What will you learn in this Process Mining: Data science in Action Course
Understand the fundamental principles of process mining and its role in data-driven decision making.
Discover process models from event logs using algorithms like Alpha Miner.
Apply conformance checking techniques to compare actual processes with predefined models.
Enhance process models with performance-related data to identify inefficiencies.
Gain hands-on experience with process mining tools such as ProM and Disco
Program Overview
1. Introduction and Data Mining Basics
⏳ 5 hours
Introduces the scope of process mining, types of analyses, and the role of event logs in extracting useful process information.
2. Process Models and Process Discovery
⏳ 3 hours
Covers the use of Petri nets and introduces Alpha Miner for generating process models from logs.
3. Different Types of Process Models
⏳ 3 hours
Explores advanced modeling techniques including BPMN and causal nets, used to represent complex workflows.
4. Discovery and Conformance Checking
⏳ 3 hours
Focuses on comparing real-life event data with expected models to detect deviations and compliance issues.
5. Operational Support and Predictive Insights
⏳ 3 hours
Demonstrates how process mining supports monitoring, prediction, and improvement of ongoing processes in real time.
6. Course Wrap-up and Final Project
⏳ 5 hours
Applies all covered concepts in a capstone project analyzing real-world datasets using tools like ProM.
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Job Outlook
Equips learners for roles such as Process Analyst, Business Intelligence Analyst, and Data Scientist.
Highly applicable in industries like healthcare, logistics, IT services, manufacturing, and finance.
Builds practical knowledge for process optimization, compliance auditing, and performance monitoring.
Helps companies improve operational efficiency by transforming event data into actionable insights.
Specification: Process Mining: Data science in Action
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