Englischsprachige Kurse (Sommersemester 2023)
Fakultät Statistik
- Advanced Statistical Learning, 4+2 9 ECTS, MD 1
Di, 16-18, HF 50, HS 3
Do, 16-18, EF 50, HS 3 - Generalized Linear Models, 4+2, 9 ECTS, MD E1
Di, 10-12, M E21
Mi, 12-14, CT ZE 01
Groll - Time Series Analysis, 4+2, 9 ECTS, MD E1, ME 4 9 ECTS
Di, 10-12, Maschinenbau, HS 1
Do, 12-14, CT ZE 02
Jentsch - Unit root and cointegration analysis, 4+2, MD E1, ME 7, 9 ECTS
Fr, 10-16, from 05.05.2023 on, M E27
Arsova - Advanced Bayesian Data Analysis, 2+2, MD E1, ME 7 4.5 ECTS
Do, 10-12, M E25
Klein - Selected Topics in Data Science, 2+2, MD E1, 4.5 ECTS
Do, 14-16, CDI 120
Klein - Econometrics, 4+2, MD E2, 9 ECTS
Di, 8-10, M E 28
Do, 10-12, M E28
Jentsch - Statistical Methods in Genetics (Bioinformatics), 4+2, MD E2, 9 ECTS
Mo, 14-16, M E21
Do, 14-16, M E21
Rahnenführer - Resampling & Simulations, 2+1, MD E2, ME 7, 6 ECTS
Mi, 12-14 M E27
Do, 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
Fakultät für Mathematik
- Numerical Solution of Differential Equations, 2+1, MD E1, 5 ECTS
Damanik
M/E29 Mo 10-12
EF/HS3 Fr 12-14 - Introduction to Computational Fluid Dynamics (CFD)
Kuzmin
M/1011 Di 10:00 2h
Fakultät für Informatik
- Architecture and Implementation of Database Systems, 4+2, MD E1, 8 ECTS
Teubner
Mo, 8-10, OH12, E.003
Mi, 8-10, OH12, E.003 - Machine Learning Paradigms for Complex Data, 4+2, MD E1, 8 ECTS
E. Müller
Di, 12-14, HG II, HS 5
Do, 14-16, EF 50, HS 2 - Real-Time Systems and Applications, 4+2, MD E1, 8 ECTS
Chen
Do, 12-14, OH12, E.003
Fr, 10-12, OH12, E.003
Veranstaltungen anderer Fakultäten / Universitäten
- Machine Learning in Robotics, MD E2, Hoffmann
Di, 12-14, HG II HS 4
Anmeldeverfahren bereits abgeschlossen - Introduction to Artificial Intelligence, MD E1, 2+1, 3 ECTS
Wiskott
Veranstaltung an der RUB
Anmeldeverfahren bereits abgeschlossen - Game Theory, MD E2, 4, 7.5 ECTS
Mo, 8:30-12, M127
Buchheim
Veranstaltung aus der Fakultät für Wirtschaft
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.
Statistics Department
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
Mathematics Departments
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
Other Departments
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)