RWTHx: A Hands-On Introduction to Process Mining

RWTHx: A Hands-On Introduction to Process Mining

by RWTH Aachen University

Process Mining Course

Offered by RWTHx

Course Description

Embark on an exciting journey into the world of Process Mining with this cutting-edge course offered by RWTHx. This introductory-level course is designed to equip you with the essential knowledge and practical skills needed to revolutionize operational processes across various industries. Process Mining is a powerful data-driven approach that can be applied to logistics, finance, production, sales, and healthcare, making it an invaluable tool for modern businesses.

What Students Will Learn

  1. Master the key concepts and techniques of Process Mining
  2. Understand automated process discovery and its applications
  3. Learn conformance checking methodologies
  4. Conduct performance analysis using Process Mining tools
  5. Apply machine learning techniques to event data
  6. Utilize the Celonis process mining software with real-life data sets
  7. Identify current trends in process management and automation
  8. Perform root cause analysis for performance and compliance issues
  9. Compare and analyze operational processes effectively
  10. Gain insights into the connections between Process Mining, data science, and machine learning

Prerequisites

  • Secondary school (high school) algebra
  • Basic understanding of mathematical concepts
  • Familiarity with business processes and their impact on organizations
  • Basic understanding of process inefficiencies

Course Content

  • Introduction to Process Mining and its applications
  • Process discovery techniques and directly-follows graphs
  • Advanced process modeling notations (DFGs, BPMN, and Petri nets)
  • Conformance checking methodologies (alignment-based, footprint-based, and token-based replay)
  • Extracting and analyzing event data
  • Object-centric event logs and their significance
  • Comparative and predictive Process Mining techniques
  • Integration of Process Mining with data science and machine learning
  • Hands-on experience with Celonis process mining software
  • Current trends in process management and automation

Who This Course Is For

  • Business analysts and process improvement specialists
  • Data scientists and IT professionals
  • Operations managers and team leaders
  • Students pursuing careers in business analytics or process management
  • Professionals in logistics, finance, production, sales, or healthcare industries
  • Anyone interested in leveraging data to optimize business processes

Real-World Applications

  1. Identifying bottlenecks and inefficiencies in business processes
  2. Improving operational efficiency and reducing costs
  3. Enhancing customer satisfaction through streamlined processes
  4. Ensuring compliance with industry regulations and internal policies
  5. Making data-driven decisions for process improvements
  6. Predicting and preventing potential process issues
  7. Automating repetitive tasks and processes
  8. Conducting root cause analysis for performance problems
  9. Optimizing resource allocation in various business functions
  10. Implementing continuous improvement strategies based on data insights

Syllabus

Week 1: Welcome and Basic Concepts

  • Overview of the Process Mining Field and Basic Concepts
  • Introduction to Celonis Tool

Week 2: Process Discovery

  • Process Discovery and Directly-Follows Graphs
  • Discover Sophisticated Process Models

Week 3: Conformance Checking

  • Alignment-Based Conformance Checking
  • Footprint-Based Conformance Checking
  • Token-Based Replay Conformance Checking

Week 4: Process Analysis

  • From Traditional Event Logs to Object-Centric Event Logs
  • Comparative and Predictive Process Mining

Week 5: Closing and Final Quiz

  • Closing Talk
  • Theoretical and Hands-on Final Exam (verified track)

By enrolling in this course, you'll gain a competitive edge in the rapidly evolving field of Process Mining, equipping yourself with the skills to drive innovation and efficiency in any organization.

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