03 – Retrieval-Augmented Generation (RAG) for Large Language Models: A Beginner’s Guide

Submission Number: 352
Submission ID: 5280
Submission UUID: db457a82-c797-4106-9de6-f5ef3b725865
Submission URI: /form/resource

Created: Fri, 05/02/2025 - 15:48
Completed: Fri, 05/02/2025 - 15:48
Changed: Thu, 01/15/2026 - 18:21

Remote IP address: 139.182.9.242
Submitted by: Dr. Nabeel Alzahrani
Language: English

Is draft: No
Yes
03 – Retrieval-Augmented Generation (RAG) for Large Language Models: A Beginner’s Guide
Learning
Intermediate

This hands-on guide introduces Retrieval-Augmented Generation (RAG), a practical technique for enhancing Large Language Models (LLMs) by integrating external knowledge sources. The resource covers core concepts in AI, LLMs, and RAG, and provides step-by-step examples and visual explanations to help learners build more accurate and context-aware AI systems.

The guide leverages open-source tools such as FAISS, Milvus, and LangChain, and is designed for learners with basic programming or AI familiarity who want to move beyond prompt-only approaches toward production-ready LLM applications.

ai, llm, generative-ai, deep-learning, machine-learning
CCMNet
{Empty}