Master's programs in Data Science: GI and Plattform Lernende Systeme offer recommendations

Data form the basis of an increasingly digitally networked society. The ability to use them to generate insights for science and beneficial applications for society and business is becoming a key competence. The Gesellschaft für Informatik e.V. (GI), in collaboration with Plattform Lernende Systeme, has published recommendations for the design of Data Science master's degree programs. They are intended to serve as a basis for the accreditation of corresponding study programs.

Download the white paper "Data Science" here (in German)

In an increasingly digitally networked world, the competent handling of data is becoming more and more important. This is true in business as well as in science, whether in the natural, life and engineering sciences or in the social and societal sciences. Colleges and universities are responding to the high demand and clear shortage of qualified data scientists by offering more and more data science courses. The AI map of Plattform Lernende Systeme provides a good overview of what is on offer. However, there are still no uniform standards for data science courses.

This is where GI and Plattform Lernende Systeme come in. They have developed recommendations for the design of data science master's programs based on a bachelor's degree in (business) computer science or mathematics. These are intended to provide guidance to those responsible for developing Data Science courses at colleges and universities. The goal is to enable students to acquire all the skills necessary for data analysis processes and to competently manage data science projects in various application domains.

Basis for accreditation of study programs

The recommendations form a basis for the accreditation of corresponding study programs. They are to be understood as minimum standards and are divided into the areas of mathematics and statistics, computer science and programming, data science methods, interdisciplinary aspects and the application of data science in the domain. They leave room for specific program profiles of colleges and universities.

The recommendations for Master's programs are based on the working paper Data Science: learning and training content published in December 2019, which was also jointly produced by GI and Plattform Lernende Systeme. In the first step, the paper addresses people who already have a relevant bachelor's degree in computer science, mathematics, statistics, or comparable fields and who aspire to work as a data scientist in research or industry.

The "Recommendations for Master's Programs in Data Science" are available for download here (in German).

Further information:

Linda Treugut / Birgit Obermeier
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