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Regular version of the site

Massive Open Online Course: "Process Mining: Data science in Action"

On November 12th 2014 starts Massive Open Online Course (MOOC) "Process Mining: Data science in Action", the course of PAIS Lab Academic Supervisor, Professor of the Eindhoven Technical University Wil van der Aalst. Already 24 000 participants from 170 countries registered for this first MOOC of Process Mining.

Watch the video on https://www.coursera.org/course/procmin for more information. Here you can also register for this 6 week course.

 

Data science  is the profession of the future, because organizations that are unable to use (big) data in a smart way will not survive. It is not sufficient to focus on data storage and data analysis. The data scientist also needs to relate data to process analysis.  Process mining bridges the gap between traditional model-based process analysis (e.g., simulation and other business process management techniques) and data-centric analysis techniques such as machine learning and data mining.  Process mining seeks the confrontation between event data (i.e., observed behavior) and process models (hand-made or discovered automatically). This technology has become available only recently, but it can be applied to any type of operational processes (organizations and systems). Example applications include: analyzing treatment processes in hospitals, improving customer service processes in a multinational, understanding the browsing behavior of customers using a booking site, analyzing failures of a baggage handling system, and improving the user interface of an X-ray machine. All of these applications have in common that dynamic behavior needs to be related to process models. Hence, we refer to this as "data science in action". 

The Coursera course “Process Mining: Data science in Action” explains the key analysis techniques in process mining. Participants will learn various process discovery algorithms. These can be used to automatically learn process models from raw event data. Various other process analysis techniques that use event data will be presented. Moreover, the course will provide  easy-to-use software,  real-life data sets, and  practical skills  to  directly apply the theory  in a variety of application domains. See https://www.coursera.org/course/procmin for details.