Explainable Artificial Intelligence
- Course ID: WFAIS.IF-XG325.0
- Room: G-1-08
- Teachers:
- Lectures: dr inż. Szymon Bobek (SBK)
- Labs:
- Mondays dr inż. Szymon Bobek (SBK)
- Wednesdays Sabri Manai, PhD Candidate (SMI)
Lectures
- [07.10.2025] [SBK] Lecture plan, rules, organizaiton of classes
- [13.10.2025] [SBK] Introduction to xAI
- [20.10.2025] [SBK] Inherently interpretable models I
- [27.10.2025] [SBK] Inherently interpretable models II
- [03.11.2025] [SBK] Global model-agnostic explanations and surrogate models
- [17.11.2025] [SBK] Local model-agnostic explanations I
- [24.11.2025] [SBK] Local model-agnostic explanations II
- [01.12.2025] [SBK] Hands-on programming assignments
- [08.12.2025] [SBK] Counterfactual explanations
- [15.12.2025] [SBK] Evaluation of XAI algorithms
- [12.01.2025] [SBK] Explanations in Neural Networks
- [19.01.2026] [SBK] Challenges of XAI in Industrial applications
- [26.01.2026] [SBK] Hands-on programming assignments
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Exam: TBD
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Exam 2nd term: TBD
- Lectures Videos: Watch here
Labs (Mondays 10:00, G-1-08)
- [20.10.2025] [SBK] Inherently interpretable models
- [27.10.2025] [SBK] Inherently interpretable models II
- [03.11.2025] [SBK] Global model-agnostic approaches I
- [17.11.2025] [SBK] Local model-agnostic approaches I
- [24.11.2025] [SBK] Local model-agnostic approaches II
- [01.12.2025] Test I
- [01.12.2025] [SBK] Programming Assignment I
- [08.12.2025] [SBK] Counterfactual explanations
- [15.12.2025] [MTM] Evaluation of XAI methods
- [12.01.2026] [BMK] Explainability in DNN
- [19.01.2026] [SBK] Programming Assignment II
- [26.01.2025] Test II
- [26.01.2025] [SBK] Projects presentations/discussion
Labs (Wednesdays 18:30, G-1-03)
- [22.10.2025] [SMI] Inherently interpretable models
- [29.10.2025] [SMI] Inherently interpretable models II
- [05.11.2025] [SMI] Global model-agnostic approaches I
- [12.11.2025] [SMI] Local model-agnostic approaches I
- [19.11.2025] [SMI] Local model-agnostic approaches II
- [26.11.2025] Test I
- [26.11.2025] [SMI] Programming Assignment I
- [03.12.2025] [SMI] Counterfactual explanations
- [10.12.2025] [SMI] Evaluation of XAI methods
- [17.12.2025] [SMI] Explainability in DNN
- [14.01.2026] [SMI] Programming Assignment II
- [21.01.2026] Test II
- [21.01.2026] [SMI] Projects presentations/discussion
Grading rules
- 100 EXP is 100% of the total points (MAX) from the lab. This consists of:
- 2×25 EXP - two tests, covering material from the laboratories and lecture
- 2×25 EXP - two assignments carried out in groups (2-5 people) during the laboratory
- The above result may be increased by any “pluses” for activity during classes (1 plus = 1 EXP) and extra programming assignments rated individually (3-5 EXP)
- Advantages are taken into account only when passing the exam within the basic deadline.
- All laboratory projects must be submitted on time.
- The mark for late projects will be multiplied by 0.5 (i.e. a maximum of half the number of points can be obtained for a late project).
- You must obtain at least 60% of points in all tests.
- Two unexcused absences are allowed.
- Each subsequent absence results in a deduction of 10 EXP.
Grading scale:
- >= 90 EXP – bdb
- >= 80 EXP – db+
- >= 70 EXP – db
- >= 60 EXP – dst+
- >= 50 EXP – dst
- < 50 EXP – ndst