In this master’s course, skills are imparted that are required to deal with the advancing digitization of many areas of society and the natural sciences. This applies, for example, to the acquisition, processing, analysis and interpretation of large digital data sets. The master’s course conveys the central aspects of modern data science, which is characterized by the amalgamation of the central fields of mathematics, statistics, computer science and machine learning, taking application-related issues into account. Through in-depth training in the corresponding sub-areas of mathematics, statistics and computer science, as well as in the relevant quantitative application fields of natural, social,
The course is divided into a basic area with the modules
and a profile area with specializations
The course and examination regulations regulate the exact structure and course of the course. It describes the content, type and requirements of the compulsory and elective modules.
The master's thesis with 30 CP should show that the students are able to work on a research task independently using scientific methods and to present the results in writing and orally. After successfully completing the study program, the university degree Master of Science (M.Sc.) is awarded.
Modules of the course
Compulsory modules of the basic area
|module||Statistics for Data Science|
|module||Machine learning for data science|
|module||Programming for Data Science|
|module||Introduction to Profile Areas|
Selection of elective modules in the profile area
|module||Ethical Foundations of Data Science|
|module||Data Science in the Social Sciences|
|module||Data Science in the Life Sciences|
|module||Selected topics of data science technologies|
|module||Database systems data science|
|module||Cognitive Neuroscience for Data Science|
|module||Natural Language Processing|
|module||Data Science software project|
The graduates are prepared for a professional management position in a wide variety of fields of activity that go hand in hand with the collection, administration, processing, analysis and interpretation of digital data. These include, for example, the areas of internet economy, health or Industry 4.0 or corresponding facilities in industry, research and administration.
To be admitted to the master’s degree, applicants must demonstrate the following requirements:
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