Process mining course FTW
I have just finished the last week of a six week course on Process Mining. The course was hosted by Coursera, and was taught by one of the main academics on the topic, Prof. Wil M. P. van der Aalst.
The workload was quite intense as each week consisted of lectures, a quiz (and two chapters of reading time in the course text book). On top of this, we got an mini mining project assignment, a tool quiz and a final exam. A lot of the topics were new to me, and I only survived because I have a Ms. degree in mathematics and because I have worked with time-related KPI's in Effektors Linea module.
Week 1 covered an introduction to process mining, different process models and notations (Transition systems, Petri nets, Workflow nets) as well as normal data mining methods and algorithms (decision trees, k-means clustering and association rules)
Week 2 was on model-based process analysis and the first simple process discovery algorithm: the alpha algorothm
Week 3 was about the quality of mined models, representational bias, BPMN and causal nets.
Week 4 was about advanced process discovery algorithms and techniques (heuristic mining, genetic mining and region-based mining)
Week 5 was dedicated to conformance checking (token replay and footprint comparisons) as well as organizational mining, performance measurements and classical usage of data mining in decision mining
Week 6 concluded the course with discussions of a full process mining framework, available tools, as well as examples of lasagna and spaghetti processes.
A true tour de force of mathematics, formal computer science and algorithms, applied to very concrete types of data and presenting very relevant techniques to handle reporting problems on process data in businesses all around us.
Was it good. Hell yeah! It tells that Prof. Wil M. P. van der Aalst.have worked in this field for many years, and there was a good relation between the lectures and the text book. I enjoyed Prof. Wil M. P. van der Aalst's teaching style and learned A LOT. So I will definitely recommend the course to every data scientist who want to expand her toolbox towards this new and interesting field. But make sure that you have the time to invest to truly dive in and get a grip on details in this very exciting field. I'm sure it's worth it, both from an academic and a professional point of view.
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