- Degree
- Master of Science in Data Science
- Course location
- Berlin
- Teaching language
- • English
- Languages
- Courses are held in English.
- Full-time / part-time
- • full-time
- Programme duration
- 4 semesters
- Beginning
- Winter semester
- Additional information on beginning, duration and mode of study
- 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 (https://www.fu-berlin.de/en/studium/beratung/kalender/index.html).
- Application deadline
- All applicants: 31 May for the following winter semester.
The dates may change. Please find more information here (https://www.fu-berlin.de/en/studium/bewerbung/master/konsekutive-masterstudiengaenge/index.html).
- Tuition fees per semester in EUR
- None
- Combined Master's degree / PhD programme
- No
- Joint degree / double degree programme
- No
- Description/content
- 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.