The Business Informatics programme consists of 120 European Credit Transfer System (EC) points and includes mandatory and optional courses. Each year is divided into four periods, which each contain two course slots. Each course is worth 7.5 EC. 


The curriculum of this Master programme consists of a mandatory and an optional section. The mandatory section consists of:

  • Introduction to Business Informatics
  • Four fundamental MBI courses
  • Thesis project and colloquium

The optional section consists of courses that enable students to individualise their programmes.


Within the MBI programme research and education integrity plays an important role. Ethical aspects of the research (e.g. privacy, hacking, information security, scientific integrity, etc.) are topics in several courses (Advanced Research Methods, Introduction to Business Informatics, Method Engineering) and an integral part of the research training. In addition, all students of the entire Graduate School of Natural Sciences must participate in the course Dilemmas of the Scientist (0.5 EC), which focuses on integrity and social responsibilities of the scientist.

Educational Methods

  • Lectures with guest speakers
  • Workshops
  • Virtual business management
  • Business simulation
  • Individual papers
  • Group projects
  • Seminars and master classes
  • Excursions and visits
  • International study trip
  • Graduation (also abroad)

Examination Methods 

  • Individual papers
  • Presentations
  • Assignments
  • Master’s thesis: In the final thesis project and colloquium (43 EC), you will plan and conduct your own research under the supervision of one of our staff members and an external coach. The thesis project will contain both a scientific and an applied study on a specific business informatics topic. Students often perform these in collaboration with an external organisation, i.e. a knowledge- or IT-intensive company. The project concludes with writing a thesis and a publishable paper based on your research. Thesis results are presented and discussed in the Master’s in Business Informatics Colloquium, where all graduating students and staff meet during a biweekly gathering.
  • Written exams


The Business Informatics programme has a wide choice of subjects available with a professional and interesting atmosphere, while also keeping the lectures informal, entertaining and personal.
David Lautenschutz
Business Informatics study programme

Interdisciplinary profiles

A profile is a coherent set of courses totaling 30 EC and can be chosen to expand the thematic range of your Master's programme. The courses are on a single theme that is usually not a standard part of the programme.

Educational profile – teacher degree

If you are passionate about sharing your knowledge, and you would consider a career as a teacher in secondary education, this profile might be right for you. The emphasis of the Educational Profile is on practitioner skills and school-based activities. Throughout the profile, learning theories and teaching methods will be taught closely linked to your day to day work in the classroom. The profile is tailored to meet the professional development needs of teachers in the early stages of their careers. More information.

Complex systems profile

Complex Systems is an interdisciplinary profile for ambitious students from different Master’s programmes, who want to work on modelling solutions within the field of Complex Systems. The profile gives you the opportunity to broaden your view and knowledge from an interdisciplinary angle and widens your opportunities for further development. It prepares you for a career in interdisciplinary fields at, for instance, financial companies. You will receive a Complex Systems certificate. More information.

Applied Data Science profile

Applied Data Science is a multidisciplinary profile for students who want to better understand and be able to apply Data Science methods, techniques, and processes to solve real-world problems in various application domains. The foundations of applied data science include relevant statistical methods, machine learning techniques and script programming. Moreover, key aspects and implications of ethics, privacy and law are covered as well. Data science methods and techniques are investigated using case studies and applications throughout the life sciences & health, social sciences, geosciences, and the humanities. More information.