with the tools and conceptual frameworks necessary to navigate complex causal inference problems in diverse fields. The students will gain analytical skills and theoretical knowledge necessary to critically evaluate causal claims, design studies that yield valid causal inferences, and contribute to advancements in causal inference methodology and applications.
- Foundations of Causal Models
- Core Causal Inference Methods
- Further Topics
Course learning outcomes
- Identify whether causal modelling is appropriate for the problem at hand
- Critically evaluate whether causal modelling is appropriate for novel scenarios
- Apply the main theoretical results to a variety of situations
- Apply principles of causal reasoning to a variety of problems
- Communicate results clearly
- Implement and interpret the results of basic causal inference algorithms