Complete RAG Bootcamp: Build, Optimize, and Deploy AI Apps

About this course

“This course contains the use of artificial intelligence”Unlock the full potential of Retrieval-Augmented Generation (RAG) — the framework behind today’s most accurate, data-aware AI systems.

This comprehensive bootcamp takes you from the fundamentals of RAG architecture to enterprise-level deployment, combining theory, hands-on projects, and real-world use cases.

You’ll learn how to build powerful AI applications that go beyond simple chatbots — integrating vector databases, document retrievers, and large language models (LLMs) to deliver factual, explainable, and context-grounded responses. What You’ll Learn

The core concepts of Retrieval-Augmented Generation (RAG) and why it’s transforming AI.Building RAG pipelines from scratch using LangChain, LlamaIndex, and FAISS.Implementing hybrid search (keyword + vector) for smarter retrieval.

Creating multi-modal RAG systems that process text, images, and PDFs.

Building Agentic RAG workflows where intelligent agents plan, retrieve, and reason autonomously.

Optimizing RAG performance with prompt tuning, top-k selection, and similarity thresholds.

Adding security, compliance, and role-based governance to enterprise RAG pipelines.

Integrating RAG into real-world workflows like Slack, Power BI, and Notion.

Deploying complete front-end and back-end RAG systems using Streamlit and FastAPI.Designing evaluation metrics (semantic similarity, precision,

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