拉斯维加斯赌城

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Department of Computer Science

  1. University
  2. Faculties
  3. Faculty of Applied Computer Science
  4. Institute of Computer Science
  5. Study Programmes
  6. Master Data Science

Master degree programme: Data Science

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:
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  • 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)
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Core Data Science Methods

The Core Data Science Methods should be taken at the beginning of the programme, as they provide a solid foundation in essential techniques and ensure a shared methodological background. These courses build upon topics covered in previous Bachelor's programmes, reinforcing fundamental concepts while delving into the specific methodologies of Data Science.
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In Computer Science, key areas include:

  • Algorithm Analysis and Design for Big Data
  • Data Engineering for Data Preparation and Quality
  • Machine Learning with a focus on probabilistic methods

In Mathematics, the main topics cover:

  • Statistical Learning Theory
  • Analytical foundations of deep learning and approximation with surrogate models
  • Advanced matrix and optimisation methods

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Bildlizenzen von Shutterstock.com.

Advanced Data Science Methods / Electives

The elective courses in Advanced Data Science Methods allow students to specialise in specific areas, whether by deepening their understanding of mathematical foundations, exploring cutting-edge techniques, or systematically applying methods to real-world domains. Courses cover topics such as...


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.

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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.?

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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.?

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Master's Thesis

The programme 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 programme is 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.

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Sample Study Plan Beginners in Winter Term

1st semester

Core Data Science: Algorithms and Data Engineering
8 CP
Core Data Science: Mathematical Methods in Data Science A
8 CP
Elective Area
8 CP
Computer Science Seminar
4 CP

Total: 28 CP

2. Semester

Core Data Science: Machine Learning
8 CP
Core Data Science:?Mathematical Methods in Data Science B
8 CP
Elective Area
12 CP
Mathematics Seminar
4 CP

Total: 32 CP

3. Semester

Elective Area
16 CP
Ethics & Computer Science
4 CP
Mathematics / Computer Science Project
10 CP

Total: 30 CP

4. Semester

Master's Thesis
30 CP

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.

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→ to the website

Admission is possible for students with B.Sc. in Computer Science, Mathematics, Data Science and related areas. As the programme includes compulsory courses in mathematics and computer science, we expect candidates to have a strong background in both areas. Therefore, students undergo an aptitude test as regulated in §4 and in Annex I of the Examination Regulations (in German only). More specifically, we expect students 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) and
  • Data Science or Machine Learning (at least 4 ECTS CP)?
The overall grade of your B.Sc. degree must be 2,70 or better according to the German grade scale,?as well as English language skills at least at level B2 (but no mandatory German language skills)
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Students who are close to successfully completing such a degree may also apply under the following conditions:
  • At least 85 % of the?required credit points of your BSc?programme completed
  • All?Requirements on language and knowledge are covered
  • The overall grade is sufficient when treating all missing credits as the worst possible passing grade
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The determination of programme-specific suitability is assessed by a selection committee.

The programme can be begun in both winter and summer terms; the regular deadlines are September 1st and March 1st. Due to visa issues, we strongly encourage non-EU citizens to apply well ahead of the deadline (suggested: May 1st for winter, December 1st for summer). Early admission is granted to allow sufficient time for visa processing.
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International?University Entrance Qualification

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Additional information for international applicants

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Application

German University Entrance Qualification

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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.

The Study Guide will help you during your first semester(s) of study in Augsburg, but also contains useful information throughout the programme.

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Download the Study Guide

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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.

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Course Catalogue for MSc Data Science

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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.

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Timetables

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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.

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Exam Schedule

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Exam dates for the Institute of Computer Science are listed? here.

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For most examination-related issues, the?→ Examination Office is your primary point of contact, including:
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  • Problems with exam registration in "Studis"
  • Registration of final theses
  • Issuance of certificates and transcripts

→ FAQs from the Examinations Office
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For more complex issues, the → Examination Board is responsible. Applications are also submitted through the Examinations Office. Common topics include:
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  • 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:
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  • 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.

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→ Subject-specific Examination Regulations MSc Data Science (all valid regulations - release pending)
→ General Examination Regulations of the University of Augsburg
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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:
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  • 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.

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Here?you can find the current exam dates.
Here?you can find information about final theses at the Institute of Computer Science.

The University of Augsburg and the Faculty of Applied Computer Science offer numerous support services:

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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).

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→ Student Advise and Counselling Service
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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.

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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.

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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.

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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
The comprehensive training in computer science and mathematics also opens up career opportunities for graduates in both areas. Furthermore, the Master’s programme serves as gateway towards further research qualifications such as the PhD progamme.??

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.

At the University, students have access to various advisory services on topics related to entrepreneurship and self-employment. You can find further information here.

FAQs & Contact Persons

Still have questions? We compiled a list of frequently asked questions, grouped by the common areas. If you cannot find an answer, you will find a list of contacts below

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Eligibility and Background

No, you can apply with other degrees. Be aware, that the programme includes strong theoretical and mathematical aspects as well as joint lectures with mathematics and computer science on Master level. The required prior knowledge might be more difficult to obtain outside these subjects.
The minimum grade for all M.Sc. programmes in Computer Science and Mathematics is 2.70 or better according to the German grading scale (1 best possible grade, 4 minimum passing grade). If your degree does not use the German grading scale, please look at the separate FAQ item

Admission to M.Sc. is Data Science requires knowledge in a number of subjects. You can find the list on the

course website?(see Entry Requirements) and the examination regulations.?

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Providing an appropriate course title is not sufficient, instead we require a rigorous treatment of the contents and systematic knowledge of methods, including but not limited to proof techniques. The admission committee requires comprehensive descriptions on the content and methods of these courses. There are several FAQ items in the Prerequisites & Documentation section on this matter.

While reputable online courses of provide a good coverage and presentation of the material, they typically lack a thorough examination system. Unless an accredited institution is vouching for the results, we therefore cannot accept online courses

In general, we do not accept practical knowledge such as work experience or projects to fulfil the admission requirements, as they lack a rigorous quality assessment.

The programme can be studied completely in English. For a transition period, a limited number of electives or exercise groups may be taught in German; students may also choose to write their theses/report in German.

Therefore, no German knowledge and German language certificates are needed for the programme itself. For everyday live, some basic German will be helpful, though.

We require English language skills at B2 level, but no German language certificates.

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The university maintains a list of recognized certificiates: Admission requirements. No other test certificates will be accepted.

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If your previous degree was taught entirely in English, a statement from your University with the Medium of Instruction (MOI) also fulfills the requirements.

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If your previous degree (e.g., the B.Sc.) was taught entirely in English, this also fulfills our requirements. If only parts of the programme were taught in English (such as the thesis), this is not sufficient. Please be aware that using an MoI may cause additional effort when applying for a visa, as not all embassies are satisfied with the university statement.
If you already achieved multiple, possibly relevant degrees, including but not limited to a second B.Sc. or an M.Sc., you can apply. Please include all degrees, transcripts and module descriptions. When presenting the contents for a requirement, it is helpful if you point out from which degree this is taken.
No, these tests are not considered and will not affect your admission.

Prerequisites & Documentation

No, an appropriate course title is not sufficient to prove sufficient knowledge for a subject area. As a consequence, uploading a transcript at this point of the application will be treated as missing documentation. Likewise, title lists from regulations are deemed to be insufficient.?

Instead, the admission committee need module descriptions to cover the contents, methods, goals and credits/contact hours, similar to our module handbook?

For each individual part, please provide a reference (e.g., page number / module identifier) into your module handbook. Please upload the full handbook, including the name of the university and the programme. A transcript with the title of the course or a reference to the CV are not sufficient. The information must be in English or German but does not need to notarized. If your module description is not in one of these languages, please provide both a translation and the original document.
If your degree was or will be issued by a university from China, India or Vietnam, you will need an APS certificate when applying. In addition to the validation of your degree, embassies in these countries will usually not issue visas without an APS certificate. If you already live inside the EU or have a follow-up degree with suitable content from a university outside these countries, this requirement may be waived, please contact us.

For our M.Sc. programmes, no VPD are required - this is only necessary for our B.Sc. programmes. The assessment will directly be performed on your degree certificates, transcripts and module description.

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There are two exceptions, however, where different kind of certificates are needed:

  1. If your degree is from China, India or Vietnam, you will need an APS certificate. There is a separate FAQ item on this
  2. If your university is not fully recognized according to Anabin as H+, your degree certificate will need to be validated by the " Zeugnisbewertung der ZAB" for statement of comparability.
If your university is not fully recognized according to?Anabin as H+, your degree certificate will need to be validated by the for statement of comparability. Reasons for that may be partial/incompatible accreditation, franchising from accredited universities, ...

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Please apply for this statement of comparability as soon as possible, as processing may take weeks to months. When you receive the statement, please include it with your degree at application time.

When applying, you will be asked to provide the number of credits / contact hours of your previous degree, as well as its duration.?One year of full-time study corresponds to 60 European Credit Transfer System (ECTS) credits.

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Therefore, a three-year Bachelor’s program in Europe is equivalent to 180 ECTS.?

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Please provide your "original" CP contact hours in the application, as stated in your transcript / module description. The application committee will then convert and check those numbers.

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You may estimate the converted value as follows:? If you have 8 "original" credits in a three-year program worth N "original" credits, you can convert them to ECTS by multiplying 8 by 180 divided by N.? If you participated in a four-year program, you need to replace 180 with 240.

The German grading system assigns grades from 1.0 (very good, maximum grade) to 5.0 (failed, minimum grade), where 4.0 is the minimum passing grade.

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You need to provide you the best possible grade and minimum (course) passing grade of your grading system when applying, and provide proof for this information (e.g., as part of your transcript). The original grade must be entered, together with these boundaries.

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The admission committee will use this information to compute your equivalent German grade and determine?if it meets the requirements (2.7 or better=lower).?Your (numerical) grade will be scaled using the modified Bavarian Formula.

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University of Augsburg provides a converter for initial guidance, but please note that the provided information is not binding.

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No, letters of recommendation will not be considered. We kindly ask you not to attach or send us any recommendation letters, as this may delay the application process.
While we understand that some of want to providing a motivation letter, we cannot consider its contents as the admission focuses on academic achievements. To keep the review process streamlined, please do not add any motivation letters.
When applying for a M.Sc. programme, electronic documents are sufficient. Only when enrolling, we need to see physical, certified copies.
No. All documentation has to be complete when the application is submitted. The only exception are final transcripts or degree certificates when the original application was sufficient for a conditional acceptance for an incomplete degree (85 %), but new documents became available before the decision.

Application Process

The application period for this degree starts alongside with those for other degrees at University of Augsburg. The specific dates are listed at the start part of the application portal. If the programme is not listed explicitly, the date for all other M.S.c degree programmes applies. In any case, the application window opens several weeks before the recommended deadline. As a general estimate, the portal will open for applications targeting the winter semester in mid-March, while applications for the summer semester will be possible from mid-September
The exclusion deadlines for applications are September 1st (winter term) and March 1st (summer term). These deadlines are clearly not sufficient if you require a visa. In this case, we strongly recommend applying until May 1st / November 1st. Applications after these recommended deadlines will still be processed, but the admittance is only valid for a single semester. Getting the visa and arriving in time is your responsibility, we will not grant extension towards the maximum duration of the programme.
The aptitude test is based on the list of prior knowledge in certain areas which needs to be included in the application. The assessment committee will review these documents and decide based on the submitted information. No written exams or interviews are needed.
To get admittance, you need to completely fulfil the requirements in terms of languages, knowledge and grades. No exceptions or extensions will be granted. The only special case is a mostly, but not completely finished degree.
If you finished all your courses, but did not yet receive your degree certificate, you can already apply. Please include on up-to-date transcript showing all courses. The degree certificate can be presented when enrolling.?
If you already finished 85 % of the required credit points of your programme, you may apply and get admitted. The requirements on language and knowledge need to be fulfilled as well as the minimum grade. To determine the grade, all missing credit points/courses should be set to the minimum passing grade. To provide a brief example: for 180 ETCS CP B.Sc., you need to have completed at least 153 CP. If you have a grade average of 2.4 so far and use 4.0 (lowest passing grade in Germany) for the remaining 27 CP, your overall grade will be 2.64: (153* 2.4 + 27*4.0) / 180. This is sufficient for admittance, as it is better than the threshold of 2.7. A grade average of 2.5 for the 153 CP will lead to a total grade of 2.73, which blocks you from early admittance. The admission committee will determine the grade based on the information provided by you
No, the admissions are not ranked. If you fulfil the necessary requirements, you will be admitted. The submission time, additional certificates or documents will not be taken into account.
University of Augsburg does not charge a fee for applying.

Applications for the winter?term will be processed starting from the following dates:??

  • Applications received March 10th - May 1st: May 1st

  • Applications received May 2nd?- July 1st: July 1st

  • Applications received July 2nd?- September 1st: September 1st

Applications for the summer term will be processed starting from the following dates:??

  • Applications received September?10th - November?1st: November 1st
  • Applications received November?2nd?- January 1st: January?1st?
  • Applications received January?2nd?- March 1st: March 1st.?

Providing a strong guarantee on the processing duration is not possible, but we aim for 3 - 6 weeks after the start for each group?

The notification is sent to you by mail, you may find details in the VIBS portal or as attachment.
Due to legal reasons, the decision document (“Bescheid”) is issued in German only.?

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An acceptance document provides information on enrollment and the beginning of the semester. We will soon send you more information.

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The notice of?rejection contains the main reason why you were not accepted on the second page, while the first page lists the requirements (again for legal reasons).


Common reasons are:

  1. Note (Grade) 
    dass Ihre Durchschnittsnote in ?previous degree? an 
der ?previous university? [...]
nicht die erforderliche Gesamtnote von 2,70 ergeben hat
    The grade you entered or was shown on your transcript did not fulfill the required minimum grade for our study programme: 2.7 or better in the German system, where 1.0 is the best possible grade and 4.0 is the minimum passing grade.
  2. Fehlende Unterlagen (Missing documentation) 
     dass die geforderten Bewerbungsunterlagen nicht vollst?ndig eingegangen sind
    The documents you submitted did not provide proof of the necessary courses and their contents. Besides missing or unrelated documents, this also covers significant inconsistencies among your documents. In particular, the title of a course from a transcript alone is insufficient to provide the necessary detail on the contents.
  3. Fehlende Gleichwertigkeit (lack of equivalence) 
    dass Ihr Studium in ?previous degree? an ?previous university? nicht als 
    gleichwertig [...] angesehen werden kann
    The courses you listed did not contain contents equivalent to those required. This could mean that?
  • the courses have no or little relation to the required subject,?
  • the methods utilized do not align,?
  • your course covers only part of the relevant material or?
  • the course contents do not reach the necessary amount
In particular, both “Multivariate Real Analysis” and "Linear Algebra" need Mathematics course(s) containing methods and proofs for analysis (calculus, not statistics) on multiple variables/dimensions and linear maps on vector spaces, respectively. The content needs to correspond to a full lecture on that topic, a fraction is not enough.
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Please note that all these criteria had to be fulfilled when submitting your application. Due to the large number of applications, we cannot provide individual feedback.?

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If your application was rejected, you may reapply in a later semester. You will have to re-register in the VIBS submission system, as account data is reset between application rounds.

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Please be aware that sending the same application again will not change the outcome. Missing documentation or a miscalculated grade can be corrected, whereas a lack of equivalence is hard to overcome.

Visa & Enrollment

Late arrival is only possible until the beginning of the second week of lectures (typically around October 20th/April 20th). Any later arrivals would lead to significant challenges with the course materials, so that students will not be able to achieve a meaningful amount of credits in their first semester.

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As admissions can only be issued for a single semester, we offer fast track readmission that will provide you with much more time to obtain a visa for the following semester.?In case that you will not be able to obtain a visa on time, you can simply go to VIBS once the admission period starts and upload your earlier admission letter. You do not need to provide any further documents in this case and you will receive a fast response with a new admission letter for the coming semester.

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The first step after receiving the acceptance letter should be your visa, as this takes most of the time and is least predictable. In parallel, please attend the online information session provided by the university. Once you have a reliable estimate of your visa processing time and know that you will be able to come for a specific semester, follow the instructions by our International Office regarding housing, enrolment, registration, etc. (/en/portal/internationals/abschluss/first-steps-first-semester-students/)
The enrolment portal opens about 2 months before lectures; your admission letter states the deadline (often extendable to week 1). Enrol only after visa approval—each semester counts toward your limit, and reversals aren't guaranteed. After enrolling, you will get access to your IT account and university email address and receive your student ID.
After you enrol, all official messages from the university will be sent to your university email address (firstname.lastname@uni-a.de). You must check this address regularly or set up forwarding to another email address. Some internal departments, such as the Examinations Office (Prüfungsamt) will communicate exclusively with you through this address.
Your student ID (CampusCard) card will be mailed to the address you provided in your application. In many cases, this will be your address in your home country. If you prefer not to have it mailed, you can arrange with the Registrar's Office to pick up your student ID card in person. Please familiarise yourself with the features of the CampusCard and the validation process: /en/studium/studieren-augsburg/semesterticket/
The registrar’s office maintains a list of required documents and describes the process. You need to send physical, certified copies of your higher education entrance qualification and previous degree. Furthermore, you need to show proof of health insurance and payment of the semester fees (/en/studium/bewerbung/einschreibung/).
Available classes and their schedule are typically published at least a month before the semester starts. After enrolling, use Digicampus to register as soon as possible for the courses you are interested in, as the professors may provide more specific material already at the very start of the semester. Late registration (after week 1) can be difficult and means missing key early materials and the course organisation phase with exercise date or group assignments. For seminars/labs/practical courses, specific application procedures may apply; these will be listed in the course descriptions.

Finances & Scholarships

University of Augsburg does not charge tuition for any student. This does not mean that studying is completely free: There is a (nominal) semester fee covering social services and public transport. Furthermore, Germany has a rather high cost of living which needs to covered by the student.
There are no tuition fees, but you must cover the semester contribution (which covers public transport), health insurance, rent, and general living expenses. As of early 2026, a realistic monthly budget for Augsburg is about 1,000–1,300 �. For up-to-date estimates, please check the International Office pages (/en/studium/organisation-beratung/organisation-und-formales/rueckmeldung/).
University of Augsburg does not provide on-campus accommodation, so you need to search and apply for housing yourself – which can be challenging. A good guideline can be found at /en/studium/studieren-augsburg/wohnen/, with additional information in our Study Guide. Please start searching early and do not just apply at a single provider. Send an email to info@aaa.uni-augsburg.de, and the International Office will provide you with a pdf guide for your room search that includes all the dorms and other possibilities we know of. University support for housing search is limited, but our onboarding team can help with landlord references or review your applications for potential issues.
Health insurance is compulsory in Germany. You will need proof of either private health insurance for students in Germany (not recommended) or of statutory German health insurance for students to enrol at university. There is a wide variety of health insurance providers in Germany, many of which have offices in Augsburg. We are not allowed to make recommendations, but a good start will be public/statutory health insurances with branches in Augsburg and English-language information (e.g., TK, Barmer, AOK).
Students from outside the EU are allowed a limited number of hours on their student visa (/en/portal/internationals/academic-immigration-office/studying/working-during-studies/). The programme is demanding, so we recommend prioritising studies over excessive work. One way to support our students is through part-time teaching or research assistantships. Another possibility is so-called "working student job"/"Werkstudierenden" where you can also use the skills you acquire during your studies. In either case, at least basic knowledge of German is helpful or even required.
Because public universities in Germany do not charge tuition, scholarships are typically limited and often competitive. You will find an overview of potential grants on the International Office pages (/en/portal/internationals/abschluss/costs-financing-scholarships/) and in the DAAD database (https://www2.daad.de/deutschland/stipendium/datenbank/en/21148-scholarship-database/). For international students who have a financial emergency, the f.au.st e.V. association (/en/portal/faust-en/) can provide financial support. Please note that this is a small organisation with limited financial resources.

Program Structure

In the first semester, we strongly recommend taking the Core Data Science courses, one for computer science and one for mathematics. The idea of these courses is to provide a solid foundation for the required knowledge and methodology by refreshing and extending core competences. This way, students will be well-prepared for advanced/elective courses and projects.?

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Together, these courses already provide more than half of the expected workload for this semester (16 out of 30 ECTS credits).

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In addition, you may take a seminar and a advanced course, but please ensure that you already have the required knowledge

Lectures usually start about 2 weeks into the semester, mid-April (summer) or mid-October (winter). The exact dates are published on the university web site (/en/studium/organisation-beratung/fristen-und-termine). In some programmes, preparation courses and welcome events already happen in the weeks before, please check this point.
The M.Sc. Data Science is designed as a full-time, 4 semester programme (120 ECTS). You should plan for about 30 ECTS per semester, which corresponds to roughly 750 - 900 hours of work, including lectures, exercises, self-study, and exams. The workload is higher during the lecture period but consider that exams and lab courses/practical will be scheduled during the semester breaks.
There is no general mandatory attendance, but the programme is not designed for remote study. Many exercises, labs, and projects require your presence on campus and access to local infrastructure. Our experience shows that there is a very strong correlation between active, on-site participation in courses and success rates.
The programme schedule is designed for full-time study, see more details at the workload FAQ item. There is a certain flexibility in the workload distribution but expect that you need significant amounts of time beyond the scheduled lectures and exercises. In addition, exams and practical courses will take part in the semester breaks.
The Data Science programme places two mandatory core modules with 8 ECTS each at the start of first and second semester: CS: Algorithms and Data Engineering (winter)/Machine Learning (summer), Mathematics: Mathematical Methods in Data Science A (winter) / B (summer). These modules already cover 16 ECTS credit of the expected 30 per semester and should be taken at the beginning of your studies. Depending on your personal preferences and previous knowledge, you may add one or two lectures from the computer science or mathematics side. Another option can be a seminar from CS, Mathematics or on ethics.
Data Science: at the beginning of the first Core Module lecture, the professors will introduce the programme, its structure and answer your questions.?
The department publishes a programme- and semester-specific course catalogue (/de/fakultaet/fai/informatik/im-studium/lehre/msc-dsc2025/), which is usually updated about one month before the semester starts and may receive minor updates later. From this catalogue you can access the Digicampus entries of each course to see detailed information and register. Directly searching Digicampus is also possible but is often less intuitive.
If you already successfully passed suitable courses, you may request recognition of these courses in your current programme. This is only possible after you are enrolled, and no reliable estimates can be given beforehand. As a general guideline, course must fit both in terms of topics/competences and methodologies. The examination office provides the directions and forms.
Many courses assume solid Python skills, and some also use other languages such as R or SQL. If you are not yet comfortable with Python, we recommend that you refresh your skills before the programme or attend the introductory B.Sc.-level programming course offered by the department (INF-0487, without credit but with supervision and feedback).

Registering for a course on Digicampus does not mean one is registered for the exam. To register for the exam there is a separate registration period and a different portal (called STUDIS) is used. You will get an email notification when the registration period is approaching.

To plan ahead: The future exam registration periods are posted on the website /en/studium/organisation-beratung/pruefungen/. There you will also find a link to the STUDIS portal mentioned above.? ?

There are currently no specific preparatory courses offered at Master level. If you are already enrolled, it may be a good idea to look at the listed prerequisites and literature for the courses you are planning to take. In terms of the literature, we do not expect you to cover the contents beforehand, but to understand if you have enough previous knowledge. If you are unsure, please register for the course and contact the professor or assistants.
Take projects after core modules and most electives (e.g., semester 3). Theses often follow projects in semester 4; options include research or industry, always directly supervised by academic staff or professors. See thesis guidelines: /en/fakultaet/fai/informatik/im-studium/abschlussarbeiten/
The M.Sc. Data Science is already a collaboration between the Computer Science and Mathematics institutes. Therefore, many courses from either side are available as electives. You might attend other courses without gaining credits if the professors accept this. The M.Sc. Computer Science puts a strong emphasis on core computer science aspects. Elective modules provide insights into employing these concepts into specific application areas, but students interested in these areas are advised to take specialised programmes.
The language centre of the university provides courses for several languages (including German as a foreign language) that are available to registered students. While these courses do not count as credits in your degree, they can be very helpful for everyday life or finding employment. Please be aware that these courses cannot be used to fulfil language requirements after enrolment. (/en/organisation/einrichtungen/sz/)

Contact Persons

Need some further assistance? Here you will find the contact details for academic advising and the dean of studies.

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Prof. Dr. Peter Michael Fischer
Studienberatung Informatik
Department of Computer Science

Email:

Prof. Dr. André Uschmajew
Student advisor Data Science
Institute of Mathematics

Email:

Prof. Dr. Matthias Schlesner
Dean of Studies for Computer Science
Lehrstuhl für Biomedizinische Informatik, Data Mining und Data Analytics

Email:

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:

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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.

By participating in seminars and research projects, students deepen their expertise in various areas of medical information sciences and enhance their ability to conduct independent scientific work and research.

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.

Students are enabled to work independently and accurately, think abstractly and creatively, and expand their knowledge autonomously.
Students gain experience in leading teams and projects, developing the ability to critically discuss problems, define subordinate goals, classify, evaluate, combine, and present interim results and ideas.
Students also develop important soft skills essential for a successful professional career, such as communication, teamwork, and presentation skills.
Students acquire competencies in interdisciplinary teamwork and learn to interact purposefully with potential users from other disciplines, analysing their needs and developing suitable solutions.
Students become sensitised to ethical issues and societal concerns, fostering a better understanding of the potential impact of their work on society.

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.

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