DS404 Data Science with Python

Lecturer: Prof. Dr. Stefan Mayer
Course description:


Language: English
Recommended for this semester or higher: 1
ECTS-Credits: 6
Course can be taken as part of following programs/modules:

Economics and Finance
European Management
General Management
International Business
International Economics
Management and Economics

Data Science in Business and Economics

Prerequisite for:




Course Type: Lecture (2 weekly lecture hours)

The lecture consists of (in-person) live sessions and online lecture videos. The dates of the live sessions are:

  1. Tuesday, October 19, 2021, from 4 pm – 6 pm c.t.
  2. Tuesday, November 16, 2021, from 4 pm – 6 pm c.t.
  3. Tuesday, December 14, 2021, from 4 pm – 6 pm c.t.
  4. Tuesday, January 11, 2022, from 4 pm – 6 pm c.t.
  5. Tuesday, February 8, 2022, from 4 pm – 6 pm c.t.
    Room HS 037 (Neuphilologicum)

Live sessions will be in-person, on campus (pending corona regulations). (Beginning of the first lecture: October 19, 2021 from 4 - 6 pm c.t - room HS 037 (Neuphilologicum).


Limited to 45 participants. Registration open for all (no first-come, first-served): Registration will open on September 1, 2021, on  Alma - end of registration time: Sunday, October 10, 2021 (23:55pm). If the number of applications (limited to 45 participants) exceeds the number of places available, we unfortunately will not be able to accept all applicants. In this case, a random selection will be made from all the applications received. Preferred access for master students from the Data Science in Business and Economics program.

Downloads: ILIAS
Method of Assessment:

Written exam (90 Minutes) or online assessment (90 Minutes).
Exam dates are available on the website of the Examinations Office.

Content: The course is an introduction to data science using Python. After a general introduction to Python, the following topics are covered: Data preparation, management, transformation, and cleaning; data visualization; machine learning.

Students who successfully complete the course know the most important basics of working with Python and are able to perform the complete process of data preparation, visualization and analysis with Python and apply their knowledge to real data sets.


VanderPlas, J. (2016). Python Data Science Handbook. O’Reilly Media.