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Process Mining with Celonis (Beginner Level)

Process mining and OCPM on the Celonis platform using Process Explorer and Variant Explorer for analysis | PI

This course provides a practical introduction to Celonis Process Mining, focusing on how organisations use real execution data to understand, analyse, and improve their business processes. You will learn how process mining works in practice, how data is transformed into process views, and how Celonis enables analysts to identify inefficiencies, deviations, and improvement opportunities based on facts rather than assumptions.

What you’ll learn

Course Content

Requirements

This course provides a practical introduction to Celonis Process Mining, focusing on how organisations use real execution data to understand, analyse, and improve their business processes. You will learn how process mining works in practice, how data is transformed into process views, and how Celonis enables analysts to identify inefficiencies, deviations, and improvement opportunities based on facts rather than assumptions.

By the end of the course, you will understand  how to use Celonis, and its modules – Studio, Apps, Action Flows, Transformation Hub and more. We will learn how to interpret process mining results correctly — how to read process flows, analyse variants, and translate insights into concrete improvement actions.

 

This course is ideal for business analysts, process consultants, transformation teams, and anyone involved in operational excellence or digital transformation who wants a clear, tool-based introduction to process mining using Celonis.

 

Upon completion of the course, learners will receive a Certificate of Completion recognising their foundational skills in Celonis process mining.

 

This is our Level 1 course, focused on introducing the fundamentals of process mining and the Celonis platform. In the Level 2 course, we go deeper into more advanced analytical techniques in Celonis.

This course uses artificial intelligence only to emulate my voice for voice-over narration.

Lia and Team