Admission requirements

Required is

• a Bachelor's degree in Business Informatics, Mathematical-Technical Software Development, Computer Science or Mathematics with a minor in Computer Science from the FernUniversität in Hagen or a Bachelor's degree in Data Science, in Business Informatics, in Mathematical-Technical Software Development, in Computer Science
• or in Mathematics with a minor in Computer Science from another university or an equivalent degree, which covers at least 50% of the content of these degree programmes and at least 40 ECTS points in Computer Science as well as at least 20 ECTS points in Mathematics.

Details

The Master's programme "Data Science" at FernUniversität in Hagen is designed for students who wish to expand their qualifications in the field of Data Science. The programme builds on a first professional qualification, preferably in the fields of Computer Science and Mathematics. Professionals who are confronted with data analysis and data-related issues and who are interested in academic deepening are also addressed. The programme lies at the intersection of Computer Science and Mathematics and aims to qualify graduates to consider future developments in the field of Data Science.

The teaching content covers the entire Data Science Life Cycle. Graduates should be able to independently carry out Data Science projects, evaluate and use appropriate tools, and answer economic questions in this context. For this purpose, mathematical and algorithmic fundamentals are taught, programming skills in relevant languages such as Python or R are deepened, and the role of Data Science in companies is illuminated.

The teaching methods include a Blended Learning system, which offers a combination of study materials sent by post, digital media, and virtual seminars. Students are expected to work cooperatively online, communicate, and be able to meet for on-site events at campus locations. The accreditation of the programme by the Accreditation Council confirms the high quality of the curriculum and the practical relevance of the learning content.