Lesson 1
Why grounding matters
A model should not invent business facts that already exist in trusted systems or documents.
All learning tracks
Applied AI EngineeringIntermediate 90–120 min
RAG, Grounding & Hallucination Control
Learn how retrieval-augmented generation changes the quality problem and how to validate source-grounded answers.
RAGEmbeddingsGrounding
Learning outcomes
Explain a RAG pipeline
Test retrieval quality
Design grounded-answer checks
Guided lessons
Learn the engineering thinking
Lesson 2
Retrieval pipeline basics
Chunking, embeddings, retrieval, ranking and context assembly all influence the final answer.
Lesson 3
Retrieval quality vs answer quality
An answer can be wrong because the model reasoned poorly or because the right evidence was never retrieved.
Lesson 4
Source attribution
Design responses so evidence can be traced and users can inspect the basis of important claims.
Lesson 5
RAG test strategy
Test missing sources, conflicting sources, irrelevant retrieval, stale content and ambiguous queries.
Hands-on practice
Do something with what you learned
Do not just tick these mentally. Write the query, create the test matrix, refactor the code, or document the decision. Practical evidence is the point.