Courses are held in English.
The start of the programme is the winter semester, which begins on 1 October. Lectures start in the second or third week of October, with welcome events taking place before.
Lectures take place in person between Monday and Friday and regular attendance is required to pass. Certain lectures, seminars or practicals may also take place as block courses or on irregular dates. This information is made available to attending students in the course catalogue.
It takes four semesters – two years – to complete the programme. During this time, the lecture-free periods (mid-July to October; mid-February to April) allow time for self-study, internships or other activities. Exams, excursions, and irregular, elective lectures may be scheduled during the lecture-free periods.
Up-to-date information on lecture times may be found on the academic calendar.
All applicants: 31 May for the following winter semester.
The dates may change. Please find more information here.
This Master's degree programme imparts skills that are necessary in order to handle the advancing digitisation of many areas of the physical and life sciences. This concerns topics such as the collection, processing, analysis and interpretation of large digital data sets. To this end, the Master's degree programme conveys the key aspects of modern data science, which is characterised by a blending of the central fields of mathematics, statistics, computer science and machine learning, taking application-related issues into account. With in-depth education in the corresponding branches of mathematics, statistics and computer science as well as in the relevant application fields of the physical and life sciences that engage in quantitative work, this programme imparts the skills needed to recognise the relevant problems in data analysis, develop and apply appropriate mathematical or computer science solutions and correctly interpret the results within the specific application context.
The following profile areas are offered to students:
Data Science in the Life Sciences: The Life Science track is designed for students aiming to apply data science methodologies to biological, biomedical, and health-related fields. This specialisation integrates core data science principles with domain-specific knowledge pertinent to the life sciences.
Data Science Technologies: The Data Science Technologies track is tailored for students aiming to deepen their expertise in computational and algorithmic aspects of data science. This specialisation emphasises advanced technical skills, preparing graduates for roles in software engineering, artificial intelligence, and big data infrastructure.
Overview
The Master’s degree programme comprises 120 credits. These credits are split between modules totalling 90 credits and the Master’s thesis with its accompanying colloquium, which comprises 30 credits.
The Master's degree programme is divided into a fundamental area comprising 30 credits (to be completed in the first semester) and a profile area comprising 60 credits (second and third semester). The Master’s thesis is usually written in the fourth semester.
Fundamentals
The following modules must be completed as part of the fundamental area comprising 30 credits:
It is recommended students complete the modules of the fundamental area in their first semester.
Profile
In the second and third semester, students may specialise in one of the following two profiles:
Students of both profiles must complete a mandatory module "Ethical Foundations of Data Science" and a 15 credit elective area, in which complementary courses from the other profile or other programmes can be selected.
Master's thesis with accompanying colloquium
The Master's thesis is usually written in the fourth semester after at least 60 credits have been completed. The processing time is 23 weeks. During this time, the students should give a presentation on the progress of their work.
For more details, please see the programme website and study regulations.
Students selecting the profile Data Science in the Life Sciences must complete the "Research Practices" module, which may be completed through an internship.
In total, the semester contribution amounts to 326.40 EUR. It includes a fee of 181.40 EUR for the transportation ticket contribution. This allows you to use local public transport in Berlin and nationwide for free. Other costs covered by the semester contribution include a 50 EUR enrolment fee, a 85 EUR semester contribution to the student support service ("studierendenWERK Berlin"), and a 10 EUR contribution to the student union.
Compared to other European countries, the cost of living in Germany is quite reasonable. However, the cost of living has also risen somewhat in Germany in recent years. The prices for food, accommodation, clothing, cultural events, etc. are slightly above the EU average. You will need around 900 to 1,300 EUR each month to cover your living expenses. The biggest expense is monthly rent, which is between 400 and 700 EUR in Berlin.
The Deutschlandstipendium scholarship allows students at Freie Universität Berlin of all nations and all parts of society to fully concentrate on their studies. The programme supports talented students with 300 EUR per month. To apply, you already have to be enrolled within the standard time to degree during the funding period or have a letter of acceptance to start a degree programme at Freie Universität Berlin.
For admission to the Master’s programme, applicants must fulfil the following admission criteria:
First Degree
You need to have completed, or be in the process of completing, a first university degree (Bachelor's or equivalent), either from Germany or an equivalent foreign degree, in a higher education programme comprising at least six semesters or 180 ECTS.
Computer Science & Mathematics
Your first degree must be a Bachelor of Science in computer science or a first degree in a different subject. If your degree was in a different subject, your previous studies must include at least 20 ECTS in mathematics and at least 10 ECTS in computer science.
The 20 ECTS in mathematics must contain at least 5 ECTS in linear algebra or calculus and at least 5 ECTS in probability theory or statistics.
The 10 ECTS in computer science must contain at least 5 ECTS in algorithms and at least 5 ECTS in a higher programming language, e.g. C/ C++, Java or Python.
More Information
You can find more information for prospective students on our homepage. Please also read our FAQ.
If you are an applicant who received their university degree outside of Germany, you need to apply to Freie Universität Berlin via uni-assist. Uni-assist will check your documents and forward them to the respective university.
Before you apply, please read our homepage concerning application procedures, and admission requirements.
For all inquiries about the application process, admission, enrolment, orientation at Freie Universität Berlin, etc., please contact the Student Services Centre: Info-Service@fu-berlin.de.
Proof of English language skills (level C1 CEFR or equivalent) is required.
All applicants: 31 May for the following winter semester.
The dates may change. Please find more information here.
The application must be submitted online: https://my.uni-assist.de/.
For further information, please also see: Application with non-German degree.
There are many ways of earning money while you study, for example as waiting staff, academic assistants, or private tutors. Knowledge of German will improve your chances of finding a part-time job, but it isn’t necessarily required. However, it is important to be aware of the legal regulations.
The student support service at the university, called "studierendenWERK Berlin", and the local representative of the "Bundesagentur für Arbeit" (Federal Employment Agency) can provide information about jobs for students. When searching for a job, look at online job boards, notice boards on campus, and ads in local newspapers.
You have the option to stay in a public/private student dormitory or in a private (shared) apartment. Student dormitories are not administrated by the university itself, so Freie Universität Berlin does not have any on-campus housing. However, it works together with "studierendenWERK Berlin" regarding student accommodation.
If you do not wish to stay in a student dormitory, you can try to find a room or an apartment on the private housing market. Many students in Berlin live in shared apartments ("WGs"). You can find these offers online (e.g. WG-Gesucht or Kleinanzeigen) or on notice boards on campus.
Available rooms/apartments near the university are rare. Therefore, students mostly commute from other parts of the city. The commute via public transportation usually takes between 30 minutes and an hour, which is considered a normal travel time in Berlin due to the size of the city.
The Career Service of Freie Universität Berlin aims to support international students at Freie Universität by providing information, advice, and events related to career planning, internships, and job applications.
The International Student Support team at FU Berlin regularly offers information events that include Q&A sessions. While personal office hours aren't available due to team size, students can contact the "Info-Service Study" for general inquiries or the General Academic Advisory Service or Psychological Counselling for complex concerns. The team also enhances expertise in international affairs, contributing to FU Berlin's internationalisation process.
To activate the map, click on the "Show map" button. We would like to point out that data will be transmitted to OpenStreetMap after activation. You can find out more in our privacy policy. You can revoke your consent to the transmission of data at any time.
