Data science

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

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

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:

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.

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

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:

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

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.

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.

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.

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.

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.

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.

For applicants with Indian educational certificates it is not yet compulsory to submit an APS certificate together with their application to uni-assist. From 15 March, applications that do not yet include an APS certificate will be processed and forwarded to TU Dortmund University if the preliminary examination is positive. After this date, applications that have been rejected before 15 March due to the lack of an APS certificate will be processed by uni-assist as soon as possible. Applicants who are admitted to a Master's degree program for the Winter semester 2023/2024 must submit their APS certificate as soon as possible. Admitted applicants can only be enrolled within the regular enrollment deadlines if an APS certificate is available.

1. 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.

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2. 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:

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

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4. an internationally recognized language certificate,

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

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6. 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](https://statistik.tu-dortmund.de/storages/statistik/r/Dow...) [Winter 2025/26 Task.](https://statistik.tu-dortmund.de/storages/statistik/r/Dow...) 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.

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8. The self-disclosure document[Self-disclosure](https://statistik.tu-dortmund.de/storages/statistik/r/Dow...)must be filled out. Please take special care to sign the document 2 times at the end.

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10. Proof of completion of the[Online Self-Assessment Test](https://statistik.tu-dortmund.de/storages/statistik/r/Dow...). 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.