About this Course
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Intermediate Level


Subtitles: English

Skills you will gain

Petri NetProcess ModelingProcess MiningData Mining

100% online

Start instantly and learn at your own schedule.

Flexible deadlines

Reset deadlines in accordance to your schedule.

Intermediate Level


Subtitles: English

Syllabus - What you will learn from this course

6 hours to complete

Introduction and Data Mining

This first module contains general course information (syllabus, grading information) as well as the first lectures introducing data mining and process mining.

18 videos (Total 228 min), 7 readings, 2 quizzes
18 videos
1.3: How Process Mining Relates to Data Mining20m
1.4: Learning Decision Trees26m
1.5: Applying Decision Trees20m
1.6: Association Rule Learning18m
1.7: Cluster Analysis13m
1.8: Evaluating Mining Results14m
Introducing Fluxicon & Disco10m
Real Life Session 01: The Demo Scenario (7 min.)7m
Real Life Session 02: Process Discovery and Simplification (11 min.)10m
Real Life Session 03: Statistics, Cases and Variants (8 min.)7m
Real Life Session 04: Bottleneck Analysis (7 min.)7m
Real Life Session 05: Compliance Analysis (6 min.)5m
Real Life Session 06: Tip 1 - Keep Copies of your Analyses (4 min.)4m
Real Life Session 07: Tip 2 - Take Different Views on your Process (7 min.)7m
Real Life Session 08: Tip 3 - Exporting Results (4 min.)4m
7 readings
Welcome to Process Mining: Data Science in Action10m
The Forum is your (Extended) Classroom10m
Process Mining: Data Science in Action Getting Started!10m
[Extra] The data used in the lectures10m
How is Process Mining Different from Data Mining?10m
Quick Note Regarding Quizzes in this Course10m
Real-life Process Mining Session10m
2 practice exercises
Quiz 120m
Real-life Process Mining Session Quiz (Not for points)12m
4 hours to complete

Process Models and Process Discovery

In this module we introduce process models and the key feature of process mining: discovering process models from event data.

8 videos (Total 159 min), 1 reading, 2 quizzes
8 videos
2.4: Transition Systems and Petri Net Properties20m
2.5: Workflow Nets and Soundness16m
2.6: Alpha Algorithm: A Process Discovery Algorithm25m
2.7: Alpha Algorithm: Limitations23m
2.8: Introducing ProM and Disco25m
1 reading
Using Event Data to Tear Down the Towers of Babel in Process Management10m
2 practice exercises
Quiz 220m
Tool Quiz40m
3 hours to complete

Different Types of Process Models

Now that you know the basics of process mining, it is time to dive a little bit deeper and show you other ways of discovering a process model from event data.

8 videos (Total 145 min), 1 reading, 1 quiz
8 videos
3.4: Dependency Graphs and Causal Nets21m
3.5: Learning Dependency Graphs21m
3.6: Learning Causal nets and Annotating Them18m
3.7: Learning Transition Systems14m
3.8: Using Regions to Discover Concurrency18m
1 reading
Process Mining in the Large: Smart Data Scientists Are More Important Than Big Computers!!10m
1 practice exercise
Quiz 320m
5 hours to complete

Process Discovery Techniques and Conformance Checking

In this module we conclude process discovery by discussing alternative approaches. We also introduce how to check the conformance of the event data and the process model.

8 videos (Total 129 min), 1 reading, 2 quizzes
8 videos
4.4: Conformance Checking Using Causal Footprints10m
4.5: Conformance Checking Using Token-Based Replay14m
4.6: Token Based Replay: Some Examples15m
4.7: Aligning Observed and Modeled Behavior18m
4.8: Exploring Event Data20m
1 reading
Conformance Checking: Positive and Negative Deviants10m
1 practice exercise
Quiz 420m
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Top reviews from Process Mining: Data science in Action

By ECJul 31st 2017

Great course. Professor Wil van der Aalst delivers great lectures, very clear and deep in general with good examples. I really enjoyed the course from the beginning to the end.

By MTJan 29th 2018

This course was wonderful. I have attempted it several times, but did not find enough time to finish it until lately. Dr. van der Aalst is magnificent in his presentation.



Wil van der Aalst

Professor dr.ir.
Department of Mathematics & Computer Science

About Eindhoven University of Technology

Eindhoven University of Technology (TU/e) is a research-driven, design-oriented university of technology with a strong international focus. The university was founded in 1956, and has around 8,500 students and 3,000 staff. TU/e has defined strategic areas focusing on the societal challenges in Energy, Health and Smart Mobility. The Brainport Eindhoven region is one of world’s smartest; it won the title Intelligent Community of the Year 2011....

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