Course 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.
Hands-On Learning
Participants design and implement a working RAG pipeline including document ingestion, chunking, and hybrid retrieval.
Mentor-Led Sessions
Industry mentors guide learners through production-ready patterns used in enterprise knowledge retrieval systems.
Career-Ready Skills
Develop practical generative AI engineering skills required to build AI assistants, knowledge search tools, and intelligent enterprise support systems.
Learning Outcomes
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
Prerequisites
Basic programming knowledge (Python recommended)
Familiarity with APIs or backend development
Basic understanding of generative AI or large language models helpful
Detailed Syllabus
Organized by professional domains with comprehensive coverage
Topics Covered:
- •What is retrieval-augmented generation
- •Why RAG improves generative AI reliability
- •RAG architecture overview
- •Enterprise AI knowledge use cases
Skills You'll Gain
Master these in-demand skills through hands-on practice
Career Progression
A clear view of the roles this programme supports, what typically comes next, and where learners progress over time
Ways to Learn
Choose the learning format that works best for you and your team
Live Online
Instructor-Led Training
Join live instructor-led sessions from anywhere. Interactive, engaging, and flexible.
- Live instructor interaction (real-time)
- Trainer-led walkthroughs and real examples
- Guided resources and session notes provided
- Structured Q&A and practical discussion
Price per person
Group enrolments and early planning options available.
All prices are exclusive of VAT where applicable. Group enrolments and custom packages available on request.
Prefer a Faster, Personalised Route into IT?
Not everyone learns best in a group. If you want focused guidance, faster clarity, and confidence you can use on the job, our 1-to-1 Fast-Track Training gives you private, mentor-led support tailored to your experience and goals.
"Many learners choose 1-to-1 when they want understanding, not memorisation."
Exam & Certification Information
Everything you need to know about the certification exams
Important Information
You will receive an Xcademia certificate of completion based on participation and successful completion of labs and scenario simulations.
Credential
Certificate of Completion
On successful completion of Retrieval Augmented Generation Bootcamp, learners receive an Xcademia Certificate of Completion. This standalone certificate is issued directly by Xcademia and is aligned with globally recognised frameworks and best practices.
Frequently Asked Questions
Everything you need to know about this course
It is an AI architecture that combines document retrieval with generative models to produce responses based on real knowledge sources.
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