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

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.