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

Event Details

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

Time: November 12, 2014 at 1pm to December 24, 2014 at 12pm
Location: Coursera
Website or Map: https://www.coursera.org/cour…
Event Type: free, online, course
Organized By: Wil van der Aalst
Latest Activity: Sep 9, 2014

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Event Description

On November 12th 2014 the first MOOC of Process Mining starts. Watch the video https://www.youtube.com/watch?v=jOOI2NBsHd0 or visit https://www.coursera.org/course/procmin for more information and to 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 softwarereal-life data sets, and practical skills to directly apply the theory in a variety of application domains.

 

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