---
url: "https://xcademia.com/courses/retrieval-augmented-generation-bootcamp"
title: Retrieval Augmented Generation Bootcamp
description: "Learn RAG techniques including chunking, hybrid search, query rewriting, and reranking to build reliable AI knowledge systems.

"
publishedAt: "2026-03-16T11:57:44.408618+00:00"
updatedAt: "2026-03-30T22:50:53.7265+00:00"
type: course
code: "AID-0019"
level: Practitioner
duration_days: "3"
track: "RAG & Vector Databases"
category: "AI, Data & Analytics"
credential_tier: tier1
price_gbp: "1999"
---

# Retrieval Augmented Generation Bootcamp

> Practical training on building Retrieval-Augmented Generation pipelines used in modern AI applications. Learn chunking, hybrid search, query rewriting, and reranking techniques used in production RAG systems.

## Overview

Retrieval-Augmented Generation (RAG) has become a key architecture pattern for developing reliable generative AI applications that use external knowledge sources. This bootcamp introduces engineers to the core techniques required to design and implement effective RAG pipelines.

Participants learn how to structure knowledge sources, create document chunking strategies, and build hybrid search pipelines combining semantic and keyword retrieval. The course also explores query rewriting and reranking techniques that improve the relevance and quality of retrieved information.

Through practical exercises, learners build a functional RAG workflow capable of retrieving information from a knowledge base and generating grounded responses suitable for real-world AI applications.

## Prerequisites

- Basic programming knowledge (Python recommended)
- Familiarity with APIs or backend development
- Basic understanding of generative AI or large language models helpful

## What you will learn

- Understand the architecture of retrieval-augmented generation systems
- Build document ingestion and chunking pipelines
- Implement hybrid search using keyword and semantic retrieval
- Apply query rewriting techniques to improve search quality
- Improve retrieval relevance using reranking strategies
- Design production-ready RAG pipelines for enterprise AI applications

## Skills you will gain

- Retrieval-augmented generation architecture
- Document chunking and knowledge preparation
- Vector embeddings and semantic search
- Hybrid search and query rewriting
- Reranking techniques for improved retrieval
- Building reliable AI knowledge pipelines

## Career progression

- AI Engineer
- Generative AI Developer
- Machine Learning Engineer
- Data Engineer
- Software Engineer (AI Applications)

## Curriculum

1. **Module 1**
2. **Module 2**
3. **Module 3**

## Exam & certification

You will receive an Xcademia certificate of completion based on participation and successful completion of labs and scenario simulations.

## Delivery options

- **Live Online** — Join live instructor-led sessions from anywhere. Interactive, engaging, and flexible.
- **Onsite Training** — We come to you. Training delivered at your workplace for teams of 6 or more.
- **Venue-Based** — Classroom training at a professional venue. Ideal for focused, immersive learning.
- **Blended** — Combine online and in-person learning for maximum flexibility and impact.

## Frequently asked questions

**1. What is Retrieval-Augmented Generation?**

It is an AI architecture that combines document retrieval with generative models to produce responses based on real knowledge sources.



**2. Is this course hands-on?**

Yes. Participants build a working RAG pipeline during practical exercises.



**3. What types of applications use RAG systems?**

Enterprise knowledge assistants, AI search systems, document intelligence platforms, and internal helpdesk AI tools.



**4. Do I need machine learning experience?**

Basic AI knowledge is helpful but not mandatory.



**5. What roles benefit most from this training?**

AI engineers, ML engineers, generative AI developers, and software engineers building AI-powered applications.

## Course at a glance

| Field | Value |
| --- | --- |
| Code | AID-0019 |
| Duration | 3 days |
| Level | Practitioner |
| Track | RAG & Vector Databases |
| Category | AI, Data & Analytics |
| Credential tier | tier1 |
| Price (GBP) | £1999 |

---

## About this content

This Markdown course profile is the citation-grade twin of [Retrieval Augmented Generation Bootcamp](https://xcademia.com/courses/retrieval-augmented-generation-bootcamp). It is published by **Xcademia** (UK Companies House 12322710) and is available for AI search engines and large language models to index, summarise, and cite.

When citing or quoting, please attribute *Xcademia* and link back to the source URL above.

- Source: https://xcademia.com/courses/retrieval-augmented-generation-bootcamp
- Publisher: Xcademia — https://xcademia.com
- Catalogue index: https://xcademia.com/llms-full.txt