Master's Degree

Applied Data Science M.Sc.

This research-oriented master's programme deepens key methods in data science and combines them with an application area, practical experience, and interdisciplinary research.

Studienabschluss

Master of Science (M.Sc.)

Standard Duration

4 Semesters

Start of Studies

Winter and Summer Semester (winter semester recommended)

Language of Instruction

mainly English

Admission Restriction

restricted admission

Credits

120 ECTS

Contents

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What You Will Study

Data science focuses on extracting knowledge from data and on the techniques required to process large and partly unstructured data sets. During your studies, methods from mathematics, computer science, and statistics are combined with expertise from an application area.

The Göttingen Master's in Applied Data Science is distinguished in particular by its interdisciplinary profile. You will gain advanced knowledge of the core methods of data science and learn how to apply them in an application area. At present, you can choose between the application areas Computational Neuroscience, Bioinformatics, Medical Data Science, Digital Humanities, Computational Sustainability, Digital Business Administration, and Physical Modeling and Data Analysis.

In this research-oriented master's programme, you learn how to develop and communicate scientific methods and findings further through your own research projects. You also gain skills for reflecting critically and ethically on the data you use, on the consequences of extensive data collection and analysis, and on the implications of partially automated, data-driven decision-making. In addition, the programme offers opportunities for internships and collaboration with partners from industry.

Programme Structure

The Master's in Applied Data Science is an advanced degree programme in which you must successfully complete coursework worth 120 credits. The programme consists of three areas of study: (1) the core academic studies, (2) the professionalisation area, and (3) the master's thesis module. Teaching is mainly in English.

Core Academic Studies

In the core academic studies, you gain in-depth knowledge of the methods from computer science, mathematics, and statistics that are relevant for data science. You work with technical infrastructures and machine learning as well as statistical models and ethical questions in data science. This part of the programme consolidates the foundations you need in order to apply and further develop specialised methods of the field in interdisciplinary contexts.

Professionalisation Area

The professionalisation area allows you to shape your profile according to your individual interests, subject-specific preferences, and career goals while acquiring professional and interdisciplinary key skills. A central element of this area is the application field. At present, you can choose between the application fields Computational Neuroscience, Bioinformatics, Medical Data Science, Digital Humanities, Computational Sustainability, Digital Business Administration, and Physical Modeling and Data Analysis.
In the professionalisation area, you also complete an internship to strengthen your professional qualifications. You can choose between a laboratory internship and an internship in industry.

Master's Thesis Module

After successfully completing a total of 90 credits in the core academic studies and the professionalisation area, you write your master's thesis to complete the programme.


A detailed, interactive overview of the programme structure is available here (external link):

You can find the module catalogue under Regulations.
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Application Areas

You choose one of the following application areas: Computational Neuroscience, Bioinformatics, Medical Data Science, Digital Humanities, Computational Sustainability, Digital Business Administration, and Physical Modeling and Data Analysis.

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Career Perspectives

Career prospects for students with solid knowledge in data science are excellent and are likely to remain so because of the increasing digitalisation of business, academia, and the public sector. Potential employers can be found in IT, banking, insurance and reinsurance, consulting firms, public research institutes, development and research departments in companies, higher education institutions, and public healthcare. Graduates are qualified to take on independent responsibilities and lead projects. They are also well prepared to found their own start-ups, for example in the role of CTO. Particularly strong academic performance may also open the way to doctoral studies.

Admission Requirements

Academic Qualifications / Admission Conditions

A bachelor's degree comprising at least 180 credits is required. If the bachelor's degree has not yet been completed, at least 135 credits are required in order to apply.

You must demonstrate at least 60 credits in foundational methods of data science. This is normally fulfilled by a bachelor's degree in data science, computer science, statistics, mathematics, or a closely related field. If you have fewer than 60 credits in these areas, you may make up up to 15 credits during your master's studies.

The legally binding admission requirements are those described in the "Regulations on Admission Requirements and Admission" (see Regulations).

Language Skills

English language proficiency at CEFR C1
or
English language proficiency at CEFR B2 and German language skills corresponding to DSH level 2.

Proof is required. An overview of possible proof of English proficiency can be found here.

The legally binding admission requirements are those described in the "Regulations on Admission Requirements and Admission" (see Regulations).

Aptitude Test and Personal Interview

All non-EU applicants have to pass an online aptitude test, which examines basic knowledge in Mathematics, Statistics and Computer Science. After the application deadline, you will receive an email containing a personal link to the aptitude test and login credentials. The test will take 40 minutes and has to be completed within a few days. The test result will be part of the selection procedure.

Additionally, you will be invited to a personal interview if you are on the shortlist for the programme. The interviews are conducted as video conferences and are part of the selection procedure.

Important note for future applicants

For future application cycles (starting with the intake for the Summer Semester 2027), we are planning to revise our selection procedure . Instead of the online aptitude test, applicants will have the opportunity to submit results from the dMAT Data Science.

The dMAT Data Science is offered by g.a.s.t. e.V. (Gesellschaft für Akademische Studienvorbereitung und Testentwicklung) in cooperation with lot of test centres all around the world. Please be advised that the next – and only – test offer before the application deadline is on 9th June 2026. For test registration, further information and sample tests, please follow the dMAT Website.


We strongly encourage all prospective applicants to take the dMAT Data Science, as a good test result can significantly enhance your chances of admission and strengthen your application profile. Applicants who do not take the test will still be considered in the selection procedure. However, in a highly competitive selection procedure as ours, submitting a good test result will be an advantage.

The changes mentioned above are based on advanced planning and are subject to final approval by the relevant university bodies.
Please check our website regularly, we will provide further confirmation as soon as possible. [Last updated: 9 April 2026]


The current application and selection procedure for the winter 26/27 intake with application deadline on 1 May remains unchanged. All applicants in this cycle will still receive the invitation for the mandatory online aptitude test a few days after the application deadline.

Eligibility Check

We do not offer individual checks of your eligibility for admission. All relevant information can be found in the admission regulations. Questions about eligibility cannot be answered.

Application

Application Documents

An online application form must be completed in order to apply. The following documents are required:

  • Degree certificates (in one file, German or English) [PDF]
  • A tabular curriculum vitae (CV) in German or English [PDF]
  • Proof of sufficient English language proficiency [PDF]
  • If applicable: proof of sufficient German language proficiency [PDF]
  • A letter of motivation (up to 300 words) in German or English explaining which specific skills and interests qualify you for the programme.

Prepare all documents in advance, that is, before starting the online application procedure. Make sure that the scanned documents are correctly formatted and available at an appropriate resolution. The file names should also be self-explanatory.

Please note that the entire application procedure is conducted online. No original documents are required for the application process, only scanned copies.

To submit the application form successfully, JavaScript must be enabled in your browser.

Application Deadline

  • May 1 for applications for the winter semester
  • November 1 of the previous year for applications for the summer semester
Further information can be found under "Go to the Application Form".

Go to the Application Form

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Admission Notification

All applicants are informed of the admission decision by email. The selection process usually takes several months.
Unfortunately, we cannot answer status enquiries about your application.

Contact

Office of Student Affairs Computer Science

Student Advisory Service
Goldschmidtstr. 1
37077 Göttingen

studienberatung@informatik.uni-goettingen.de