Complementary Subject Area Digital Science

The Complementary Subject Area Digital Science (Ergänzung Digital Science) of 30 ECTS credits is offered to bachelor and master students from a wide range of backgrounds. 

Goal: The Complementary Subject Area Digital Science is designed to augment the students’ skill set and open the door to new career opportunities in the age of digitalization. It provides a solid foundation in digitalization relevant to students’ disciplines. It conveys generic skills required for automated data analysis and offers a selection of courses on specific technologies, methods and aspects related to students’ majors. Finally, it offers the opportunity to conduct a complete data-based decision-making process under the individual supervision of our teachers. To assure high effectiveness of learning, interdisciplinary groups are kept small and vary from 20 to 40 students.

Expected learning outcome: Upon successful completion of the Complementary Subject Area Digital Science, students are capable of applying fundamental methods in the field of digital science. They understand methods and techniques from the fields of programming, data management and data analysis. They are aware of the broad context of digitalization. They are able to apply techniques of digital science to their field. 

Structure and content overview 

The Complementary Subject Area Digital Science combines information technology skills and mathematical and statistical knowledge all embedded in the substantive expertise from students’ study majors. 

  • Information technology skills are required to manage data, to automate processes and to make them replicable. 
  • Mathematical and statistical knowledge is necessary to understand and meaningfully apply statistical models and machine learning methods. 
  • The substantive expertise is needed to be able to find sources of data and meaningfully interpret results obtained from the data analysis.

The package consists of five modules with, in total, six courses of 5 ECTS credits each. Half of the courses focus on generic skills (1-3.a) and a half on domain-specific skills and applications (3.b-5). 




The following learning outcomes are expected under the successful completion of the particular modules.

Module 1: Introduction to Programming: Students understand the basics of a programming language used in data analysis. They acquired the ability to use the most important control flow and data structures in the programming language in order to develop their own programs.

Module 2: Introduction to Data Management: Students understand the basics of data management, which are used in the area of data analysis. They are able to deal systematically with data and metadata and have the ability to organize and manipulate data. In addition, they learned selected aspects of conversion, quality assurance, reuse and retention of data.

Module 3: Data Analysis: Students understand the basics of data analysis. They acquired the ability to use selected methods of data analysis and are capable of interpreting data and present it verbally and visually.

Module 4: Aspects of Digitalization: Students know selected topics relevant to the digitization of their discipline. These topics include, but are not limited to, aspects related to humanities, social sciences and economics but also more general ethical and legal aspects. Students have acquired the ability to apply the methods of the subjects learned in their discipline.

Module 5: Data Analysis Lab: Students apply learned methods of data analysis within individual projects. They lead an exemplary data-based decision-making process from the inquiry, through the data analysis, the data interpretation to the evaluation of the data-based decisions. They are able to conduct a similar process in their field of study.

Admission and References

The Complementary Subject Area Digital Science can be taken within bachelor and master programmes without any restrictions on students’ background or prior experience. It offers flexibility in content and structure to meet the needs of diverse academic programmes. Moreover, the courses are offered mostly at off-peak hours. 

There are two options to take courses:

  • as the complete package of 30 ECTS credits, if a study major programmes incorporate complementary subject areas, 
  • as individual courses (each 5 ECTS credits) within the module Non-disciplinary/Interdisciplinary Skills and the module Individual Choice of Specialisation.

It is possible to initially take individual courses and have them accredited later when the programmes incorporate complementary subject areas. Study deans may provide information about future integration plans. 

For more information please check the following resources.

  • The formal description of the Complementary Subject Area Digital Science and its modules can be found in the university bulletin (in German). 
  • The list of the current and upcoming courses given by DiSC’s teachers can be found in the courses’ catalogue.
  • For studying related issues, please subscribe to DiSC@OLAT, which was created as an information exchange platform for students interested in courses related to digitalization. We provide there a list of currently open and planned courses, suggested studying order, news, a discussion platform, and more. 
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