Welcome to the Wiki of the course "Databases and Information Systems" in the winter semester 2025/2026

Information about the exam on Tuesday, 17th March 2026

Results of the official evaluation of this course

The course is given by Prof. Dr. Hannah Bast and assisted by Robin Textor-Falconi.

It takes place every Tuesday from 14:05 - 15:55 h in the seminar room 101-1-9/13 and on Zoom (meeting link, meeting ID: 622 3637 6628, passcode: DBISWS2526). The first lecture is on Tuesday 14.10.2025 and the last lecture is on Tuesday 03.02.2026. There will be no lectures on the Tuesday 04.11.2025 and on the three Tuesdays 23.12.2025, 30.12.2025 and 06.01.2026 (Christmas break). In total there will be 13 lectures.

The tutors for this course are Patrick Brosi, Johannes Kalmbach, Sebastian Walter and Christoph Ullinger. The administrator of the supporting systems (Daphne, SVN, Forum) is Axel Lehmann.

Important Links

Our course management system Daphne (login with your RZ user name and password).
The forum for announcements and questions.
The manual for how to ask questions on the forum.
Our rules for the exercise sheets. Please read them carefully, completely and before you start working on the exercises. They are valid for all exercise sheets of this course.
Information about Subversion (SVN) can be found here (in German) and here (in English); about some editors (including Vim) here (in German).
The courses from previous semesters: Information Retrieval WS 23/24, Information Retrieval WS 22/23, Information Retrieval WS 21/22, Information Retrieval WS 19/20, Information Retrieval WS 18/19, Information Retrieval WS 17/18, Information Retrieval WS 16/17, Information Retrieval WS 15/16, Information Retrieval WS 13/14, Information Retrieval WS 12/13.
The exams from previous semesters: WS 23/24, WS 22/23, WS 21/22, WS 19/20, WS 18/19, WS 17/18, WS 16/17, WS 15/16, WS 13/14, WS 12/13.
Here you find a list of the Python packages you should have installed in your environment. Alternatively you can download and use our Linux Image (for Virtualbox or VMWare) which already contains all packages.
A PyTorch cheatsheet can be found here. An overview over basic tensor usage within PyTorch can be found here. If you are already familiar with NumPy you can find information about how NumPy operations translate to PyTorch operations here.
Here you can find a link to a video tutorial about how to work on the exercise sheets with our course system Daphne and SVN.

Lecture Slides, Video Recordings, Exercise Sheets, and Code

For visitors from outside the University of Freiburg: You can freely access all the course materials below, except the solutions.