Deep Learning – Winter Term 2026/27

This is the website for the Deep Learning lecture at the University of Tübingen in the Winter term 2026/27.

More detailed information will be added here before the start of the semester.

When, where, how

Both the lecture and the tutorial will be held in-person.

• Lecture: Wednesday 14:15–15:45, Hörsaal N05, Hörsaalzentrum Morgenstelle.
• Tutorial: Wednesday 16:15–17:45, Hörsaal N05, Hörsaalzentrum Morgenstelle.
• Lecturer: Sebastian Bordt.
• First lecture: 14.10.2026
• Credits: 6 ECTS.

There will be no lecture / tutorial on 18.11.2026.

Content

In this course, students gain and understanding of the theoretical and practical concepts of deep neural networks, including optimization, inference, architectures and applications. After the course, students should be able to develop and train deep neural networks, reproduce research results and conduct original research in this area. For additional information, take a look at the content of the class in Winter 24/25 .

Prerequisites

Basic programming skills (Python) and a solid background in linear algebra and probability. Prior exposure to machine learning is helpful but not strictly required.

Registration

Registration details (Ilias / Alma) will be announced here before the start of the semester.

Questions?

Information on lecturers, tutorials, exams and course materials will be added to this page soon. Only in case of urgent questions, please contact Sebastian Bordt.