Submission information
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
Webform: Knowledge Base Resources
| Approved | Yes |
|---|---|
| Title | 03 – Retrieval-Augmented Generation (RAG) for Large Language Models: A Beginner’s Guide |
| Category | Learning |
| Skill Level | Intermediate |
| Description | 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. |
| Link to Resource | |
| Tags | ai, llm, generative-ai, deep-learning, machine-learning |
| Domain | CCMNet |
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