What will you learn in this Process Mining: Data science in Action Course
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Understand the fundamental principles of process mining and its role in data-driven decision making.
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Discover process models from event logs using algorithms like Alpha Miner.
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Apply conformance checking techniques to compare actual processes with predefined models.
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Enhance process models with performance-related data to identify inefficiencies.
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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
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Equips learners for roles such as Process Analyst, Business Intelligence Analyst, and Data Scientist.
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Highly applicable in industries like healthcare, logistics, IT services, manufacturing, and finance.
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Builds practical knowledge for process optimization, compliance auditing, and performance monitoring.
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Helps companies improve operational efficiency by transforming event data into actionable insights.
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Related Reading
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