Process Mining

Modulnummer: Q09-02
Englischer Titel: Process Mining
Leistungspunkte: 9
Lehrperson: Weidlich

Empfohlene Vorkenntnisse

- Foundations of Softare Design (e.g., the course "Modelling and Specification")

Zwingende Voraussetzungen

- The course can only be taken by students that have not completed the old module Q5-5 of the same name.

Inhalt

One emerging branch of data science is process mining. In the field of process automation, process mining aims at deriving qualitative and quantitative insights on the execution of a process based on recorded events logs.

The course focuses on the formal foundations and basic techniques of process mining. Specifically, this includes algorithms for process discovery that construct models from event data. Also, essential conformance checking techniques to identify deviations between models and event data, e.g., by replay or alignment construction will be discussed. Finally, advanced techniques for model extension, process simulation, and performance prediction will be reviewed.

The lectures are complemented with exercises, in which course participants are exposed to real-world data and work with process mining techniques. The exercises include a project work that takes up state-of-the-art developments in the field.

Erforderliche Arbeitsleistungen für LP-Vergabe und Prüfungszulassung

Successful completion of the project work, which may include

- submissions of written reports on assigned tasks

- presentations on the solutions for assigned tasks

- the development and application of software

Lehrveranstaltungen

Vorlesung: 4 SWS
Übung: 2 SWS

Zugeordneter Vertiefungsschwerpunkt

Algorithmen und Modelle: nein
Modellbasierte Systementwicklung: nein
Daten- und Wissensmanagement: ja
Ohne Vertiefungsschwerpunkt: nein

Sprache im Modul

Deutsch: nein
Englisch: ja

Angeboten für Studiengänge

M. Sc.: ja
M. Ed.: ja
Wirtschaftsmaster: ja

Angeboten im

Wintersemester: ja
Sommersemester: nein

Turnus

Jedes Jahr