Retrieval-Augmented Generation

About this course

Build a grounded understanding of retrieval-augmented generation, from document ingestion and search to answer generation and end-to-end evaluation.

This advanced course is part of the Agentic AI & Intelligent Automation school. Work through the curriculum below in a instructor-led / cohort format, with an estimated study time of 25 h.

Course curriculum

• Module 1 — Why Retrieval-Augmented Generation
• Module 2 — Ingestion and Chunking
• Module 3 — Lexical Retrieval and Evaluation
• Module 4 — Dense Retrieval and Vector Indexes
• Module 5 — Hybrid Search, Filters and Reranking
• Module 6 — Generating Grounded Answers
• Module 7 — Evaluating RAG End to End
• Module 8 — Production RAG: Security, Freshness and Operations

Applied learning

• Case Study — Kestrel's Two Knowledge Assistants
• Lab 1 — Retrieval baseline and evaluation harness
• Lab 2 — Dense, hybrid and reranked retrieval
• Lab 3 — A grounded, access-controlled Q&A service
• Capstone — An Evaluated RAG System

Who this course is for

Technology Professional; Engineer / Architect; Enterprise Team

Prerequisites

NE-AI-103

Course details

• Course code: NE-AGI-301
• Level: Advanced
• Estimated duration: 25 h
• Delivery: Instructor-Led / Cohort