Lecture: 2.01.810 Designing Explainable Artificial Intelligence - Details

Lecture: 2.01.810 Designing Explainable Artificial Intelligence - Details

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General information

Course name Lecture: 2.01.810 Designing Explainable Artificial Intelligence
Subtitle inf810
Course number 2.01.810
Semester SoSe2023
Current number of participants 9
expected number of participants 12
Home institute Department of Computing Science
Courses type Lecture in category Teaching
First date Tuesday, 11.04.2023 15:00 - 16:00, Room: (ONLINE)
Type/Form V+Ü
Pre-requisites Participation requirements:
• Basic knowledge in Artificial Intelligence/Machine Learning
• Interest in the scientific development and evaluation of IT artifacts, which goes hand in hand with literature work
• Willingness to deal with qualitative and/or quantitative evaluation methods
• Interest in prototyping

Recommended prior knowledge:
• Basic knowledge of artificial intelligence and/or relevant programming skills (e.g., Python)
• Familiarity with software for the design of prototypical information systems
(e.g., for user interfaces)
Learning organisation Course goals:
• Become acquainted with the research field of Explainable Artificial Intelligence (XAI)
- Become acquainted with different methods and techniques from the field of Explainable Artificial Intelligence (XAI) as well as their characteristics
- Hands-on experience creating XAI systems
Performance record In addition to compulsory attendance at the block seminar, the examination performance will consist of a practical paper or a term paper. The basis for this examination is selected literature (approx, 3 pages per person), which will be handed out in the kick-off meeting on 11.04.
Lehrsprache deutsch

Rooms and times

Tuesday, 11.04.2023 15:00 - 16:00
Monday, 25.09.2023 - Friday, 29.09.2023 09:00 - 17:00


This course combines theoretical foundations from the field of Explainable Artificial Intelligence (XAI) with practical implementations for real-world problems. This includes:
• Communicating the status quo on the topic of Explainable Artificial Intelligence (XAI) and relevant use cases, stakeholders and research opportunities
• Instantiating possible solutions
• Using qualitative and/or quantitative research methods for the evaluation of possible solutions
• Working on (inter)disciplinary questions with high relevance for research and practice

This module will be held as a 1-week block course and (probably) in cooperation with students from the Ruhr University Bochum (Prof. Dr. Christian Meske). Further information can be found here:

Admission settings

The course is part of admission "Anmeldung gesperrt (global)".
Erzeugt durch den Stud.IP-Support
The following rules apply for the admission:
  • Admission locked.