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Explainable Artificial Intelligence
- Course ID: WFAIS.IF-XG325.0
- Room: G-1-08
- Teachers:
- Lectures: dr inż. Szymon Bobek (SBK)
- Labs: dr inż. Szymon Bobek (SBK)
Lectures
- [05.10.2026] [SBK] Lecture plan, rules, organizaiton of classes
- [12.10.2026] [SBK] Introduction to xAI
- [19.10.2026] [SBK] Inherently interpretable models I
- [26.10.2026] [SBK] Inherently interpretable models II
- [09.11.2026] [SBK] Global model-agnostic explanations and surrogate models
- [16.11.2026] [SBK] Local model-agnostic explanations I
- [23.11.2026] [SBK] Local model-agnostic explanations II
- [30.11.2026] [SBK] Hands-on programming assignments
- [07.12.2026] [SBK] Counterfactual explanations
- [14.12.2026] [SBK] Evaluation of XAI algorithms
- [21.12.2026] [SBK] Explanations in Neural Networks
- [11.01.2027] [SBK] Challenges of XAI in Industrial applications
- [18.01.2027] [SBK] Hands-on programming assignments
Exam: First Term: 01.02.2027 — XXX Room XXX
Exam: Second Term: 18.02.2027 — XXX, Room XXX
- Lectures Videos: Watch here
Labs (Mondays 10:00, G-1-08)
- [19.10.2026] [SBK] Inherently interpretable models
- [26.10.2026] [SBK] Inherently interpretable models II
- [09.11.2026] [SBK] Global model-agnostic approaches I
- [16.11.2026] [SBK] Local model-agnostic approaches I
- [23.11.2026] [SBK] Local model-agnostic approaches II
- [30.11.2026] Test I
- [30.11.2026] [SBK] Programming Assignment -- start
- [07.12.2026] [SBK] Counterfactual explanations
- [14.12.2026] [MTM] Evaluation of XAI methods
- [21.12.2026] [BMK] Explainability in DNN
- [11.01.2027] [SBK] Programming Assignment -- end
- [18.01.2027] Test II
- [18.01.2027] [SBK] 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
- 50 EXP - mini project assignment
- The above result may be increased by any “pluses” for activity during classes (1 plus = 1 EXP)
- Advantages are taken into account only when passing the exam within the basic deadline.
- All laboratory projects must be submitted on time
- You must obtain at least 60% of points in all tests. In total, meaning (T1_score+T2_score)/(50) should be greater or equal to 0.6).
- Two unexcused absences are allowed.
- Each subsequent absence results in a deduction of 10 EXP.
- Min 50% of presence at laboratories is required
Grading scale:
- >= 90 EXP – bdb
- >= 80 EXP – db+
- >= 70 EXP – db
- >= 60 EXP – dst+
- >= 50 EXP – dst
- < 50 EXP – ndst