Advanced Lecture

Causality in AI

Study causal discovery, inference, and decision making to build AI systems that reason beyond correlations.

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Course overview

The lecture covers fundamentals of causal reasoning, interventions, and counterfactual analysis. Students learn how to combine statistical models with causal semantics to answer "what-if" questions.

  • • TBA

Key details

Term
Irregular (block course)
Format
Lecture
Credits
3 CP
Language
English
Responsible
Moritz Willig, AIML TU Darmstadt

Schedule & resources