052412 VU Business Intelligence II (2024W)
Continuous assessment of course work
Labels
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 Fr 13.09.2024 09:00 to Fr 20.09.2024 09:00
- Deregistration possible until Mo 14.10.2024 23:59
Details
max. 25 participants
Language: English
Lecturers
Classes (iCal) - next class is marked with N
- Thursday 03.10. 09:45 - 13:00 PC-Unterrichtsraum 2, Währinger Straße 29 1.OG
- Thursday 10.10. 09:45 - 13:00 PC-Unterrichtsraum 2, Währinger Straße 29 1.OG
- Thursday 17.10. 09:45 - 13:00 PC-Unterrichtsraum 2, Währinger Straße 29 1.OG
- Thursday 24.10. 09:45 - 13:00 PC-Unterrichtsraum 2, Währinger Straße 29 1.OG
- Thursday 31.10. 09:45 - 13:00 PC-Unterrichtsraum 2, Währinger Straße 29 1.OG
- Thursday 07.11. 09:45 - 13:00 PC-Unterrichtsraum 2, Währinger Straße 29 1.OG
- Thursday 14.11. 09:45 - 13:00 PC-Unterrichtsraum 2, Währinger Straße 29 1.OG
- Thursday 21.11. 09:45 - 13:00 PC-Unterrichtsraum 2, Währinger Straße 29 1.OG
- Thursday 28.11. 09:45 - 13:00 PC-Unterrichtsraum 2, Währinger Straße 29 1.OG
- Thursday 28.11. 11:30 - 13:00 Seminarraum 2, Währinger Straße 29 1.UG
- Thursday 05.12. 09:45 - 13:00 PC-Unterrichtsraum 2, Währinger Straße 29 1.OG
- Thursday 12.12. 09:45 - 13:00 PC-Unterrichtsraum 2, Währinger Straße 29 1.OG
- Thursday 09.01. 09:45 - 13:00 PC-Unterrichtsraum 2, Währinger Straße 29 1.OG
- Thursday 16.01. 09:45 - 13:00 PC-Unterrichtsraum 2, Währinger Straße 29 1.OG
- Thursday 23.01. 09:45 - 13:00 PC-Unterrichtsraum 2, Währinger Straße 29 1.OG
- Thursday 30.01. 11:30 - 13:00 Hörsaal 1, Währinger Straße 29 1.UG
- Thursday 20.02. 13:15 - 14:45 Seminarraum 6, Währinger Straße 29 1.OG
Information
Aims, contents and method of the course
Assessment and permitted materials
The performance assessment in the Business Intelligence II course is formed by the sum of three components:
1) Group project: max. 35% (including Presentation)
2) Exam on Part A (fundamental topics): max 35%
4) Exam on Part B (advanced topics): max. 30%
1) Group project: max. 35% (including Presentation)
2) Exam on Part A (fundamental topics): max 35%
4) Exam on Part B (advanced topics): max. 30%
Minimum requirements and assessment criteria
Overall at least 50% of the points need to be achieved.The grade is calculated from the total points of the components as follows:
>= 87,5% very good (1)
>= 75% good (2)
>= 62,5% satisfactory (3)
>= 50% sufficient (4)
< 50% not sufficient (5)
>= 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)
* Selected book chapters/sections
* Exercises (theoretical and practical)
* Selected book chapters/sections
Reading list
· Wil van der Aalst: Process Mining: Data Science in Action, 2nd edition (Recommended)
· Josep Carmona et al. Conformance checking, 1st edition (Recommended)
Relevant chapters and sections will be indicated per lecture.
· Josep Carmona et al. Conformance checking, 1st edition (Recommended)
Relevant chapters and sections will be indicated per lecture.
Association in the course directory
Module: BUS BI2 DSA BI
Last modified: Fr 14.02.2025 11:25
The course features lectures and exercises that focus on the formal foundations, algorithms, and techniques of process mining. The course will be divided in two main parts.Part A will focus on fundamental tasks in process mining, namely:
· Process discovery, which aims to derive a process model from recorded events
· Conformance checking, which aims to identify deviations between event data and process models
For the above subjects, the course will cover fundamental algorithms as well as advanced, state-of-the-art techniques.Part B will focus on advanced topics, such as:
- Event log extraction, quality and preprocessing
- Predictive process monitoring
- Object-centric process miningThe course will combine lectures with practical exercises, include a guest lecture and practical session with a leading process mining company. Examinations that target your understanding and ability to apply the covered concepts will be complemented with a replication study, in which you dive deep into state-of-the-art research.***Prerequisites***
- You are not required to have taken Business Intelligence I (there will be some redundancy)
- Familiarity with process modeling (BPMN or Petri nets) is helpful but not expected
- Basic programming skills are required for the practical exercises (Python) and group project