Semester:WS 23/24
Type:Module
ECTS-Credits:3.0
Scheduled in semester:3
Semester Hours per Week / Contact Hours:30.0 L / 22.5 h
Self-directed study time:67.5 h
Type:Module
ECTS-Credits:3.0
Scheduled in semester:3
Semester Hours per Week / Contact Hours:30.0 L / 22.5 h
Self-directed study time:67.5 h
Module coordination/Lecturers
- Prof. Dr. Pavel Laskov
(Modulleitung)
Curricula
Master's degree programme in Information Systems (01.09.2019)Events
Description
Process Mining covers conceptual foundations, methods, and technologies for analysing business processes with the help of digital trace data that stems from information technology. In particular, students learn how to mine digital trace data. The course focuses on three primary topics:
- Petri-net foundations of process analysis
- Process mining algorithms
- Process mining tools and applications
Learning Outcomes
After successful completion of the course, students will:
- understand the foundational concepts of process mining
- understand how process mining algorithms work
- understand how a process mining project can be conducted in practice
Qualifications
Lectures Method
- The course involves interactive lectures with exercises to integrate theoretical knowledge with practical design and analysis skills.
- The e-learning platform Moodle is used throughout the course to disseminate course material and for information and discussion.
Admission Requirements
Though not mandatory, students should have attended the first-semester course Business Process Management.
Literature
Compulsory reading:
- Dumas, M., La Rosa, M., Mendling, J., & Reijers, H. (2018). Fundamentals of Business Process Management (2nd edition). Berlin, Germany: Springer.
Additional reading:
- Van der Aalst, W. (2011). Process Mining: Discovery, Conformance and Enhancement of Business Processes. Berlin, Germany: Springer.
Exam Modalities
Written exam (60min)