Process Mining: Data science in Action Course Syllabus

Overview: This course provides a comprehensive, hands-on introduction to process mining, combining theoretical foundations with practical applications using industry-standard tools. Designed for professionals seeking to leverage data for process optimization, the curriculum spans six modules totaling approximately 21 hours. Learners will explore process discovery, conformance checking, and performance analysis using real event logs, culminating in a capstone project. Lifetime access ensures flexible learning at your own pace.

Module 1: Introduction and Data Mining Basics

Estimated time: 5 hours

• Introduction to process mining and its applications
• Understanding event logs and their structure
• Types of process mining analyses: discovery, conformance, and enhancement
• Role of data in process-aware decision making

Module 2: Process Models and Process Discovery

Estimated time: 3 hours

• Fundamentals of process modeling
• Introduction to Petri nets as modeling formalism
• Applying the Alpha Miner algorithm
• Generating process models from event logs

Module 3: Different Types of Process Models

Estimated time: 3 hours

• Advanced process modeling techniques
• Introduction to BPMN (Business Process Model and Notation)
• Causal nets for representing workflow dependencies
• Comparing modeling formalisms for different use cases

Module 4: Discovery and Conformance Checking

Estimated time: 3 hours

• Techniques for process discovery from logs
• Conformance checking fundamentals
• Identifying deviations between actual and modeled processes
• Applications in compliance and auditing

Module 5: Operational Support and Predictive Insights

Estimated time: 3 hours

• Real-time monitoring of business processes
• Predictive process analytics
• Performance enhancement using mining results
• Identifying inefficiencies and bottlenecks

Module 6: Final Project

Estimated time: 5 hours

• Analyze real-world event data using ProM or Disco
• Discover and visualize a process model
• Perform conformance checking and report findings

Prerequisites

• Basic understanding of data analysis concepts
• Familiarity with fundamental modeling ideas
• Some exposure to business processes or workflows

What You'll Be Able to Do After

• Discover process models from event logs using algorithms like Alpha Miner
• Apply conformance checking to assess process compliance
• Enhance models with performance data to identify inefficiencies
• Use tools like ProM and Disco for real-world process analysis
• Support operational decision-making with data-driven process insights