Master Data Science
The MSc in Data Science combines thorough methodological understanding, state-of-the art methods and challenging applications. It extends the knowledge learned in preceding BSc programmes to lead to towards cutting-edge research and industry applications.
At a glance
The MSc Data Science offers a comprehensive education in the concepts and methods of data science, incorporating knowledge and methodology from Computer Science and Mathematics. Special emphasis is placed on the sound training of fundamental (mathematical) concepts so as to be able to competently assess the properties and limitations of the methods. The main topics are:
- Machine Learning, AI, and Deep Learning
- Statistics, Matrix Algorithms, and mathematical foundations of ML
- Data Structures, Algorithms and Optimizations for Big Data
- Data Engineering with Big Data Infrastructures and Data Wrangling
Highlights
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Joint programme in of CS and Mathematics departments, providing both conceptual foundations and real-world applications
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Taught in English (some elective courses in German)
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Close connections to industry and research, including the interdisciplinary Center for Advanced Analytics and Predictive Sciences
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No tuition fees for any student at UniA
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Small group sizes in lectures and practical sessions ensure excellent and personalised support.
- Renowned computer science faculty in the CHE ranking.
- Active student community with regular events and activities.
Before the Study
Examination Modules
The Master's programme in Data Science consists of a total of 120 credits and, according to the current examination regulations for 2025, comprises the following assessment areas:
- Core Data Science Methods (32 credits)
- Advanced Data Science Methods / Electives (at least 36 credits)
- Scientific Project Work
- Data Science Project (10 credits)
- Seminar: Mathematics and Computer Science (4 credits each)
- Social Aspects of Data Science / Ethics (4 credits)
- Master's Thesis (30 credits)
Core Data Science Methods
The Core Data Science methods should be taken at the beginning of the programming, as they firmly establish a common background as well the set of required methods.
These courses pick up subjects taught in preceding Bachelors’ programs, deepen the knowledge and focus on the specifics of data science.
In Computer Science, the main areas are Algorithm Analysis and Design for Big Data, Data Engineering for Data Preparation/Quality. and Machine Learning with a focus on probabilistic methods.
In Mathematics, the main topics are Statistical Learning Theory, analytical foundations of deep learning and approximation with surrogate models, advanced matrix and optimization methods.
Advanced Data Science Methods / Electives
Scientific Project Work
Seminars
The goal of seminars is to train the ability to research complex scientific topics, report and present them in the student’s own words and discuss complementary works, also in small groups. Two seminars need to be taken, one in Mathematics and one in Computer Science as to stress each discipline’s specific approaches.
Data Science Project
In a project, students will work individually or as small team to tackle problems motivated by industry applications or recent research in their field. Such projects typically involve smaller, well-contained practical parts of the overall problem such solving parts of a method design, implementing an algorithm or evaluating specific approaches. Projects are typically supervised by academic staff, providing closer insights into the research areas of the individual professors.
Social Aspects / Ethics
Given the tremendous effect data-driven application and AI have on the various aspects of our society, a multitude of ethical questions arise, including but not limited to accountability, privacy and fairness. These courses offer to opportunity to recognize the ethical implications of data science and provides guidelines how to incorporate ethics into Data Science and AI processes.
Master Thesis
The program is concluded by a 6-month full-time Master's thesis, where students will be involved in cutting-edge research with individual supervision and support. They will demonstrate how to apply the knowledge gained in the program to current problems and assess the outcome. We expect a written thesis and final oral presentation. Topics from seminars and the project can be the starting of a Master's thesis, but students are free to complete your Master's dissertation with a different supervisor.
The Master's programmes are structured for a standard duration of 4 semesters. The sample study plan provides a recommended approach for completing the programme within this timeframe. Deviations may occur depending on individual study trajectories. Enrolment is available in both the winter and summer semesters.
Sample Study Plan Beginners in Winter Term
1st semester
Total: 28 CP
2. Semester
Total: 32 CP
3. Semester
Total: 30 CP
4. Semester
Total: 30 CP
Introduction for First-Year Students in Computer Science
We offer in-person welcome sessions for Computer Science in both the Bachelor’s and Master’s programmes. Access to the welcome session is through our teaching platform, Digicampus. To register there, you will need your IT account details ("RZ-Kennung"), which you will receive after enrolment.
Admission is possible for students with BSc in Data Science, Computer Science, Mathematics and related areas. Students undergo an aptitude test as regulated in §4 and in Annex I of the Examination Regulations (in German only). More specially, we expect student to show proof of sufficient previous knowledge in the following areas:
- Multivariate calculus/analysis (at least 5 ECTS CP)
- Linear Algebra (at least 5 ECTS CP)
- Fundamentals of (Higher) Programming Languages (at least 4 ECTS CP)
- Practical Programming Experience (at least 4 ECTS CP), e.g., by practical exercises or a lab course
- Algorithms or Numerical Methods (at least 5 ECTS CP)
- Discrete Structures/Mathematics, Databases or Data Engineering (at least 5 ECTS CP) und
- Data Science or Machine Learning (at least 4 ECTS CP)
German University Entrance Qualification
Application
Please insert link to the master's programme of the university page with anchor #application
During the Study
To help make the start of your studies as smooth as possible, we've gathered all essential information for new Computer Science students in one place:
Here, you'll find everything you need for a successful beginning to your academic journey.
Course Catalogue
All the courses offered in the current semester, including lecturers, rooms, and times, can be found in Digicampus. These are also compiled here in accordance with your degree programme and examination regulations.
At the turn of the semester, the courses for the following semester are usually available around four weeks before the start of term.
Please adapt the link to the degree programme:
Timetables
For the compulsory and core courses of the degree programme, the faculty prepares a timetable, which also includes some elective courses. Please note that there is no distinction made between different examination regulations.
Exam Schedule
The faculty maintains a central exam schedule, where lecturers register the exams. You will also find links to the exam schedules of other faculties, such as for minor subjects or interdisciplinary degree programmes.
Exam dates for the Institute of Computer Science are listed here.
For most examination-related issues, the → Examination Office is your primary point of contact, including:
- Problems with exam registration in "Studis"
- Registration of final theses
- Issuance of certificates and transcripts
→
FAQs from the Examinations Office
For more complex issues, the →
Examination Board is responsible. Applications are also submitted through the Examinations Office. Common topics include:
- Deadline extensions (e.g., overall study time, final theses)
- Compensation for disadvantages
- Recognition of prior study and examination achievements
Examination Regulations
The examination regulations establish the guidelines for the degree programme, such as:
- Scope and content of module groups
- Mandatory and optional courses within the module groups
- Scope of examinations
- Deadlines, such as for orientation exams or the maximum duration of study
- Types and progression of examinations
Examination regulations are divided by area of application and build on each other. Over time, the examination regulations are modified to develop the degree programme further. The version that applies to you is the one in force at the time of your enrolment in its consolidated form. You can check this information in the "Studis" system.
Please adapt the links to the subject examination regulations and the module handbooks below.
→ Subject-specific Examination Regulations MSc Medical Information Sciences (all valid regulations)
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Faculty Examination Regulations of the Faculty of Informatics
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General Examination Regulations of the University of Augsburg
Module Handbook
The module handbook lists a catalogue of potential courses and provides details on these courses. The specific courses you are required or allowed to take are determined by the examination regulations. Not every course is offered every semester; please refer to the timetable and Digicampus for more information.
The information provided includes, among other things:
- The person responsible for the module
- Course content
- Learning objectives
- Examination format
- Allocation to the module group (see examination regulations)
- Contact hours/Workload
- Recommended semester
The module handbook changes slightly from semester to semester and depends on the degree programme and examination regulations. The information in the module handbook can also be found on Digicampus.
The University of Augsburg and the Faculty of Applied Computer Science offer numerous support services:
Central Student Advisory Service
The Central Student Advisory Service provides a broad range of support on non-subject-specific topics such as learning advice, self- and time management, psychological and systemic counselling, studying with disabilities, studying with a family, social and legal advice ("Studentenwerk"), career entry and orientation (Career Service), studying abroad and support for international students (International Office).
→
Student Advise and Counselling Service
Dean of Studies
The Dean of Studies at the FAI offers advice on teaching, examinations, support services, and teaching evaluations. However, the Dean of Studies is not responsible for individual study counselling or planning.
Examination Board
For more complex queries related to exams, recognitions, and applications, it may be helpful to consult directly with the chair of the Examination Board.
Subject-Specific Counselling and Other Contacts
The subject-specific advisors for each degree programme provide individual feedback on study-related questions such as course progression, choosing minor subjects/specialisations/internships, and preparing applications.
After the Study
Once all academic requirements have been completed, you must apply for your degree certificate. You can find details on this process on the → Examinations Office website.
Here you will find information on doctoral studies at the Institute of Computer Science at the University of Augsburg.
As digitalisation reaches all areas of daily life, ever larger volumes of complex data are being generated. Graduates of the Data Science degree programmes have excellent career prospects with their in-depth knowledge of analysing this data. The field of data science as a modern interdisciplinary science underpins the process of digitalisation and the effective utilisation of data in many application areas:
- Data analysis / Big Data
- AI/machine learning
- Digital transformation in the SME/industry sector
- Process optimization and automation, e.g., in logistics, online retail or the energy sector
- Medicine and Pharmaceutical industry
- System analysis/consulting
Do you want to stay in touch with your fellow students and meet them again at a variety of network events? Then join the → University of Augsburg's alumni network.
Qualification Objectives
The Master’s degree programme in Data Science provides students with a comprehensive education, preparing them for a wide range of career opportunities. The qualification objectives include:
Students acquire both an in-depth understanding of the theoretical foundations in medicine and mathematics, as well as advanced knowledge relevant to computer science. They also gain practical experience in the development and application of computational methods in biomedical research, medical care, and health-related applications.
Students learn to develop, refine, and apply advanced and innovative concepts, methods, techniques, and technologies in medical informatics to identify and solve complex information processing problems in (bio)medical and health-related fields.
Graduates are well-prepared for demanding professional roles in companies, public institutions, as well as in academic and non-academic research. They can work in a variety of sectors, particularly in healthcare, and both academic and non-academic research settings.
FAQs & Contact Persons
Still have questions? Here you will find answers to frequently asked questions and the contact details for academic advising, the dean of studies, and the student representative body—where you can get further assistance.
- Phone: +49 821 598 - 2134
- Phone: +49 821 598 - 5916
- Phone: 0821 / 598-2255