// the find
HoussemDellai/ai-course
Learning Azure AI with APIM, Semantic Kernel and LangChain.
A personal collection of numbered notebooks and scripts walking through Azure OpenAI, RAG, Semantic Kernel, LangChain, and APIM-fronted LLM setups. It's built for developers learning the Azure AI stack step by step, not for pulling into a real project.
The numbered folder structure (010, 020, 030, 100...) gives a genuine progression from raw SDK calls to RAG to agent patterns, which is more useful as a learning path than most scattered tutorial repos. It covers both Python and C# for the same concepts side by side, and the RAG folder ships with a real corpus of scraped Azure AI docs plus pre-chunked JSON, so you can run the retrieval examples without hunting down your own dataset.
Compiled build output (bin/obj, .dll, .pdb, .exe) is checked into git for at least one of the C# projects, which bloats the repo and will conflict the moment someone builds locally. A .env file is committed in 100_rag_intro, which is a real risk if it ever held live keys and sets a bad example regardless. There's no top-level README tying the folders together or explaining prerequisites, and the Infracost/Terraform manifest files suggest infra tooling that isn't documented anywhere in the tree, so you're left guessing how the pieces are meant to connect.