The digital transformation of our world is creating a constantly growing treasure of very large amounts of often unstructured data. Here, unstructured means that the data is difficult to process by machine because it is not organized. The field of Data Science deals with the development and application of methods to gain insights from such data. For example, medical findings as well as X-ray images are easy for doctors to interpret and it is easy for them to link the information from both data sources to form an overall picture. However, this is still very difficult for intelligent systems that could support doctors in their work. Another example of a Data Science problem is using aerial images to assess how healthy a field is in order to take effective action against plant pests and diseases with as little intervention as possible.

Data Science is located at the intersection of Mathematics, Computer Science, Statistics and Machine Learning. Therefore, students learn the fundamentals of Computer Science and Mathematics as well as in-depth knowledge of data analysis in the Bachelor’s programme Applied Data Science. This includes Machine Learning, Statistics, Data Literacy, Data Protection and Privacy, Data Infrastructures and High-Performance Computing.

The Göttingen study programme is characterized in particular by its interdisciplinary profile - not only in the fundamentals. As good data scientists require not only methodological knowledge but also expertise in the field of the data to be processed, students choose an application domain in which they learn to apply the methods of Data Science. As a basis for this, you attend subject-specific courses from the respective areas. You can currently choose between Digital Business Administration, Biology/Bioinformatics, Digital Humanities, Medical Informatics, Breeding Informatics, Physical Modeling and Data Analysis as well as Computational Sustainability. It is possible to visit courses from more than one of the application domains.

Students are also ideally prepared for the often international working environment thanks to a growing range of courses taught in English. With "Machine Learning", one of the advanced compulsory modules is taught in English. Of course, students have the opportunity to attend an English course as part of their studies if required.

A total of 180 ECTS has to be completed in order to earn the Bachelor's degree.

The programme is divided into three fields of study: core curriculum, area of professionalisation and the Bachelor's thesis.

• Fundamentals of Computer Science:

  What are the basics of automated data processing with computers?

  Fundamentals of Computer Science, programming, databases

• The mathematical foundations of Data Science:

  Which mathematical concepts do I use to analyze data and let computers learn?

  Analysis, Linear Algebra, Probability Theory

• Fundamentals of Data Science:

  How do I gain insights from data?

  Statistics, Data Literacy, Machine Learning

• Elective area »Data Science«: specialization in the field of "Infrastructure and Processes" or in the field of »Data Analysis«.
• »Application domain«: specialization in one of the seven application domains. It is possible to gain insights into several application domains.
• Practical project and internship: Practical work in a team and collaboration in a research group.
• Key skills: among others, programming in Python and dealing with the ethical aspects of Data Science. There is also the opportunity to attend language courses or acquire soft skills, e.g. in rhetoric or intercultural competence.

• The Bachelor's thesis can be written in one of the application domains as well as in the methods of Data Science.
• Prior to the Bachelor’s thesis (worth 12 ECTS) students are required to attend a course on scientific writing (worth 3 ECTS) which also includes giving and receiving peer review during the thesis writing process.

Detailed information on the structure of the degree programme, the application domains and all the modules can be found in the directory of modules, available at "Regulations" in the right-hand column. Sample study plans can be found in the examination and study regulations. You can also click through the programme and its contents in detail in our interactive study structure: (external link, in German): https://prezi.com/view/Br4ctKuETohm4iALiNwe/

Data Scientists are currently in demand in almost all disciplines, both in research and in business. Possible employers can be found for example in marketing, banks, insurance companies, the IT sector, management consultancies, public research institutes , in the pharmaceutical sector (clinical trials), in the public health sector as well as in colleges and universities.

Given the proximity of the training to the application domains directly at the university, research departments dealing with data-driven research in the domains in question are prospective areas of work. In all of these domains, there is currently a lack of specialists in Germany.

Please refer to: Entry requirements at Göttingen University

The Bachelor's degree programme "Applied Data Science" is a German-language program. Therefore, sufficient knowledge of the German language is required.
Advanced knowledge in English is recommended.

See more at: Language requirements for international prospective students

Those who choose Applied Data Science as a field of study should be interested in both a mathematically formal and an application-oriented practical approach.
The ability to work in a team is an important prerequisite for later professional life.
Specialized technical knowledge, especially in programming, is not a prerequisite for this programme.

Open admission (Enrollment without prior application)
Application Guide

Open admission (Enrollment without prior application)
Application Guide

Open admission
(Application at International Studies)