Advanced RAG for OpenSearch
- 7 Sections
- 21 Lessons
- 5 Quizzes
- 2h Duration
Introduction
Chapter 1: Simple RAG and Hybrid Search
Chapter 2: Context Prompting for RAG
Chapter 3: Hybrid RAG
- Introduction
- Lesson 1: The Two Kinds of Retrieval: Keyword vs Vector Search
- Lesson 2: The Vocabulary Gap: Where Keyword Search Falls Down
- Lesson 3: Hybrid Search with Reciprocal Rank Fusion (RRF)
- Lesson 4: Evaluating Retrieval Quality with a Golden Set
- Lesson 5: From Retrieved Evidence to Grounded Answers
- Conclusion
- Chapter 3: Exam
Chapter 4: RAG with Memory
Hands-On Lab
Course Conclusion
Basic Retrieval Augmented Generation is easy to demo, but not all RAG deployments are created equal. Deploying a robust RAG solution requires more than pointing your language model at a lot of documents, asking it a question, and expecting the answer to be exactly what you need.
This course is about building a robust a RAG deployment. Over four chapters, you will learn how to build it one layer at a time: starting with a basic RAG system, then adding more predictable answers, intentional context decisions, and memory integration.
This course also includes a free self-paced hands-on labs workshop, so you can build the same system you see in the lessons. You do not need to have built a RAG system before. We start simple, add one layer at a time, and explain what each layer is for before we build it. By the end, you will understand the key building blocks, why they matter, and how to apply them through hands-on experience building a robust RAG system for your business.
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