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040101 KU Advanced Business Analytics (MA) (2020W)
Continuous assessment of course work
Labels
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.
Registration/Deregistration
Note: The time of your registration within the registration period has no effect on the allocation of places (no first come, first serve).
- Registration is open from Mo 14.09.2020 09:00 to We 23.09.2020 12:00
- Deregistration possible until Sa 31.10.2020 12:00
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
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
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
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.
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: Th 28.01.2021 16:08
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).