392047 Real-World Problems of Artificial Intelligence (S) (SoSe 2026)

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This course critically examines the challenges that emerge when artificial intelligence (AI) systems are applied to complex, real-world problems. Students will engage with advanced topics at the intersection of AI theory, data-driven modeling, and socio-technical systems. The course emphasizes understanding the gap between laboratory performance and practical deployment, highlighting issues such as generalization, data bias, uncertainty, interpretability, and ethical responsibility. Through scholarly readings, analytical discussions, and a hands-on tutorial, students will learn to evaluate and design AI solutions that are robust, fair, and context-aware. The course integrates perspectives from computer science, data ethics, and human–computer interaction to prepare students for research and professional practice in responsible AI development. Prerequisites: Solid understanding of machine learning and AI concepts, proficiency in Python and basic knowledge of statistics or data analysis.

Teaching staff

Dates ( Calendar view )

Frequency Weekday Time Format / Place Period  
weekly Do 14-16 CITEC 3.220 13.04.-24.07.2026

Subject assignments

Module Course Requirements  
39-M-Inf-AI-adv-foc Advanced Artificial Intelligence (focus) Advanced Artificial Intelligence (focus) Advanced Artificial Intelligence (focus): Seminar Student information
- Graded examination Student information
39-M-Inf-AI-adv_a Advanced Artificial Intelligence Advanced Artificial Intelligence Advanced Artificial Intelligence: Seminar Graded examination
Student information
39-M-Inf-AI-app Applied Artificial Intelligence Applied Artificial Intelligence Applied Artificial Intelligence: Seminar Student information
- Graded examination Student information
39-M-Inf-AI-app-foc_a Applied Artificial Intelligence (focus) Applied Artificial Intelligence (focus) Applied Artificial Intelligence (focus): Seminar Student information
- Graded examination Student information

The binding module descriptions contain further information, including specifications on the "types of assignments" students need to complete. In cases where a module description mentions more than one kind of assignment, the respective member of the teaching staff will decide which task(s) they assign the students.

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Registered number: 5
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SS2026_392047@ekvv.uni-bielefeld.de
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Last update basic details/teaching staff:
Saturday, January 3, 2026 
Last update times:
Friday, January 9, 2026 
Last update rooms:
Friday, January 9, 2026 
Type(s) / SWS (hours per week per semester)
seminar (S) / 2
Language
This lecture is taught in english
Department
Faculty of Technology
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659961111