Universität Wien

040123 KU Programming for Business Analytics (MA) (2024W)

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

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.
Moodle
Tu 12.11. 16:45-18:15 Digital

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

  • Tuesday 01.10. 16:45 - 18:15 Digital
  • Thursday 03.10. 15:00 - 18:15 Hörsaal 17 Oskar-Morgenstern-Platz 1 2.Stock
  • Thursday 10.10. 15:00 - 18:15 Hörsaal 17 Oskar-Morgenstern-Platz 1 2.Stock
  • Tuesday 15.10. 16:45 - 18:15 Digital
  • Thursday 17.10. 15:00 - 18:15 Hörsaal 17 Oskar-Morgenstern-Platz 1 2.Stock
  • Thursday 24.10. 15:00 - 18:15 Hörsaal 17 Oskar-Morgenstern-Platz 1 2.Stock
  • Tuesday 29.10. 16:45 - 18:15 Digital
  • Thursday 31.10. 15:00 - 18:15 Hörsaal 17 Oskar-Morgenstern-Platz 1 2.Stock
  • Thursday 07.11. 15:00 - 18:15 Hörsaal 17 Oskar-Morgenstern-Platz 1 2.Stock
  • Thursday 14.11. 15:00 - 18:15 Hörsaal 17 Oskar-Morgenstern-Platz 1 2.Stock
  • Thursday 21.11. 15:00 - 18:15 Hörsaal 17 Oskar-Morgenstern-Platz 1 2.Stock
  • Tuesday 26.11. 16:45 - 18:15 Digital
  • Thursday 28.11. 15:00 - 18:15 Hörsaal 17 Oskar-Morgenstern-Platz 1 2.Stock
  • Thursday 05.12. 15:00 - 18:15 Hörsaal 17 Oskar-Morgenstern-Platz 1 2.Stock
  • Tuesday 10.12. 16:45 - 18:15 Digital
  • Thursday 12.12. 15:00 - 18:15 Hörsaal 17 Oskar-Morgenstern-Platz 1 2.Stock
  • Tuesday 07.01. 16:45 - 18:15 Digital
  • Thursday 09.01. 15:00 - 18:15 Hörsaal 17 Oskar-Morgenstern-Platz 1 2.Stock
  • Thursday 16.01. 15:00 - 18:15 Hörsaal 17 Oskar-Morgenstern-Platz 1 2.Stock
  • Tuesday 21.01. 16:45 - 18:15 Digital
  • Thursday 23.01. 15:00 - 18:15 Hörsaal 17 Oskar-Morgenstern-Platz 1 2.Stock
  • Thursday 30.01. 15:00 - 18:15 Hörsaal 17 Oskar-Morgenstern-Platz 1 2.Stock

Information

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 consists of a weekly on-site lecture (3 hours) and a biweekly online exercise session (2 hours).

Assessment and permitted materials

Exercises 30% - Submitted to Moodle before exercise session.
Theoretical exam 30% - On site exam at the end of the term.
Applied project 40% - Final discussions will take place in February and March.

Minimum requirements and assessment criteria

x = Total points in percent

5: x < 50%
4: 50% <= x < 62.5%
3: 62.5% <= x < 75%
2: 75% <= x < 87.5%
1: 87.5% <= x

Examination topics

Lecture notes, literature excerpts, home assignments

Reading list

An Introduction to Statistical Learning with Applications in Python (2023) by G. James, D. Witten, T. Hastie, R. Tibshirani and J. Taylor

Available for free download: https://www.statlearning.com

Association in the course directory

Last modified: We 25.09.2024 10:25