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657 tutors in 31 topics, built by 75 teachers. Each one follows a lesson plan its teacher wrote.

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RAG Explained for Non Engineers

RAG Explained for Non Engineers

Understand how AI assistants answer from company documents, what can go wrong and what to ask your team.All levelsRAG and search4.7(3)66 lessonsSample
Emeka NwosuFree
Vector Databases for Beginners

Vector Databases for Beginners

Learn what a vector database does, when you need one and how to choose without falling for marketing.BeginnerRAG and search4.3(3)63 lessonsSample
Emeka Nwosu$4
Fine tune, prompt or retrieve?

Fine tune, prompt or retrieve?

Choose between prompting, retrieval and fine tuning for your problem, and know whyAll levelsFine tuning and training4.7(3)59 lessonsSample
Neha VaradanFree
Your First RAG Pipeline, End to End

Your First RAG Pipeline, End to End

Build a small retrieval augmented chatbot over your own documents, step by step, and see where it fails.BeginnerBuilding with LLM APIs4.7(3)59 lessonsSample
Emeka NwosuFree
Embeddings Explained for Builders

Embeddings Explained for Builders

Understand what embeddings capture, what they miss and how to use them for search, grouping and matching.BeginnerRAG and search4.5(2)53 lessonsSample
Emeka Nwosu$4
When Retrieval Is the Wrong Tool

When Retrieval Is the Wrong Tool

Decide when RAG fits a problem and when a database query, tool call, longer prompt or plain search fits better.All levelsRAG and search4.5(2)40 lessonsSample
Fumiko Arai$5
Planning a RAG Pilot for Company Docs

Planning a RAG Pilot for Company Docs

Scope a small, measurable pilot for an assistant over your company documents before anyone builds too much.BeginnerRAG and search4.5(2)37 lessonsSample
Fumiko Arai$4
Parsing PDFs and Messy Documents

Parsing PDFs and Messy Documents

Get clean, well ordered text, tables and page numbers out of PDFs, scans, slides and office files.BeginnerRAG and search4.5(2)36 lessonsSample
Fumiko Arai$5
Long Context Versus Retrieval

Long Context Versus Retrieval

Choose between sending whole documents to a long context model and retrieving passages, using evidence.All levelsRAG and searchNew
Fumiko Arai$6