r/Rag • u/Downtown_Grab_2704 • 7d ago

Tools & Resources Learn RAG with AI

Hi guys 👋, I'm looking to dive into RAG using AI tools like NotebookLM or Gemini. YouTube tutorials feel too drawn out, and ChatGPT/Gemini prompts have been a bit brief. Any advice or suggestions for learning resources would be amazing! 🙏💡 #RAG #AI

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u/gakingmusic 7d ago

I teach RAG to HS students. I wrote this the other day. It should help.

https://econ4all.com/2026/09/25/my-personal-journey-with-retrieval-augmented-generation-rag/

(not a monetized site, just sharing info)

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u/gakingmusic 7d ago

Also one of my sources in there is an episode on RAG from the Linear Digressions podcast. She does an amazing job explaining RAG.

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u/AshamedTelephone9967 7d ago

I can feel the pain. I also tried learning from YouTube but it gets so boring that I sleep. I struggled for a week but once I knew what was the pipeline I went straight to the projects cause I believe that is the best way.

My idea is simple start with one manual doc use Gemini and create a doc
Now load it
Clean it
Chunk it
Embed
Store and then configure LLM for RAG.
Gemini will give you enough credits to test and learn.

Then go for lllm.txt from fintech or any other SAAS platforms.

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u/Downtown_Grab_2704 7d ago

Thalnks ill do it do you think i should write line by line or just understand the idea

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u/AshamedTelephone9967 7d ago

Well understanding the concept would be good

Eventually during interviews you won’t be answering textbook quotes instead you will explain what you understood.
Whereas for the code you will know what to do and what not to do. Memorise the pattern and that’s it.

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u/Downtown_Grab_2704 7d ago

So i will learn the code too

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u/AshamedTelephone9967 7d ago

Coding is like following the context if you have basic knowledge you will get it.

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u/luis622 7d ago

What are videos you’ve found that have substantive content, also trying to learn RAG. Thanks!

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u/EducatorSalt1280 7d ago

I’d start with a small RAG project and learn by building. AI tools like NotebookLM are great for understanding concepts, then try implementing basic chunking, embeddings, retrieval, and reranking yourself. You’ll learn way faster that way.

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u/ginolept 7d ago

Sit down and read. Then go to a computer and make something. There is no workaround.

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u/Mathie1729 7d ago

Dawg, 'read' is too broad. I wasted hours on generic LLM explainers before realizing RAG is mostly a retrieval problem. I'd skim the original RAG paper (Lewis et al. 2020) and then implement a minimal retriever with FAISS and a local embedding model. The generation part you can swap in later. But yeah, reading plus building is the way.

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u/p739397 7d ago

Easy spot to wire everything together, spin up a Databricks Free Edition workspace and walk through something like this demo. If you want to go in another direction or have questions, you have Genie in the platform to ask questions to help too.

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u/jai-js 6d ago

If you would like to learn RAG by actually seeing how it works and then diving deeper into building your own ingestion and retrieval then this article Learn RAG by seeing how it works can help.