English language courses (summer semester 2023)
- Advanced Statistical Learning, 4+2 9 ECTS, MD 1 Tue, 16-18, HF 50, HS 3 Thu, 16-18, EF 50, HS 3
- Generalized Linear Models, 4+2, 9 ECTS, MD E1 Tue, 10-12, M E21 Wed, 12-14, CT ZE 01 Groll
- Time Series Analysis, 4+2, 9 ECTS, MD E1, ME 4 9 ECTS Tue, 10-12, Mechanical Engineering, HS 1 Thu, 12-14, CT ZE 02 Jentsch
- Unit root and cointegration analysis, 4+2, MD E1, ME 7, 9 ECTS Fri, 10-16, from 05.05.2023 on, M E27 Arsova
- Advanced Bayesian Data Analysis, 2+2, MD E1, ME 7 4.5 ECTS Thu, 10-12, M E25 Klein
- Selected Topics in Data Science, 2+2, MD E1, 4.5 ECTS Thu, 14-16, CDI 120 Klein
- Econometrics, 4+2, MD E2, 9 ECTS Tue, 8-10, M E 28 Thu, 10-12, M E28 Jentsch
- Statistical Methods in Genetics (Bioinformatics), 4+2, MD E2, 9 ECTS Mon, 14-16, M E21 Thu, 14-16, M E21 Rahnenführer
- Resampling & Simulations, 2+1, MD E2, ME 7, 6 ECTS Wed, 12-14 M E27 Thu, 12-14 M E27 Pauly / Amro Lecture ends on May 04. Prerequisite: Passed Statistical Theory
- Industrial Data Science 2, 2P, MD E2, 4.5 ECTS Pauly
Faculty of Mathematics
- Numerical Solution of Differential Equations, 2+1, MD E1, 5 ECTS Damanik M/E29 Mon 10-12 EF/HS3 Fri 12-14
- Introduction to Computational Fluid Dynamics (CFD) Kuzmin M/1011 Tue 10:00 2h
Faculty of Computer Science
- Architecture and Implementation of Database Systems, 4+2, MD E1, 8 ECTS Teubner Mon, 8-10, OH12, E.003 Wed, 8-10, OH12, E.003
- Machine Learning Paradigms for Complex Data, 4+2, MD E1, 8 ECTS E. Müller Tue, 12-14, HG II, HS 5 Thu, 14-16, EF 50, HS 2
- Real-Time Systems and Applications, 4+2, MD E1, 8 ECTS Chen Thu, 12-14, OH12, E.003 Fri, 10-12, OH12, E.003
Courses of other faculties / universities
- Machine Learning in Robotics, MD E2, Hoffmann Tue, 12-14, HG II HS 4 Registration already closed
- Introduction to Artificial Intelligence, MD E1, 2+1, 3 ECTS Wiskott Course at RUB Registration already closed
- Game Theory, MD E2, 4, 7.5 ECTS Mon, 8:30-12, M127 Buchheim Course from the Faculty of Business and Economics
Courses taught in English (Winter Semester 2022/23)
The following elective courses will be held in English in winter semester 2022.
Many other German language courses are also open for M.Sc. Data Science students. However, generally, for these courses you need to be fluent in German). If you are interested in such courses, please contact Daniel Horn dhornstatistik.tu-dortmundde.
Note that at the current point in time (2021/08/30) it is impossible to say whether classes will be allowed on campus or have to be online, and in the end, this will be different for each class. So please check the individual websites for more information.
Pre-requisites and Reading Courses
Information on the pre-requisites and Reading courses for both Data Science and Econometrics can be found in our Moodle room here.
For all Statistics courses, you should bring sufficient skills in the fields of Statistics, i.e. you should take and finish your Statistics pre-requisites at first.
- Statistical Theory (9 credits (10 credits for Econometrics), 4+2, MD 2, part of ME 1) Tue 10:00-12:00 Wed 10:00-12:00
- Asymptotic Theory (only second half of the semester) (4,5 Credits (5 Credits for Econometrics), 2+1, MD Methods, part of ME 1) Wed 12:00-14:00 Thu 14:00-16:00
- Statistics in Toxicology (Testing) (4.5 credits, 2+1, MD Applications) Mon, 10:00-12:00
- Survival Analysis (9 credits, 4+2, MD Methods; ME 7) Wed 10:00-12:00 Thu 16:00-18:00
- Industrial Data Science (4.5 credits, 2+1, MD Applications) Fri 08:00-10:00
- Deep Learning (9 credits, 4+2, MD Methods) Tue 16:00-18:00 Wed 16:00-18:00
- Unit root and cointegration analysis (9 Credits, 4+2, MD Methods) Blockcourse in February
- Panel Data Econometrics (9 Credits, 4 +2, MD Methods) Tue 14:00-18:00
- Text as Data (4,5 Credits, 2 +1, MD Methods) Tue 10:00-12:00 Fri 08:00-10:00
- Statistical Network Analysis (4.5 Credits, 2 +, MD Methods) Tue 14:00-16:00
Computer Science Department
For all Computer Science courses, you should bring sufficient skills in the fields of Computer Science, i.e. you should take and finish your Computer Science pre-requisites at first.
- Statistical Learning for Big Data (9 Credits, 4+2, MD 5) Tue, 16:00-18:00 Thu 14:00-16:00
- Causality (6 credits, 2+2, MD Methods Mon 14:00-16:00
For all Mathematics courses, you should bring sufficient basic knowledge in the field of Mathematics.
- Numerical Methods for PDEs (4 Credits, 2+1, MD Methods Fr 14:00-16:00
- Programming Course Data Science with Python (3 Credits, Programming Course) Wed 16:00-20:00
We again have some courses from the linguistics departments. Registration is already closed. Please note that the application to linguistic content is in the foreground of the course.
2 courses from Bochum
- Introduction to Linguistic Data Science (10 credits, 2 semesters, MD Applications)
- Introduction to Computational Linguistics (10 credits, 2 semesters, MD Applications)
2 courses from Dortmund
- Statistics meets Linguistics (4.5 credits, MD Applications)
- Research Methods in English Linguistics (4.5 credits, MD Applications)