Subtitled "Ultimate Guide To Mastering RAG", this is a course for beginners to learn how to build AI apps utilizing Microsoft products and RAG.

It is the newest Microsoft's offering in the stream of AI
tutorials the likes of "AI Agents for Beginners" and "Generative AI for Beginners", and while MCP is currently occupying the headlines of the AI ecosystem, RAG is still going strong as it's the fundamental building block of GenAI applications.

At IProgrammer we've covered RAG quite a few times with articles like "Azure RAGChat Deep Dive", "The Advanced + Agentic RAG Cookbooks", "Getting Going With RAG"
, "RAG from Scratch" (links at the end of this one), so I guess that we vouch for it.

This new course, "RAG Time: Ultimate Guide to Mastering RAG" is made by Pamela Fox, Cloud Advocate in Python at Microsoft, who has a solid background in making educational material for Microsoft products.

It consists of six overlapping chapters which while live-streamed, they've ended up as a complete youtube playlist, accompanied by its Github repo that contains the text material and the code,
to be cloned in order to follow along. The chapters are:

RAG and Knowledge Retrieval Fundamentals
Understand the strategic importance of RAG and knowledge retrieval

Build the Ultimate Retrieval System
Explore how Azure AI Search powers retrieval system

Optimize Your Vector Index at Scale
Learn real-world optimization techniques for scaling vector indexes

RAG for All Your Data
Discover how multimodal data can be indexed and retrieved

Hero Use-Cases for RAG
Get inspired by hero use cases of RAG in action

Agentic RAG
Learn about Agentic RAG an build your first Agentic RAG solution

The series cover various aspects of a RAG system:

• RAG fundamentals
• Building the ultimate retrieval system
• Optimize your vector index at scale
• RAG for all your data
• Hero use cases

is totally addressed to beginners in GenAI, but Python knowledge is required.

What you'll need to follow along:

1. An Azure account with proper permissions to access the following services:

• An Azure OpenAI service with an active deployment of a chat model and an embedding model.
  
  
• An Azure AI Search service with an index that contains vectorized text data. 

2. Install Python 3.8

And finally, fork the repository and clone it to your local machine:

git clone https://github.com/your-org/rag-time.git

Let the journey begin!

More Information

RAG Time

Related Articles

Azure RAGChat Deep Dive

The Advanced + Agentic RAG Cookbooks

Getting Going With RAG

RAG from Scratch 

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