Course Content

Bachelor programme Data Science and Business Analytics

Data science is a new academic discipline that provides not only statistical and technical skills but also practical and applied knowledge in a selectable specialist area. In order to ensure a broad interdisciplinary education, this knowledge is supplemented by content from the fields of economics, law and ethics.

Basic Study (1st and 2nd semester)

  • Data science: conveys the skills of data analysis, machine learning and artificial intelligence. Students learn how to collect, process, analyse and visualise data.
  • Informatics: deals with information processing, transmission and storage. Important focus areas include: programming fundamentals, big-data technologies and business intelligence.
  • Economics and law: deals with economic fundamentals as well as legal and ethical issues.

Specialisation Study (as of the 4th semester)

Elective module: Since data specialists always carry out their analyses in a specific context, the study enables specialisation in a selectable field of application (e.g. marketing, health, media, security, production).* Important fundamentals of the specialist area are taught and a basic understanding of frequent problems is established. *Specialist areas are introduced in the third semester and can be chosen freely. They are offered to students as needed and require a minimum of five participants.

Vocational Internship (4th and 6th semester)

The internships are to be completed in the 4th (five weeks) and 6th semester (10 weeks). The students contact favoured companies independently. To this end, the extensive partner network of the study programme is available to them.

Semester Abroad or European Project Semester (5th semester)

An essential part of the study programme is the international and interdisciplinary project semester. The English-language semester should ensure that independent of stays abroad, experiences in dealing with international teams are had by all students. In order to solve an interdisciplinary problem within the project, the goal is to form groups (with a group size of three to six students) with an international and interdisciplinary composition. The international-project semester can also be completed abroad at a partner university.

Practical Training

The study programme Data Science and Business Analytics maintains intensive cooperation with important partners from the economy and science. This ensures that the study content covers the requirements of the practical experience and takes into account future developments.

The inclusion of external lecturers also enables students to build up practice-relevant knowledge. Additionally, practical transfer and application competencies are promoted by two vocational internships and an international-project semester in which a task formulation from the economy is treated in international teams.

Examples of the use of data science

Big Data

Data Science

Artificial Intelligence

Internet of Things

Why Data Science?

A Human View

Despite the many fully automatic enquiry possibilities through artificial intelligence or deep learning, the most important task is often left to humans. Although an AI can detect patterns, they are not necessarily able to detect cause and effect. If one wants to know why the detected patterns occur, it is the task of the data scientist to comprehensibly explain causal relationships.