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Generative AI

RAG Systems

Chunking, embeddings and retrieval — grounding an LLM's answers in your own documents.

8 weeks
Madhapur, Hyderabad · Live Online
Intermediate

Overview

A focused deep-dive on retrieval-augmented generation — the technique that lets an LLM answer questions about your own documents accurately, instead of guessing.

Who Should Attend

Developers who already understand basic LLM usage and want to specialize in building reliable, grounded AI applications.

Prerequisites

Basic Python and familiarity with calling LLM APIs.

Fees & Batch Dates Current fees, upcoming batch dates and live vs. self-paced options are shared directly by an advisor — accurate pricing changes too often to publish a number here that might already be stale.
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Curriculum

What you'll learn

Modules

01
Embeddings & Vector SearchTurning documents into something an LLM can retrieve and reason over.
02
Chunking StrategiesSplitting documents in ways that actually improve retrieval quality.
03
Retrieval Pipeline DesignBuilding the full retrieve-then-generate flow.
04
RAG EvaluationMeasuring whether your RAG system is actually working, not just running.

Tools & Technologies

Vector DatabasesLangChainEmbedding ModelsPython

Projects You'll Build

Document Q&A ToolBuild a working assistant that answers questions from a document set.

Career Roles This Prepares You For

GenAI EngineerAI Application Developer
Related resources

Go deeper before you enroll

GenAI Interview QuestionsWhat is a Vector Database?
Certification

What you walk away with

A Skill IT Education certificate of completion, and — most importantly — a completed project for your portfolio. This is an academy certificate, distinct from third-party industry certifications like CEH or PMP, which are issued directly by their certifying bodies.

Before you enroll

Questions people actually ask

How is this different from the full GenAI & LLM Engineering program?
This course goes deeper specifically on RAG. The full program covers RAG plus prompting and agents at a broader level.

Check the next RAG Systems batch

Talk to an advisor for current fees, batch dates and mode of delivery.

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