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Claude + RAG (Retrieval-Augmented Generation)

Build Knowledge-Grounded AI Systems with Claude and RAG

Learn how to build Retrieval-Augmented Generation (RAG) systems using Claude to create AI applications that answer questions accurately using your own data. This Claude + RAG training and certification course teaches developers how to design, build, and deploy production-grade RAG pipelines.

✔ Instructor-Led RAG Training

✔ Hands-On RAG Pipeline Labs

✔ Real-World Knowledge Base Projects

✔ Claude + RAG Certification Included

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    Course Overview

    Course Image

    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

    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

    Expert-Led RAG Training

    Learn from AI engineers with real-world experience building production RAG systems with Claude.

    Hands-On RAG Pipeline Building

    Hands-On RAG Pipeline Building

    Build real RAG pipelines, from document ingestion to retrieval and generation, through guided labs.

    Practical Enterprise Use Cases

    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

    • arrow Instructor-led interactive RAG sessions
    • arrow Real-world RAG case studies
    • arrow Hands-on RAG pipeline development labs
    • arrow Industry-recognized certification
    • arrow Access to RAG development resources
    • arrow 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

    RAG is one of the most in-demand skills in applied AI, as enterprises need Claude-powered systems that are grounded in accurate, trusted data.

    • RAG Engineer • AI Search Engineer • Generative AI Developer • Knowledge Engineer • AI Solutions Architect

    Engineers skilled in building RAG systems with Claude are among the highest in-demand roles in the applied AI job market.

    Business Impact

    FAQ?

    RAG is a technique that combines Claude with a retrieval system to generate answers grounded in your own data.

    Basic programming and data handling knowledge is helpful but not mandatory for this Claude + RAG course.

    Participants will work with the Claude API, vector databases, and embedding models to build RAG pipelines.

    Yes, participants will receive an industry-recognized Claude + RAG certification.

    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

    Claude for Cloud Developers

    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

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