Universität Wien
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040101 KU Advanced Business Analytics (MA) (2020W)

6.00 ECTS (3.00 SWS), SPL 4 - Wirtschaftswissenschaften
Continuous assessment of course work

The course language is English.

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

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

Watch the short welcome video!

This is a hybrid class: generally, lectures will be streamed and recorded. This means that you can participate in the classroom (with distance) or online and/or watch the recorded lecture at a later time.

  • Tuesday 06.10. 11:30 - 13:00 Digital
  • Wednesday 07.10. 09:45 - 11:15 Digital
  • Tuesday 13.10. 11:30 - 13:00 Digital
  • Wednesday 14.10. 09:45 - 11:15 Digital
  • Tuesday 20.10. 11:30 - 13:00 Digital
  • Wednesday 21.10. 09:45 - 11:15 Digital
  • Tuesday 27.10. 11:30 - 13:00 Digital
  • Wednesday 28.10. 09:45 - 11:15 Digital
  • Tuesday 03.11. 11:30 - 13:00 Digital
  • Wednesday 04.11. 09:45 - 11:15 Digital
  • Tuesday 10.11. 11:30 - 13:00 Digital
  • Wednesday 11.11. 09:45 - 11:15 Digital
  • Tuesday 17.11. 11:30 - 13:00 Digital
  • Wednesday 18.11. 09:45 - 11:15 Digital
  • Tuesday 24.11. 11:30 - 13:00 Digital
  • Wednesday 25.11. 09:45 - 11:15 Digital
  • Tuesday 01.12. 11:30 - 13:00 Digital
  • Wednesday 02.12. 09:45 - 11:15 Digital
  • Wednesday 09.12. 09:45 - 11:15 Digital
  • Tuesday 15.12. 11:30 - 13:00 Digital
  • Wednesday 16.12. 09:45 - 11:15 Digital
  • Tuesday 12.01. 11:30 - 13:00 Digital
  • Wednesday 13.01. 09:45 - 11:15 Digital
  • Tuesday 19.01. 11:30 - 13:00 Digital
  • Wednesday 20.01. 09:45 - 11:15 Digital
  • Tuesday 26.01. 11:30 - 13:00 Digital
  • Wednesday 27.01. 09:45 - 11:15 Digital

Information

Aims, contents and method of the course

In this course, fundamentals of business analytics will be covered. The students will be able to derive relevant business knowledge through methods of advanced business analytics from large, complex databases.
They will be able to identify the underlying analytics tasks of a business problem, to select and apply appropriate data mining algorithms, and to derive plans of actions from their outputs to solve the business problems. The students will have an overview of relevant analytics methods, including a selection of particular methods such as explorative data analysis, descriptive and predictive modelling (e.g. cluster analysis, association analysis, classification).

Assessment and permitted materials

Midterm test (40%): Nov 10, 11:30
Final test (40%): Jan 27, 09:45
Homework (20%):
-- Submission 1: Mon, Nov 30, 12:00
-- Submission 2: Mon, Jan 18, 12:00

Minimum requirements and assessment criteria

Midterm test and one more examination (homework / final test) must be passed individually. In total, 100 points can be achieved. Grades are assigned as follows:
1 (very good) • 100-90 points
2 (good) • 89-76 points
3 (satisfactory) • 75-63 points
4 (sufficient) • 62-50 points
5 (not enough) • 49-0 points

Examination topics

Midterm test/Final test: Slides and topics covered in the lectures and exercises.
Homework: topics covered in the exercises.

Reading list

Provost/Fawcett: Data Science for Business - What you need to know about data mining and data-analytic thinking. http://www.data-science-for-biz.com/

Berthold/Klawonn: Guide to Intelligent Data Analysis, Springer

Association in the course directory

Last modified: Fr 12.05.2023 00:12