Retrieval-Augmented Generation (RAG) Training in Doha

Retrieval-Augmented Generation (RAG) Training in Doha, Qatar

Participants learn how to design RAG pipelines that reduce hallucinations, improve answer quality, and leverage private data securely using modern AI stacks.

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Retrieval-Augmented Generation (RAG) Training is a professional training program delivered by ProgNXT in Doha, Qatar. ProgNXT, a globally recognized corporate training provider in 55+ countries, offers this Retrieval-Augmented Generation (RAG) Training course with hands-on, instructor-led sessions. The Retrieval-Augmented Generation (RAG) Training is a hands-on program focused on building accurate, scalable, and enterprise-ready GenAI...

Expert Panel

Designed by the ProgNXT AI & Data Science Expert Panel, specializing in Generative AI, Machine Learning, and ChatGPT applications

ProgNXT AI & Data Science Expert Panel

Course Code: PEE50
14 Hrs
Last Updated: April 2026

Course Rating5/5

The Retrieval-Augmented Generation (RAG) Training is a hands-on program focused on building accurate, scalable, and enterprise-ready GenAI applications by combining Large Language Models (LLMs) with external knowledge sources.
Participants learn how to design RAG pipelines that reduce hallucinations, improve answer quality, and leverage private data securely using modern AI stacks.

Welcome to the official Retrieval-Augmented Generation (RAG) Training certification program in Doha, Qatar. This comprehensive training is designed to elevate your professional skills and provide you with practical, industry-relevant knowledge locally. As a globally recognized corporate training provider operating in 55+ countries, ProgNXT ensures that our curriculum meets the highest standards of excellence.

Whether you are looking to upskill your team or advance your personal career, our expert-led sessions will guide you through the core concepts of this domain. Upon successful completion of the 14 Hrs program, participants will receive a globally accepted certification, demonstrating their proficiency and readiness to tackle complex challenges in the field.

Basic Python programming knowledge
Introductory understanding of Generative AI or LLMs
Familiarity with APIs and JSON
Prior experience with ML or data engineering is helpful (not mandatory)

By the end of this training, participants will be able to:

Understand RAG concepts and architectures
Build end-to-end RAG pipelines
Implement document ingestion and chunking strategies
Use embeddings and vector databases effectively
Improve response accuracy and reduce hallucinations
Deploy and evaluate production-ready RAG systems

RAG architecture design
Prompt engineering for RAG
Embeddings and vector search
Document processing and chunking
Context retrieval optimization
RAG evaluation and monitoring
Secure and scalable GenAI deployment

RAG architecture understanding
Document ingestion and chunking
Embedding and retrieval accuracy
Prompt design quality
End-to-end RAG pipeline implementation

Participants who attend all sessions and successfully complete the course assessments will receive a ProgNXT Certificate of Completion.

Introduction to RAG & Enterprise GenAI

Why RAG is needed for enterprise AI
Limitations of standalone LLMs
RAG vs fine-tuning

RAG Architecture & Workflow

High-level RAG system design
Data ingestion → retrieval → generation flow
Online vs offline RAG pipelines
Stateless vs stateful RAG systems

Document Ingestion & Data Preparation

Handling PDFs, Word, HTML, and text files
Cleaning and preprocessing text
Metadata extraction and enrichment
Versioning and data updates

Chunking Strategies & Indexing

Fixed-size vs semantic chunking
Overlapping chunks and context windows
Chunk size impact on accuracy and cost
Indexing best practices

Embeddings & Vector Databases

What are embeddings and how they work
Creating embeddings at scale
Vector indexing and similarity search
Performance and cost considerations

Retrieval Strategies

Similarity search vs hybrid search
Keyword + vector retrieval
Filtering using metadata
Ranking and re-ranking techniques

Prompt Engineering for RAG

Prompt templates for grounded responses
Injecting retrieved context safely
Reducing hallucinations
System prompts vs user prompts

RAG with Frameworks

Building RAG pipelines using LangChain
Using LlamaIndex for document indexing
Comparing frameworks and trade-offs
Modular and extensible pipeline design

Advanced RAG Techniques

Multi-document and multi-hop RAG
Conversational RAG with memory
Agentic RAG workflows
Query rewriting and expansion

Evaluation & Optimization

Measuring RAG quality and relevance
Latency, cost, and accuracy trade-offs
Human-in-the-loop evaluation
Continuous improvement strategies

Security, Governance & Responsible AI

Protecting sensitive enterprise data
Access control and authorization
Data leakage prevention
Compliance and audit considerations

Deployment & Scaling RAG Systems

API-based RAG services
Caching and performance optimization
Scaling retrieval and inference
Monitoring and observability

Hands-on Exercises

Summary and Conclusion

Participants will receive course materials, slides, reference materials, exercises and access to resources for further learning.

Participants will be evaluated based on: Daily quizzes, mock questions and query resolution. Group Discussion and Case Study Discussion. Assessment will be through hands-on labs, quizzes, and hands-on exercises.

ProgNXT Certificate of Completion will be awarded to participants who complete the course and pass the evaluations.

Retrieval-Augmented Generation (RAG) Training Events in doha

Online Events

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More Upcoming Session Dates

November 2026

📍 Doha, Qatar

3rd Nov 2026→4th Nov 2026

🌐 Online Instructor-Led

8th Nov 2026→9th Nov 2026

📍 Doha, Qatar

23rd Nov 2026→24th Nov 2026

🌐 Online Instructor-Led

25th Nov 2026→26th Nov 2026

December 2026

🌐 Online Instructor-Led

5th Dec 2026→6th Dec 2026

📍 Doha, Qatar

12th Dec 2026→13th Dec 2026

🌐 Online Instructor-Led

19th Dec 2026→20th Dec 2026

📍 Doha, Qatar

28th Dec 2026→29th Dec 2026

Events for other courses in Doha, Qatar

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Retrieval-Augmented Generation (RAG) Training in Doha