Jupyter Notebooks
Download notebook files to run in your local environment or Google Colab. Login required for download.
📚 Concept Notebooks (9)
Notebooks covering core concepts and basic exercises for each topic.
| Week | Topic | Key Content | Download |
|---|---|---|---|
| 01 | Ontology Intro | Knowledge representation, Upper/Domain ontology | |
| 02 | RDF & RDFS | SPO triples, rdflib, SPARQL | |
| 03 | OWL & Reasoning | Class hierarchy, Restrictions, Reasoner | |
| 04 | Knowledge Extraction | NER, Relation Extraction, Entity Resolution | |
| 05 | Neo4j | LPG modeling, Cypher queries | |
| 06 | GraphRAG | Hybrid retrieval, Sub-graph extraction | |
| 07 | Ontology Agents | Rule-based planning, Multi-agent | |
| 08 | Domain Projects | Medical/Legal/Finance Case Study | |
| 09 | Service Architecture | Visualization, API, Performance |
🎬 Project Notebooks: Movie Recommendation Knowledge Graph (9)
Build a complete Movie Recommendation Knowledge Graph over 9 weeks. Apply concepts learned each week to a real project.
| Week | Project Milestone | Content | Download |
|---|---|---|---|
| 01 | Movie Domain Design | Define ontology with owlready2 | |
| 02 | RDF Conversion | Create triples for 10 movies with rdflib | |
| 03 | Reasoning Rules | VeteranDirector, Blockbuster inference | |
| 04 | Auto Extraction | Collect 100 movies from Wikipedia | |
| 05 | Neo4j Storage | Build graph DB and recommendation queries | |
| 06 | GraphRAG | Natural language movie recommendation chatbot | |
| 07 | Auto Update | Multi-agent for new movie detection | |
| 08 | Domain Expansion | Movie → Medical ontology transformation | |
| 09 | Deployment | FastAPI + Docker deployment |
Recommended Learning Path: Study theory with Concept Notebooks first, then practice with Project Notebooks.
Premium Notebooks
Practice (Exercises)
TODO-style exercises for each topic. Fill in the code yourself to learn.
Solutions
Complete solutions for practice notebooks. Reference when stuck.
Interviews
- Theory 50 - 50 ontology/knowledge graph theory questions
- Coding 30 - 30 coding problems
- Case Study 20 - 20 business cases
- Mock Interviews 30 - 30 mock interview scenarios
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