TU/e - Process Mining: Data science in Action

Process Mining: Data science in Action
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Coursera
Overview

Skills you will learn

What are the course deliverables?

After taking this course you should:
-have a good understanding of Business Process Intelligence techniques (in particular process mining)
- understand the role of Big Data in today's society
- be able to relate process mining techniques to other analysis techniques such as simulation, business intelligence, data mining, machine learning, and verification
- be able to apply basic process discovery techniques to learn a process model from an event log (both manually and using tools)
- be able to apply basic conformance checking techniques to compare event logs and process models (both manually and using tools),
- be able to extend a process model with information extracted from the event log (e.g., show bottlenecks)
- have a good understanding of the data needed to start a process mining project
- be able to characterize the questions that can be answered based on such event data
- explain how process mining can also be used for operational support (prediction and recommendation), and - be able to conduct process mining projects in a structured manner.

More about this course

The course 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.
This course starts with an overview of approaches and technologies that use event data to support decision making and business process (re)design. Then the course focuses on process mining as a bridge between data mining and business process modeling. The course is at an introductory level with various practical assignments.