Explainable AI
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.
The course will cover:
- Intrinsically Interpretable Models
- Global Model-Agnostic Methods
- Local Model-Agnostic Methods
- Optimisation
- Neural Network Interpretability
- Time Series Interpretability
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Course structure
Teaching format
The teaching activities consist of lectures.
The language of instruction is English.Assessment
The course is examined through an on-campus written exam and assignments.
Examiner
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Schedule
The schedule will be available no later than one month before the start of the course. We do not recommend print-outs as changes can occur. At the start of the course, your department will advise where you can find your schedule during the course. -
Course literature
Note that the course literature can be changed up to two months before the start of the course.
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Contact
This course is part of a programme / course package and is not available for application as a stand-alone course.
Study counsellors - master
- Visiting address
Nod Buildning, Borgarfjordsgatan 12, Kista
- Office hours
Please contact us via email if you want to book a meeting. We are available on Campus in Kista and via Zoom.
- Phone hours
Thursday 12.30–2 pm
- Irregular office hours
No phone hours on Thursday 1 May.
