Course Overview
Retrieval-Augmented Generation (RAG) combines Claude’s language capabilities with your own data to produce accurate, grounded, and up-to-date responses. This course teaches you how to design and build RAG systems from scratch.
In this course, you will learn how to chunk and embed documents, build vector databases, and design retrieval pipelines that feed relevant context into Claude.
Through hands-on labs, participants will build complete RAG applications, including document ingestion, semantic search, and Claude-powered answer generation.
By the end of this course, learners will be able to design and deploy production-ready RAG systems that reduce hallucination and improve answer accuracy.
Course Distinction
What makes our course unique?
Unlock the Power of Knowledge-Grounded AI
Master Retrieval-Augmented Generation to build AI systems that answer questions using your own trusted data.
Expert-Led RAG Training
Learn from AI engineers with real-world experience building production RAG systems with Claude.
Hands-On RAG Pipeline Building
Build real RAG pipelines, from document ingestion to retrieval and generation, through guided labs.
Practical Enterprise Use Cases
Learn how RAG powers enterprise search, customer support, research assistants, and internal knowledge bases.
Course Content
- What is RAG and why it matters
- RAG vs fine-tuning vs long context
- RAG architecture overview
- Use cases for RAG with Claude
- Document chunking strategies
- Generating embeddings for text and documents
- Choosing an embedding model
- Handling structured and unstructured data
- Introduction to vector databases
- Semantic search and similarity search
- Hybrid search techniques
- Optimizing retrieval accuracy
- Connecting retrieval systems to the Claude API
- Prompt design for RAG applications
- Citation and source attribution
- Handling multi-document context
- Re-ranking retrieved results
- Multi-step and agentic RAG
- Query rewriting and expansion
- Evaluating RAG system accuracy
- Scaling RAG pipelines
- Monitoring and reducing hallucination
- Security and data privacy in RAG
- Cost optimization for RAG applications
Capstone Project
Design, build, and deploy a complete RAG application using Claude that answers questions accurately from a real document or knowledge base.
Key Features
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Instructor-led interactive RAG sessions -
Real-world RAG case studies -
Hands-on RAG pipeline development labs -
Industry-recognized certification -
Access to RAG development resources -
Capstone RAG project
Skills Covered
- Retrieval-Augmented Generation
- Vector Databases & Embeddings
- Semantic Search
- RAG Pipeline Design
- Prompt Engineering for RAG
- Claude API Integration
- Hallucination Reduction Techniques
- RAG System Evaluation
Advancements
Business Impact
FAQ?
Customized Corporate RAG Training
We also provide corporate training programs tailored for teams building RAG-powered knowledge systems with Claude.
✔ Custom curriculum for your data sources
✔ Team onboarding to RAG development
✔ Flexible training delivery
✔ Enterprise consulting support
Who Should Attend
AI/ML Engineers
Software Developers
Data Engineers
Search & Knowledge Engineers
Solutions Architects
Data Scientists
Build Knowledge-Grounded AI with Claude + RAG
Become a specialist in building accurate, retrieval-augmented AI systems using Claude.
✔ Learn from industry experts
✔ Work on real RAG projects
✔ Earn certification
Testimonial
What people are say?

















