Universität Wien

040330 UK Programming for Business and Economic Analytics (MA) (2025W)

8.00 ECTS (4.00 SWS), SPL 4 - Wirtschaftswissenschaften
Continuous assessment of course work
MIXED
Moodle
Tu 02.12. 11:30-13:00 PC-Seminarraum 5 Oskar-Morgenstern-Platz 1 1.Untergeschoß

Registration/Deregistration

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

Details

max. 50 participants
Language: English

Lecturers

Classes (iCal) - next class is marked with N

  • Wednesday 12.11. 13:15 - 14:45 PC-Seminarraum 2 Oskar-Morgenstern-Platz 1 1.Untergeschoß
  • Friday 14.11. 09:45 - 11:15 PC-Seminarraum 2 Oskar-Morgenstern-Platz 1 1.Untergeschoß
  • Tuesday 18.11. 09:45 - 11:15 PC-Seminarraum 2 Oskar-Morgenstern-Platz 1 1.Untergeschoß
  • Wednesday 26.11. 13:15 - 14:45 PC-Seminarraum 2 Oskar-Morgenstern-Platz 1 1.Untergeschoß
  • Thursday 27.11. 09:45 - 11:15 PC-Seminarraum 2 Oskar-Morgenstern-Platz 1 1.Untergeschoß
  • Wednesday 10.12. 13:15 - 14:45 PC-Seminarraum 2 Oskar-Morgenstern-Platz 1 1.Untergeschoß
  • Thursday 11.12. 09:45 - 11:15 Digital
  • Friday 12.12. 09:45 - 11:15 PC-Seminarraum 2 Oskar-Morgenstern-Platz 1 1.Untergeschoß
  • Monday 15.12. 09:45 - 11:15 PC-Seminarraum 5 Oskar-Morgenstern-Platz 1 1.Untergeschoß
  • Tuesday 16.12. 09:45 - 11:15 PC-Seminarraum 2 Oskar-Morgenstern-Platz 1 1.Untergeschoß
  • Wednesday 07.01. 15:00 - 16:30 PC-Seminarraum 5 Oskar-Morgenstern-Platz 1 1.Untergeschoß
  • Thursday 08.01. 09:45 - 11:15 PC-Seminarraum 5 Oskar-Morgenstern-Platz 1 1.Untergeschoß
  • Monday 12.01. 09:45 - 11:15 Digital
  • Tuesday 13.01. 11:30 - 13:00 PC-Seminarraum 5 Oskar-Morgenstern-Platz 1 1.Untergeschoß
  • Wednesday 21.01. 13:15 - 14:45 PC-Seminarraum 2 Oskar-Morgenstern-Platz 1 1.Untergeschoß
  • Friday 23.01. 09:45 - 11:15 PC-Seminarraum 2 Oskar-Morgenstern-Platz 1 1.Untergeschoß
  • Monday 26.01. 09:45 - 11:15 Digital
  • Tuesday 27.01. 11:30 - 13:00 Hörsaal 9 Oskar-Morgenstern-Platz 1 1.Stock

Information

Aims, contents and method of the course

This course introduces Python programming fundamentals tailored for Applied Economics students, emphasizing practical data analysis and computational skills essential for economic research. Students will learn to use Python as a powerful tool for economic analysis, data manipulation, and quantitative research. The course bridges programming concepts with real-world economic applications.

Main topics:
- Introduction to programming
- Python basics
- Data structures fundamentals
- Scientific computing with numpy
- Data processing with pandas
- Machine Learning & AI basics
- Python for problems in Applied Economics

Content delivery occurs in weekly hybrid sessions, with homework assignments to deepen the practical skills.
The students will be enabled to work on a final quantitative mini-project in the area of Business & Economics.

Assessment and permitted materials

Final exam (on-site multiple choice): 40%
Homework assignments: 20%
Mini-project: 40%

Minimum requirements and assessment criteria

For a positive grade, students have to achieve at least 50 percent of the maximum score (overall) AND the theory exam has to be positive (>= 50%).
Grading key:
4: 50% to <63%
3: 63% to <75%
2: 75% to <87%
1: 87% to 100%

Examination topics

- Lecture slides
- Python code developed together in class (live .ipynb notebooks)
- Library documentation (where indicated)

Reading list

- Python language reference
- Official online documentation of used libraries

Association in the course directory

Last modified: We 12.11.2025 07:25