052412 VU Business Intelligence II (2021W)
Continuous assessment of course work
Labels
MIXED
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).
- Registration is open from Mo 13.09.2021 09:00 to Mo 20.09.2021 09:00
- Deregistration possible until Th 14.10.2021 23:59
Details
max. 25 participants
Language: English
Lecturers
Classes (iCal) - next class is marked with N
Kickoff Meeting (Online): 07.10. 09:45
Link: https://bbb.cs.univie.ac.at/b/mar-apf-koe-otc
Thursday
07.10.
09:45 - 13:00
Digital
Thursday
14.10.
09:45 - 13:00
Digital
Thursday
21.10.
09:45 - 13:00
Digital
Thursday
28.10.
09:45 - 13:00
Digital
Thursday
04.11.
09:45 - 13:00
Digital
Thursday
11.11.
09:45 - 13:00
Digital
Thursday
18.11.
09:45 - 13:00
Digital
Thursday
25.11.
09:45 - 13:00
Hörsaal 3, Währinger Straße 29 3.OG
PC-Unterrichtsraum 4, Währinger Straße 29 1.OG
PC-Unterrichtsraum 4, Währinger Straße 29 1.OG
Thursday
02.12.
09:45 - 13:00
Digital
Thursday
09.12.
09:45 - 13:00
Digital
Thursday
16.12.
09:45 - 13:00
Digital
Thursday
13.01.
09:45 - 13:00
Digital
Thursday
20.01.
09:45 - 13:00
Digital
Thursday
27.01.
18:30 - 21:30
Hörsaal 11 Oskar-Morgenstern-Platz 1 2.Stock
Hörsaal 13 Oskar-Morgenstern-Platz 1 2.Stock
Hörsaal 14 Oskar-Morgenstern-Platz 1 2.Stock
Hörsaal 13 Oskar-Morgenstern-Platz 1 2.Stock
Hörsaal 14 Oskar-Morgenstern-Platz 1 2.Stock
Information
Aims, contents and method of the course
Assessment and permitted materials
The grade is derived from the sum of the two parts (i.e. a maximum of 100 points in total):
* Part A: theoretical and practical exercises submitted individually (max. 55 points)
* Part B: written exam (no aids allowed, max. 45 points).
* Part A: theoretical and practical exercises submitted individually (max. 55 points)
* Part B: written exam (no aids allowed, max. 45 points).
Minimum requirements and assessment criteria
‣ Part A: 55% exercises (theoretical and practical)
‣ Part B: 45% written examIn Part A and Part B at least 50% of points need to be achieved and overall at least 50% of points need to be achieved.The grade is calculated from the total points as follows:
>= 87,5% very good (1)
>= 75% good (2)
>= 62,5% satisfactory (3)
>= 50% sufficient (4)
< 50% not sufficient (5)
‣ Part B: 45% written examIn Part A and Part B at least 50% of points need to be achieved and overall at least 50% of points need to be achieved.The grade is calculated from the total points as follows:
>= 87,5% very good (1)
>= 75% good (2)
>= 62,5% satisfactory (3)
>= 50% sufficient (4)
< 50% not sufficient (5)
Examination topics
* Lecture (slides)
* Exercises (theoretical and practical)
* Exercises (theoretical and practical)
Reading list
* Lecture slides are available in Moodle
* W. Grossmann, S. Rinderle-Ma: Fundamentals of Business Intelligence. Springer-Verlag Berlin Heidelberg (2015)
* W. van der Aalst. Process Mining, Springer (2016)
* M. Dumas, M. La Rosa, J. Mendling, H. A. Reijers: Fundamentals of Business Process Management. Springer (2018)
* W. Grossmann, S. Rinderle-Ma: Fundamentals of Business Intelligence. Springer-Verlag Berlin Heidelberg (2015)
* W. van der Aalst. Process Mining, Springer (2016)
* M. Dumas, M. La Rosa, J. Mendling, H. A. Reijers: Fundamentals of Business Process Management. Springer (2018)
Association in the course directory
Module: BUS BI2 DSA BI
Last modified: Fr 12.05.2023 00:13
* process mining
* social network mining
* process analysis
* decision miningIn addition, the following techniques will be discussed:
- Article spinners for businesses
- Stock exchange predictions
- Recommender systemsAll methods will be carried out in several exercises working on a variety of data from BI projects.Students, attending the course, are expected to have knowledge in the following topics:
* Advanced knowledge in Python3.6+ and performing machine learning and data analytics tasks
* Knowledge on process mining algorithms (alpha algorithm, genetic miner, heuristic miner)
* It is recommended but not mandatory to have participated in Business Intelligence I from SS 2021 (https://ufind.univie.ac.at/de/course.html?lv=052411&semester=2021S).