Servicenavigation

Statistik: mehr als Erbsen zählen

You are here:

Lecture Overview and Timetable

The full information about the courses at the Department of statistics can be found here (in German).

Preliminary Courses for the Master Programmes

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 knowledge of all the important content from your bachelor courses. There will be 3 different pre-courses:

The first one is a statistics pre-course in German language which covers especially the most important content of the statistics bachelor. It Is a three week course and takes place 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 pre-courses are e-learning courses on the learning platform moodle in English language. They have no fixed timetable. Therefore, you can do them where and whenever you want.

One of them is an online statistics course. It mostly covers the same content as the first precourse and is recommended for both master 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

Courses taught in English (Summer Semester 2022)

The following courses will be held in English in summer 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 dhorn@statistik.tu-dortmund.de.

 

The general teaching scheme for the upcoming semester is in-person teaching, so for most classes you will have to come to campus. However, some classes my stay hybrid by the choice of the respective lecturer. So please check the individual websites for more information.

 

Note that most information in the upcoming list is just mirrored from the LSF, in case of doubt, the LSF has the correct information.

 

We added an information on the teaching form for every course. Note that this information is just taken from the respective course webpages. It is just for your information, in case of doubt, the information on the course webpage is the correct one.

 

On Wednesday, March 30, 10:00 there will be a digital presentation of all the english language lectures

 

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.

  • Advanced Statistical Learning
    Prof. Groll, 4 + 2, MD 1 (9 Credits) Info Slides
    Thu 16:00-17:00, EF50/HS3
    Teaching form: Inverted classroom: 2 videos per week, 1 hour in-person Q&A
  • Generalized Linear Models
    Prof. Groll, 4 + 2, MD Methods (9 Credits) Info Slides
    Thu 11:00-12:00 GBIII/HS103
    Teaching form: Inverted classroom: 2 videos per week, 1 hour in-person Q&A
  • Statistics in Toxicology I (Modelling)
    Dr. Kappenberg, 2 + 1, MD Applications (4.5 Credits) Info Slides
    Wed 14:00-18:00, M/E21
    Teaching form: In-person. In addition to the script and the live lecture, videos (short version of the live lecture) are available
  • Econometrics
    Prof. Jentsch, 4 + 2, MD Applications (9 Credits) Info Slides
    Tue 08:00-10:00, M/E28
    Thu 10:00-12:00 M/E28
    Teaching form: In-person.
  • Time Series Analysis
    JProf. Arsova, 4 + 2, MD Methods(9 Credits) Info Slides
    Tue 10:00-12:00, HGII/HS4
    Thu 12:00-14:00 GBIII/HS108
    Teaching form: In-person.
  • Advanced R
    Dr. Horn, M.Sc. Görz, 2 + 1, MD 3 Programming Course (3 Credits) Info Slides
    Mo 12:00-14:00, CT/HS 15
    Teaching form: In-person, lecture will be recorded and uploaded.
  • Introduction to Causal Inference
    Menggang Yu, MS 6/7, ME 7, MD Methods E1-9 (4.5 Credits)
    June, 17th to July, 29th
    Mo 10:15-11:45, CDI 120
    Tue 14:15-14:45, CDI 120

 

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.

 

Mathematics Departments

For all Mathematics courses, you should bring sufficient basic knowledge in the field of Mathematics.

 

Other Departments

  • Learning in Robotics
    Prof. Hoffmann, 2 + 1, MD Applications (4,5 Credits)
    Tue, 12:15-13: HGII/HS4
    Only a limited amount of seats available. Please register via our deans office by writing an email to ds_learn_rob@statistik.tu-dortmund.de using the header "[Application for a seat in Learning in Robotics Summer 2022]", the application deadline is March 31.
  • Introduction to Artificial Intelligence
    Prof. Wiskott, 2 + 1, MD Methods (3 Credits)
    Only a limited amount of 15 seats available. Please register via our deans office by writing an email to ds_learn_rob@statistik.tu-dortmund.de using the header "[Application for a seat in Introduction to Artificial Intelligence Summer 2022]", the application deadline is April 4, 23:00.

 

Moreover, some of the seminars and case studies will be held in English.

Courses taught in English (Winter Semester 2021/22)

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 dhorn@statistik.tu-dortmund.de.

 

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.

 

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.

 

 

Mathematics Departments

For all Mathematics courses, you should bring sufficient basic knowledge in the field of Mathematics.

 

Other Departments

From the Linguistic Data Science Department in Bochum, there are 2 courses. Both of them are limited to 10 Data Science students per course. Registration for this courses took place per mail until Wednesday, October 06, 23:59, please do not register directly at the teachers, all such requests will be ignored.

 

From the Linguistic Department in Dortmund, there is 2 courses. The Statistics meets linguistics course is limited to 15 participants from the statistics department, the research methods course to 8 participants. Registration for this courses took place per mail until Wednesday, October 06, 23:59, please do not register directly at the teachers, all such requests will be ignored.

Please note that the application to linguistic content is in the foreground of the course.

 

Seminars at the Department of Statistics