Build AI That Knows Your Data - RAG (Retrieval-Augmented Generation)

About Course

Master Retrieval-Augmented Generation (RAG) to build AI applications that deliver accurate, context-aware answers using your organization’s documents and knowledge bases. Learn vector databases, embeddings, semantic search, and production-ready RAG architectures for enterprise AI solutions.

This RAG training course teaches you how to build Retrieval-Augmented Generation systems that allow AI to pull from your own documents and data sources for accurate, grounded answers. You will learn vector databases, embedding strategies, chunking techniques, hybrid search, evaluation methods, and how to deploy production-grade RAG systems for customer support, internal knowledge bases, and AI-powered search experiences.

Understand the fundamentals of Retrieval-Augmented Generation (RAG) and its real-world applications.
Build complete RAG pipelines from document ingestion to AI-generated responses.
Create and optimize embeddings for semantic search.
Work with popular vector databases such as Pinecone, Weaviate, Chroma, and pgVector.
Implement effective chunking, indexing, and metadata strategies for different document types.
Build hybrid search systems combining vector and keyword search.
Apply advanced retrieval techniques including query rewriting, re-ranking, and multi-query retrieval.
Evaluate and improve RAG performance using precision, recall, faithfulness, Ragas, and LangSmith.
Reduce hallucinations by grounding AI responses with trusted knowledge sources.
Deploy scalable, secure, and production-ready RAG applications for businesses and organizations.

Course Content

Topic 1: Introduction to RAG (Retrieval-Augmented Generation)
This RAG training course teaches you how to build Retrieval-Augmented Generation systems that allow AI to pull from your own documents and data sources for accurate, grounded answers. You will learn vector databases, embedding strategies, chunking techniques, hybrid search, evaluation methods, and how to deploy production-grade RAG systems for customer support, internal knowledge bases, and AI-powered search experiences.

Module 1: Why RAG?
Module 2: RAG Architecture Fundamentals
Module 3: Embeddings and Vector Search
Topic 1
Assignment

Vector Databases and Data Preparation

Advanced RAG Techniques

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Build AI That Knows Your Data – RAG (Retrieval-Augmented Generation)

About Course

What Will You Learn?

Course Content

Module 1: Why RAG?

Module 2: RAG Architecture Fundamentals

Module 3: Embeddings and Vector Search

Topic 1

Assignment

Vector Databases and Data Preparation

Module 4: Vector Databases

Module 5: Chunking and Data Preparation

Topic 1

Assignment

Advanced RAG Techniques

Module 6: Advanced RAG Techniques

Module 7: Evaluation and Quality

Module 8: Production RAG

Topic 1

Assignment