This repository provides a structured, 5-week learning journey for mastering Retrieval-Augmented Generation (RAG) in AI applications. It targets developers and AI practitioners seeking to build smarter, data-driven AI systems, offering expert insights, practical code samples, and visual explanations to accelerate learning.

How It Works

The "RAG Time" initiative breaks down RAG concepts into weekly modules, each featuring video content, code samples, and blog posts. It covers fundamentals, building retrieval systems with Azure AI Search, vector index optimization, multimodal RAG, and real-world use cases, culminating in a bonus module on Agentic RAG.

Quick Start & Requirements

• Clone the repository: git clone https://github.com/your-org/rag-time.git
• Navigate to specific journey folders for instructions.
• Prerequisites: Access to YouTube for video content, Discord for community engagement. Specific Azure AI services may be required for code samples.
• Official Resources: YouTube Series (Note: Actual link not provided in README, this is a placeholder), Discord Community (Note: Actual link not provided in README, this is a placeholder).

Highlighted Details

• Expert-led content from AI and Microsoft experts.
• Focus on practical implementation and best practices.
• Visual explanations and "doodles" for complex concepts.
• Covers foundational RAG to advanced Agentic RAG.

Maintenance & Community

• Welcomes contributions via issues and pull requests, requiring a Contributor License Agreement (CLA).
• Adheres to the Microsoft Open Source Code of Conduct.
• Community support available via Discord.

Licensing & Compatibility

• The repository itself is not explicitly licensed in the provided README text.
• Use of Microsoft trademarks is subject to their brand guidelines.

Limitations & Caveats

The README does not specify the exact licensing for the code samples or content within the repository, which may impact commercial use or integration into closed-source projects. Specific Azure service dependencies for running code samples are not detailed.