Admission

Keep in mind that our study program ist based on the theoretical (mathematical) foundations of statistics and computer science to derive advanced methods of Data Science. Often applicants are surprised after enrolling with us how mathematically / statistically oriented our study program is. The program is designed as a consecutive Master's program to our Bachelor in Data Science. All contents of the Bachelor are therefore assumed to be known.

An online self-assessment test is available for you to check your previous knowledge. The processing of the test prior to your application is obligatory, please be conscientious in processing it. Without a bachelor in Data Science from our department, you will most likely be missing some of the content from our bachelor's program, mostly this is actually related to the mathematical and statistical basics. The self-assessment test should show you whether and to what extent you lack previous knowledge.

We expect you to work on the contents you are missing independently in addition to your Master's studies and to close the gaps in your knowledge yourself. If you have had too much trouble completing the corresponding tasks of the self-test, we would even advise you not to apply. Otherwise, we would be very pleased if you decide to join us.

1. A suitable bachelor's degree. There are 2 possibilities here:

   1. You have completed a Bachelor's degree in Data Science with us.

   2. You have completed another bachelor's degree at a German university.

      (Comparable degrees at foreign universities are recognized according to legal regulations). In this case, admission is possible if your studies are evaluated by us as informatics / statistics / mathematics oriented. According to our examination regulations, this orientation is given if your qualifying Bachelor's degree has the following contents:

      1. Achievements in the central areas of mathematics, computer science and statistics to the extent of at least 44 credit points, composed of achievements in computer science in the areas of "algorithms", "data structures", "object-oriented programming" and "software engineering" to the extent of at least 8 credit points, as well as achievements in mathematics in the areas of "analysis", "linear algebra", "differential equations", "discrete mathematics" and "numerics" to the extent of at least 8 credit points, as well as achievements in basic courses in statistics in the areas of "Introduction to (Descriptive) Statistics" and "Introduction to Probability Theory" amounting to at least 4 credit points and from achievements in advanced statistics courses from the area of "Inference", especially in the areas of "Point Estimation", "Interval Estimation", "Hypothesis Testing" and "Stochastics" amounting to at least 8 credit points, and.

      2. Achievements in computer science from the area of "Databases" to the extent of at least 4 credit points.

      3. Achievements in the field of data modeling amounting to at least 8 credit points, from achievements in courses of data modeling from the fields of "(generalized) linear models", "statistical / machine learning methods", "time series" and "(practical) optimization" amounting to at least 8 credit points.

      An admission under conditions is possible. The obligatory achievements mentioned before can be replaced by conditions as follows, which have to be fulfilled after the enrollment in the study program:

      1. The 44 credit points in Mathematics + Computer Science must have been earned. If fewer points have been earned, admission is not possible.

      2. The 8 credit points in mathematics must have been earned. If fewer points have been earned, admission is not possible. If at least 8 points have been earned, but the level of Advanced Mathematics 1 and 2 has not been reached through the corresponding courses, admission is subject to the condition that the module MD Req 1: Advanced Mathematics must be completed. In this case, the lecture Advanced Engineering Mathematics in English must be heard.

      3. The 8 credit points in Computer Science can be obtained by conditional admission under certain circumstances: If the relevant Bachelor's program does not include 8 credit points in Computer Science, but an introduction to any higher programming language (C++, Java, Python, R, ...) amounting to at least 4 credit points has been heard, admission is possible under the condition MD Req 2: Data Structures and Programming. This module must be fulfilled by the English language Reading Course Data Structures and Programming. However, this is only possible if no further requirements have to be fulfilled in points 6. and 7. If less than 8 credit points in relevant computer science courses and also no programming course of at least 4 credit points have been completed in the Bachelor's program, admission is not possible.

      4. The 4 credit points in an introductory course in databases can be replaced by the requirement module MD Req 3: Information Systems. In this module, either the German-language lecture Information Systems or the English-language Reading Course Information Systems must be completed.

      5. The 4 credit points in an introductory course in statistics must have been completed. If less than 4 credit points have been earned, admission is not possible.

      6. The 8 credit points in advanced statistics courses from the area of inference can be replaced by the two requirement modules MD Req 5: Inference and MD Req 6: Linear Models (both English-language Reading Courses) or by the German-language lecture Estimating and Testing. However, only if there are no requirements for points 3. or 7. at the same time.

      7. The 8 credit points in courses in the area of data modeling can be achieved by the requirement module MD Req 8: Introduction to Statistical Learning. In this module, either the German lecture Introduction to Statistical Learning or the English reading course Introduction to Statistical Learning must be completed. However, only if there are no requirements to be fulfilled in points 3. or 6. at the same time.

      Therefore, a total of at least 44 of the required 56 credit points must have been completed in any case; a maximum of 12 credit points may be made up by imposing conditions: On the one hand the course from the area of databases in the amount of 4 ECTS, on the other hand exactly one of the 3 courses in the areas of computer science basics (algorithms and data structures), advanced statistics (inference) or data modeling in the amount of 8 ECTS each. In addition, it is possible that in case of insufficient knowledge of mathematics, another mathematics course has to be provided as a requirement. Here, you as the applicant have the obligation to prove that the courses you have attended can be assigned to the corresponding areas. Often the names of the courses are meaningful enough (e.g. Analysis I), often the course Engineering Mathematics III is actually an introduction to statistics. For this purpose, it may be necessary to submit appropriate module handbooks with your application.

2. The final grade of the Bachelor's degree previously checked for application is at least good (2.7) in the German system. No exception can be made to this rule. If you did your Bachelor's degree abroad, your final grade will be converted into the German grading system during the application process; we use the modified Bavarian formula for this purpose.

3. Sufficient knowledge of English, which must correspond at least to level B2 of the Common European Framework of Reference for Languages (CEFR). Here we accept the following proofs:

   1. a German certificate of the Allgemeine Hochschulreife (English from 5th grade or from 7th grade up to the Abitur),

   2. an internationally recognized language certificate,

   3. a certificate of graduation from an English-language school or an English-language course of study,

   4. comparable evidence.

4. A statistical report must be prepared and submitted with the application as proof of special technical aptitude. The assignment and further instructions can be found in these documents: Summer 2025 Task. The prepared report must be submitted with the other application materials. Graduates of the in-house B.Sc. Data Science have already proven their special professional aptitude by graduating from the same and therefore do not have to submit the report. Students of other programs of the Faculties of Computer Science, of Mathematics and of Statistics at TU Dortmund University should contact the Student Advisory Service of Statistics before transferring.

5. The self-disclosure documentSelf-disclosuremust be filled out. Please take special care to sign the document 2 times at the end.

6. Proof of completion of theOnline Self-Assessment Test. Please note that the final score of the self-assessment test has no influence on your admission. Confirmation of participation in the self-assessment test will be provided via the self-assessment document.

Proof of German language skills is NOT required. The entire study program can be completed without knowledge of the German language.

Please note that other criteria such as Master's degrees, professional experience and certificates from (professional) further education according to legal regulations cannot be used for assessment.

The study program is NOT admission restricted. If you meet the above criteria, you are guaranteed a place on the course for the semester in question. However, it is not possible to defer admission to a future semester.

1. Within Germany and you are already enrolled at TU Dortmund University:

   1. Procedure: Fill out the application for change of studies and submit it to the Registrar's Office.

   2. Deadline: Friday before the start of lectures

   3. Required documents: The completed application, your (preliminary) degree certificate, a proof of your English language skills, self-disclosure document, statistical report to prove special professional aptitude.

   4. Procedure: The Student Secretariat forwards your application to us for verification of the criteria in step 1 (usually within a few days). If this is given, you will be automatically enrolled. We recommend a timely application a few weeks before the start of the semester.

   5. Contact person in case of formal problems: We can NOT help you with this. Please contact the Student Secretariat.

2. Within Germany and you are not enrolled at the TU Dortmund:

   1. Procedure: apply online at the Student Secretariat, use the campus portal for this purpose.

   2. Deadline: Friday before the start of lectures (We recommend a timely application a few weeks before the start of the semester).

   3. Required documents: The completed application, your (provisional) degree certificate, proof of your English language skills, self-disclosure document, statistical report to prove special professional aptitude, proof of German health insurance, a certified copy of your university entrance qualification.

   4. Procedure: The Registrar's Office will forward your application to us for review of the criteria in step 1 (usually within a few days). If this is given, you will receive a notice of admission, after which you can enroll within the deadline given on the notice of admission.

   5. Contact person for formal problems: We can NOT help you with this. Please contact the student secretariat.

3. Within the EU:

   1. Procedure: apply at the International Office.

   2. Deadline: Friday before the start of lectures.

   3. Required documents: A list of required documents can be found on the website of the International Office linked above. Furthermore, the following documents are required for the Master in Data Science: English language certificate, self-disclosure document, statistical report to prove the special professional aptitude, module handbooks of the basic mathematics lectures.

   4. Procedure: You first apply online at the International Office, no documents will be sent by mail. The International Office will forward your application to us for review. Since there are many international applicants, this can take several weeks or even months. Afterwards, you will receive the admission decision from the International Office and may enroll in our program. You can find all information about enrollment here

   5. Contact person for formal problems: We can NOT help you with this. Please contact the International Office.

      Important notice: We are NOT informed about the current status of your application.

4. Outside the EU:

   1. Procedure: apply at the International Office , the application itself takes place via uni-assist.

   2. Deadlines: November 15 to January 15 (application for summer semester); March 15 to June 15 (application for winter semester). We recommend an early application, as we need a few weeks to process your applications and you may still need to take care of a visa and an apartment in Germany afterwards.

   3. Required documents: A list of required documents can be found on the website of the International Office linked above. Furthermore, the following documents are required for the Master in Data Science: English language certificate, self-disclosure document, statistical report to prove the special professional aptitude, module handbooks of the basic mathematics lectures.

   4. Procedure: You first apply online at the International Office. There is no provision for documents to be sent by post. Your application will be forwarded to us for review. Since there are many international applicants, this can take several weeks or even months. Afterwards, you will receive the admission decision from the International Office and may enroll in our study program. You can find all information about enrollment here.

   5. Contact person for formal problems: We can NOT help you with this. Please contact the International Office.

      Important notice: We are NOT informed about the current status of your application.

1. Extra Requirements: if you have not completed our Bachelor in Data Science, you have probably been admitted under conditions. These conditions serve to bring your level of knowledge closer to our Bachelor graduate’s level. These extra requirements have to be fulfilled after enrollment and before attending the course Case Studies. Please note that in the case of extra requirements your studies may take longer than two years.

2. Study organization: there will be orientation events at the beginning of your studies. These will take place at the beginning of October for winter intake together with the newcomers in the Bachelor's program of our department, and at the beginning of April for summer intake. Participation is highly recommended as you will receive a lot of useful information regarding your studies and get to know your fellow students and the campus.

3. Precourses: Before the start of the lectures you should check out our precourses which will help you to prepare for your upcoming master and to refresh your memories of all the important stuff from your bachelor courses. There will be 3 different precourses:

   The first one is a statistics precourse in German language which covers especially the most important content of the statistics bachelor. It takes place 3 weeks live on campus or via zoom (due to the corona virus). It is recommended if you prepare for the statistics master.

   The second and third precourses are online courses on the learning platform moodle in English language. They have no fixed timetable. So, you can do them where and whenever you want.
   
   One of them is a online statistics course. It mostly covers the same content as the first precourse and is recommended for both master's programmes Data Science and Econometrics. The other one is a data science course and is highly recommended for all data science students.

   For more information click here

4. You can find a lot of information for foreign students on the website of the International Office.