Each compulsory course is accompanied by a lecturer over the course of several years. The evaluations and feedback from students can thus be systematically incorporated into the further development of the courses, and the courses remain consistent over the years. Large events are supported by the use of online learning platforms, which simplifies communication between students and teachers. A large number of the courses in the first several semesters also provide an opportunity to participate online.

Bilateral agreements with 12 partner universities in Europe. Intensive networks in research with top scientists worldwide, international collaboration as part of EU programmes, projects of the ESF and the DAAD and with award winners of the Humboldt Foundation.

Université de Nantes, Frankreich; Technological University Dublin, Irland; Università di Pisa, Italien; Università degli Studi Giustino Fortunato, Italien; Universität Luxemburg; Göteborgs Universitet, Schweden; Ege Üniversitesi Izmir, Türkei

Very good access to high-performance cluster "HILBERT", which can also be used by students for appropriate final theses. Excellent infrastructure for artificial intelligence and machine learning applications.

Strong interdisciplinary orientation of research, e.g. through the participation of Bioinformatics in the Cluster of Excellence of Biology; and through intensive collaboration with the Social Sciences department at the Düsseldorf Institute for Internet and Democracy (with a focus on Digital Democracy) and the Leibniz Institute for Social Sciences in Cologne; Close collaboration with the Faculty of Medicine in the areas of Data Science and Artificial Intelligence; Joint professorships with the Jülich Research Centre in Data Science and Machine Learning.

Set-up of a group of employees devoted to the development and support of basic teaching principles with a special focus and continuing education in didactics. This involves developing a programme for early detection of problems and for supporting weak students.

https://www.hhu.de/studium/bewerbung-und-einschreibung/bewerbungsportal/zulassungsfreie-einschreibung