IE 692: Advanced Process Mining (FSS 2024)

Process mining is an emerging branch of data science that aims at deriving qualitative and quantitative insights on the execution of organizational processes, based on the analysis of recorded event sequences.

The course features lectures and exercises that focus on the formal foundations, algorithms, and techniques of process mining. Specifically, this course covers aspects such as:

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
Process enhancement, which aims to augment process models with information on the temporal, organizational, and data perspectives of a process
Predictive monitoring, which aims to make predictions about ongoing process instances
Techniques to preprocess, abstract, cluster event data for improved analyses

For the above subjects, the course will cover fundamental algorithms as well as advanced, state-of-the-art techniques.

During the exercises that follow each lecture, you will practice through pen-and-paper exercises, as well as implementation and evaluation using open source process mining tools and libraries.

The lectures and exercises are complemented by a practical assignment in which students will work in groups on a project that involves implementation and/or evaluation of a process mining technique.

Goals

After completing this course, you will be able to:

Understand the importance and potential of process mining
Know and apply both fundamental and advanced techniques for core process mining tasks
Be able to analyze real-world data using open-source process mining tools

Organization

Lecturer: Jana-Rebecca Rehse
Tutors: Alexander Kraus and Adrian Rebmann
Type of course: Lecture, exercises, group assignment (6 ECTS)
Registration: enroll in Portal2

Prerequisites

You are expected to be familiar with the use of Petri nets and BPMN for process modeling, and being able to do basic programming in Python. IS 515 or having experience with process mining are NOT prerequisites.