All mandatory modules as well as a good selection of elective modules are taught in English so that the programme can be completed in English only. Additional modules taught in German extend the range of possible elective courses.
Application period for a start in the winter semester: 1 May – 15 July
There is a limited admission window, 1 December – 15 January, for a start in the summer semester. This admission window is strictly restricted to applicants who obtained their first degree in an EU country and who fulfil all requirements for direct admission without aptitude evaluation. Please consult the programme web pages whether you might be eligible. In general, we recommend starting the programme in the winter semester.
The successes of artificial intelligence, especially machine learning, impressively demonstrate the potential of mathematical and statistical methods. They enable us to recognise hidden correlations in large amounts of data using automation and make them usable in a targeted manner. The Master's degree programme in Data Science imparts in-depth knowledge of modern methods of data analysis and machine learning and combines theoretical principles with practical applications. The course focuses on
Through this interdisciplinary orientation, students acquire both methodological expertise and the ability to solve complex data problems in scientific and industrial contexts.
The programme offers a core set of modules that provide a solid foundation in mathematics, statistics, the fundamentals of data science and machine learning, as well as interdisciplinary opportunities:
“Mathematics for Data Science” (10 ECTS credit points) in the first semester establishes the fundamental mathematical concepts from analysis and linear algebra and, where necessary, fills any gaps due to differences in students’ Bachelor education.
“Principles of Data Science” and “Principles of Machine Learning” (10 ECTS credit points) form the disciplinary core; one of the two must be taken and both may be taken.
5–10 ECTS credit points in statistics and/or probability. Students can choose from several modules which rotate from year to year.
5–10 ECTS credits points in any area of (applied) mathematics. Students can choose from several modules that rotate from year to year.
“Advanced Programming” (5 ECTS credit points) teaches efficient implementation of advanced mathematical and statistical algorithms in Python.
“Database Management” (5 ECTS credit points) focuses on structured handling of big data, databases, and data analytics.
“Operations Research” (5 ECTS credit points) covers linear and integer optimisation with applications.
The “Applied Data Science Project” (10 ECTS credit points) is an independent team project in which data science methods are applied to solve a real-world problem.
“Ethics and Law” (5 ECTS credit points) addresses the ethical and legal issues arising from the collection and analysis of data.
Students also take one “Studium.Pro” (5 ECTS credit points) transdisciplinary module.
A further 20 ECTS credit points can be freely chosen from the modules with relevance to data science from the existing course offerings in any of the following KU degree programmes:
Interdisciplinary Master’s in Mathematics: all modules
Interdisciplinary Master’s in Mathematics – Applications in Physical Geography: most modules
Interdisciplinary Master’s in Mathematics – Applications in Economics: most modules
Master’s in Business Analytics and Operations Research: some modules
Bachelor’s in Mathematics: Selected modules
Bachelor’s in Data Science: Selected modules
Finally, students complete a Master’s thesis (30 ECTS credit points).
Machine learning and mathematical methods are being developed worldwide and applied across borders. For this reason, the course of study has a consistent international focus and is primarily offered in English. This creates ideal conditions for a career in globally active companies and at the same time facilitates the integration of international students. The English-language study programme creates a diverse, intercultural environment that promotes professional and personal exchange.
There is the opportunity to spend a semester abroad in the third semester and gain valuable international experience. Our students benefit from the KU's global network – the university maintains partnerships with more than 300 universities around the world. Whether North America or Asia, Australia, South America or Europe, you will find the right programme for yourself. The KU International Office provides support with planning and organisation of stays abroad.
78 EUR per semester
The costs of living in Ingolstadt or Eichstätt are relatively low compared to large university cities. Rental costs in subsidised student residences (offered by the Studentenwerk Erlangen, the Canisius-Stiftung or the St Gundekarwerk) range between 300 EUR to 400 EUR per month depending on size and furnishing. Rental costs in privately owned residences are slightly higher and range around 750 EUR per month in Ingolstadt. In Eichstätt, rental costs are generally slightly lower. All KU students can eat in the university’s canteen at favourable prices. The price for a main dish is between 3.50 and 5.50 EUR. Health insurance costs are approx. 140 EUR per month. In total, you should plan for monthly costs of 1,000 EUR, possibly less in Eichstätt.
The KU offers academically qualified international students in financial need a scholarship (approximately 450 EUR per month). Scholarships are awarded for a period of five months. There is no automatic extension, but it is possible to reapply.
Please find more information on financial issues, scholarships and prerequisites on our website.
You are required to have, or expect to complete, a Bachelor’s degree in Data Science, Mathematics, Statistics, Computer Science, Physics, or a closely related field.
It is expected that your Bachelor’s degree substantially covers the core subjects of a Bachelor’s degree in Data Science as taught at KU, which entail the following:
Solid mathematics background consisting of at least one year of Linear Algebra and one year of Analysis, including fundamental proofs, as well as a first introduction to Optimisation (reference modules are the KU modules Linear Algebra I and II, Analysis for Data Science I and II, and Optimisation for Data Science)
Basic knowledge in probability and statistics (reference modules are the KU modules Introduction to Statistics and Introduction to Stochastics)
Basic knowledge in algorithms and programming (reference modules are the KU modules Algorithms and Data Structures and Introduction to Programming).
In addition, you are expected to have taken more advanced classes in at least some of these subjects. Applicants should fill in a self-assessment form as part of their application. The purpose of the form is to guide applicants on whether their academic background is sufficient to begin a Master's degree in Data Science. Note: It is not necessary that all requirements are satisfied or that modules match perfectly. However, you should be able to find a positive match for the majority of the modules named.
If you have not fully covered all of the core modules listed above, you may still be admitted, but you may be required to retake one or more Bachelor’s modules. These modules cannot be applied toward the Master’s degree requirements.
Applicants from non-EU countries are strongly encouraged to submit the results of a standardised test, ideally the GRE subject test Mathematics.
Application period for a start in the winter semester: 1 May – 15 July
There is a limited admission window, 1 December – 15 January, for a start in the summer semester. This admission window is strictly restricted to applicants who obtained their first degree in an EU country and who fulfil all requirements for direct admission without aptitude evaluation. Please consult the programme web pages whether you might be eligible. In general, we recommend starting the programme in the winter semester.
It is possible to find a job as a student assistant ("Hiwi") by contacting professors and university departments directly. Information on current job vacancies can also be found on the website of each chair.
There are also different offers for temporary part-time jobs outside the university, for example, in restaurants or in shopping malls. Eichstätt and Ingolstadt are the cities with the lowest unemployment rates in Germany.
The International Office at the KU offers a housing service. It helps international students find accommodation, and it facilitates the contact between students and the future landlord or landlady. This service is free of charge. However, a housing service deposit is charged, and this will be refunded at the end of your rental contract. Please find more information on housing at the KU here.
German language courses offered by KU's language centre during the semester are free of charge.
Pre-semester language courses are fee-based.
Studying at KU is more than just acquiring specialist knowledge. We broaden our horizons together and take responsibility in and beyond the individual degree programmes. KU has a particular focus on topics such as personal development, sustainability, social skills and social commitment.
KU was ranked "Most Popular University in Germany" in 2021, 2022, 2024, and 2026 by the online platform StudyCHECK.de, one of the most prominent information sites for studying in Germany. This award confirms the ideal study conditions at the KU. Our 5,000 students are able to work and learn in a friendly and welcoming atmosphere. They benefit from personal supervision, interdisciplinary study offers, excellent facilities, a well-stocked library, a broad range of sports and leisure activities, comprehensive support from the KU International Office, and a large global network with over 260 partner universities.
The Catholic University of Eichstätt-Ingolstadt (KU) is the only Catholic university in the German-speaking world. It is fully accredited, meaning that the degrees and qualifications it awards are equivalent to those issued by German state universities. The KU is committed to its cosmopolitan character and warmly welcomes students of all denominations and faiths, as well as students of no religious belief.
The degree programmes in Data Science are centred at the Mathematical Institute for Machine Learning and Data Science (MIDS). It is located in the historic buildings of the first Bavarian university which was founded in 1472, moved to Landshut in 1800 and has been located in Munich since 1826 as Ludwig-Maximilians-Universität. Ingolstadt's history as a university town continued 188 years later. In 1989, the KU Faculty of Economics opened in Ingolstadt. In 2023, the foundation of the MIDS marked the return of university life to the historic city centre.
Ingolstadt, with about 135,000 inhabitants, is the dynamic centre of a culturally and economically growing region. It is one of the cities with the youngest, most diverse, and fastest growing population in Germany. The theatre, the AUDI summer concerts, the jazz days and the Museum of Concrete Art are just a few of the cultural highlights. In a historical setting, a large number of restaurants, clubs and pubs invite you to unwind after lectures and seminars often just a few steps away from campus. The day can also be spent relaxing on the Danube beach or at the lake. And of course, as in any Upper Bavarian city: enjoy the local beer gardens for a "Brezel" and a beer or two. And if you yearn for something more cosmopolitan, the centre of Munich is only a 40-minute train ride away.
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