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.

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.

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.

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.

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.

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.

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.

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).

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).

Based on the submitted documents, a preselection of applicants is invited to a selection interview. The interviews are conducted as video conferences and are part of the selection procedure.

All international applicants must also complete an online aptitude test.

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.

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.

• 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".

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.