Explainable AI 7,5 credits
The course is an advanced course that focuses on explainability for AI methods.
The course addresses the question of how to explain "black-box" models that are opaque and do not provide any explanation for their inner workings. The course introduces different explainability paradigms, such as post-hoc methods, surrogate models, Shapley values, and counterfactual explanations.
Last updated: October 26, 2023
Source: Department of computer and systems sciences, DSV