Due to the large success of the previous two runs, this 6 week online course is 
repeated as of October. The course provides data science knowledge that can be 
applied directly to analyze and improve processes in a variety of domains.

Starts: October 7, 2015

For more information and to register visit:
Process Mining: Data science in Action<https://www.coursera.org/course/procmin>.

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).

Process mining 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. Over 65,000 participants joined in the 
first two runs where they learned 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 were also presented. 
Moreover, the course provides easy-to-use software, real-life data sets, and 
practical skills to directly apply the theory in a variety of application 
domains. To give everyone who missed the previous runs a chance to follow this 
course, the course runs again as of October 7, 2015.



Kind regards,

[TUe_top]

dr.ir. J.C.A.M. (Joos) Buijs
Post-Doctoral Researcher
Fac. Wiskunde & Informatica

[email protected]<mailto:[email protected]>
http://www.tue.nl/staff/j.c.a.m.buijs

Not in the office on Mondays

Den Dolech 2, 5612 AZ
P.O. Box 513, MF 7.062
5600 MB Eindhoven
The Netherlands

In case a direct reply is desired:
Office MF 7.062
Lync [email protected]<sip:[email protected]>
Skype joos.buijs
M +31 6 42 77 89 88 (preferred)
T +31 40 247 3661



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