Universität Wien FIND

Due to the COVID-19 pandemic, changes to courses and exams may be necessary at short notice (e.g. cancellation of on-site teaching and conversion to online exams). Register for courses/exams via u:space, find out about the current status on u:find and on the moodle learning platform. NOTE: Courses where at least one unit is on-site are currently marked "on-site" in u:find.

Further information about on-site teaching and access tests can be found at https://studieren.univie.ac.at/en/info.

Warning! The directory is not yet complete and will be amended until the beginning of the term.

040123 KU Programming for Business Analytics (MA) (2020W)

8.00 ECTS (4.00 SWS), SPL 4 - Wirtschaftswissenschaften
Continuous assessment of course work

Only students who signed up for the class in univis/u:space are allowed to take the class (that means, that you have to at least be on the waiting list if you want to take this class). No exceptions possible.


Note: The time of your registration within the registration period has no effect on the allocation of places (no first come, first serve).


max. 50 participants
Language: English


Classes (iCal) - next class is marked with N

Please note that (online) attendance is NOT compulsory, EXCEPT for the last two sessions (January 21 and 28).
Question times will take place as of November 5 (live, online).
There will be no live sessions on October 8, 15, 22, and 29.

Thursday 01.10. 09:45 - 11:15 Digital
Thursday 08.10. 09:45 - 11:15 Digital
Thursday 15.10. 09:45 - 11:15 Digital
Thursday 22.10. 09:45 - 11:15 Digital
Thursday 29.10. 09:45 - 11:15 Digital
Thursday 05.11. 09:45 - 11:15 Digital
Thursday 12.11. 09:45 - 11:15 Digital
Thursday 19.11. 09:45 - 11:15 Digital
Thursday 26.11. 09:45 - 11:15 Digital
Thursday 03.12. 09:45 - 11:15 Digital
Thursday 10.12. 09:45 - 11:15 Digital
Thursday 17.12. 09:45 - 11:15 Digital
Thursday 07.01. 09:45 - 11:15 Digital
Thursday 14.01. 09:45 - 11:15 Digital
Thursday 21.01. 09:45 - 11:15 Digital
Thursday 28.01. 09:45 - 11:15 Digital


Aims, contents and method of the course

The main scope of this course is an introduction to the programming language Python. The course covers the basics of programming, as well as in depth skills necessary for data analysis and optimization algorithms. The course content is provided in the form of video files. A continuous learning is assured by weekly homework assignments.

Assessment and permitted materials

Homework (20%), Midterm exam (30%), Endterm exam (40%), Theory exam (10%).
All submission will be online via Moodle. The exams will be online as well.

Minimum requirements and assessment criteria

For a positive grade, students have to achieve at least 50 percent (overall score).
Grading key:
4: 50% to <63%
3: 63% to <75%
2: 75% to <87%
1: 87% to 100%

Examination topics

Lecture notes, literature excerpts, home assignments

Reading list

Deitel, P. J., & Dietal, H. (2020). Intro to Python for Computer Science and Data Science: Learning to Program with AI, Big Data and the Cloud. Pearson Education, Incorporated.

Association in the course directory

Last modified: Mo 19.10.2020 14:47