A self-paced learning hub that explains process mining concepts, event logs, bottleneck detection, and how process intelligence tools are used to improve operational workflows.
Live site: https://liyrs58.github.io/process-mining-hub/
This project was built as a structured learning artifact rather than a generic notes page. It breaks process mining into practical modules and connects the theory to the kinds of business questions analysts face in operations, consulting, finance, and enterprise software.
- Process mining fundamentals and terminology
- Event logs, case IDs, activities, timestamps, and process variants
- Bottleneck and rework analysis
- Conformance checking and root-cause investigation
- How platforms such as Celonis position process intelligence in real organisations
- Certifications and learning evidence collected during the project
| Area | Evidence |
|---|---|
| Business analysis | Connects process data concepts to operational improvement decisions |
| Self-directed learning | Converts certification and research material into a structured public hub |
| Technical communication | Explains specialist concepts in plain language |
| Frontend delivery | Static HTML/CSS site deployed with GitHub Pages |
| Product thinking | Organises learning modules around practical user questions |
.
|-- index.html # Main learning hub
|-- modules/ # Topic modules
|-- assets/ # Styling and supporting assets
|-- CERTIFICATIONS.md # Certification notes/evidence
`-- .nojekyll # GitHub Pages configuration
python3 -m http.server 8000
# Open http://localhost:8000This is a learning and communication project, not a production process-mining engine. Its value is in explaining the domain clearly and showing how operational data can be reasoned about.