Learning roadmap
Choose a goal, then follow each stage as an ordered, explained outline.
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Build a durable mental model, then transfer it into a working application.
Stage purpose: Establish the vocabulary and first working mental model.
Required background: Complete the linked prerequisites below or bring equivalent experience.
Expected outcome: Explain the core idea and use it in a small example.
Estimated time: 30 minutes
Prerequisites: No prerequisite topics
Evidence: Practise the outcome in code and record what you learned.
Current status: Not started
Recommended next: Knowledge Graph Primitives & Graph RAG with Neo4j — Carry the Knowledge Graphs & Graph RAG mental model into the next step with a concrete transfer exercise.
Stage purpose: Connect the concepts into a repeatable problem-solving model.
Required background: Complete the linked prerequisites below or bring equivalent experience.
Expected outcome: Apply the model to a representative exercise without copying a recipe.
Estimated time: 30 minutes
Prerequisites: Knowledge Graphs & Graph RAG
Evidence: Practise the outcome in code and record what you learned.
Current status: Not started
Recommended next: Text → Graph — LLM Entity Extraction — Carry the Knowledge Graph Primitives & Graph RAG with Neo4j mental model into the next step with a concrete transfer exercise.
Stage purpose: Transfer the concepts into a realistic implementation task.
Required background: Complete the linked prerequisites below or bring equivalent experience.
Expected outcome: Produce a small artifact that proves the decision works.
Estimated time: 30 minutes
Prerequisites: Knowledge Graph Primitives & Graph RAG with Neo4j
Evidence: Practise the outcome in code and record what you learned.
Current status: Not started
Recommended next: Complete this path by applying these outcomes in your own project.
Prioritise high-frequency material, retrieve it quickly, and practise explaining it clearly.
Stage purpose: Secure the concepts that recur in most interviews.
Required background: Complete the linked prerequisites below or bring equivalent experience.
Expected outcome: Give a concise, accurate explanation with one concrete example.
Estimated time: 12 minutes
Prerequisites: No prerequisite topics
Evidence: Answer aloud, give a concrete example, and identify the relevant trade-off.
Current status: Weak
Recommended next: Knowledge Graph Primitives & Graph RAG with Neo4j — Use Knowledge Graphs & Graph RAG as the setup for the next interview trade-off and explain the connection aloud.
Stage purpose: Rehearse implementation choices that invite common follow-up questions.
Required background: Complete the linked prerequisites below or bring equivalent experience.
Expected outcome: Walk through a realistic API decision and defend the trade-offs.
Estimated time: 12 minutes
Prerequisites: Knowledge Graphs & Graph RAG
Evidence: Answer aloud, give a concrete example, and identify the relevant trade-off.
Current status: Weak
Recommended next: Text → Graph — LLM Entity Extraction — Use Knowledge Graph Primitives & Graph RAG with Neo4j as the setup for the next interview trade-off and explain the connection aloud.
Stage purpose: Prepare the details that distinguish a deeper answer.
Required background: Complete the linked prerequisites below or bring equivalent experience.
Expected outcome: Connect the concept to reliability, complexity, or production behavior.
Estimated time: 12 minutes
Prerequisites: Knowledge Graph Primitives & Graph RAG with Neo4j
Evidence: Answer aloud, give a concrete example, and identify the relevant trade-off.
Current status: Weak
Recommended next: Complete this path by applying these outcomes in your own project.