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Here's a 9-hour crash course curriculum for learning to build LLM applications. All resources are free. 𝗣𝗔𝗥𝗧 𝟭 - 𝗔 𝗚𝗘𝗡𝗧𝗟𝗘 𝗜𝗡𝗧𝗥𝗢 𝗧𝗢 𝗟𝗟𝗠𝗦 (1h 30m) Intro & overview of language models, next-word prediction, embeddings, cosine similarity, semantic search Resources: 📺 30m: Simple intro (MBerm) https://lnkd.in/eCfYMdUK 📖 40m: llms nohype (MRied) https://lnkd.in/eY6Pd9bJ 📺 10m: Next wrd prd (LBouc) https://lnkd.in/ergd9FT2 📺 10m: Sem search (LSerr) https://lnkd.in/eRnnhmuj --- 𝗣𝗔𝗥𝗧 𝟮 - 𝗧𝗥𝗔𝗡𝗦𝗙𝗢𝗥𝗠𝗘𝗥 𝗔𝗥𝗖𝗛𝗜𝗧𝗘𝗖𝗧𝗨𝗥𝗘 (1h 30m) Encoder-decoder architecture, masking, attention, transformers, GPTs Resources: 📺 30m: Visual llm (3Blu1Br) https://lnkd.in/egJPUhuX 📺 20m: Enc-Dec (JStarm) https://lnkd.in/eJNfAKZ8 📺 10m: Attention (LSerr) https://lnkd.in/eEFrS5uV 📺 15m: Transformers (LSerr) https://lnkd.in/eVcnZxad 📺 15m: GPTs (DataBrks) https://lnkd.in/es9bKS-z --- 𝗣𝗔𝗥𝗧 𝟯 - 𝗣𝗥𝗢𝗠𝗣𝗧 𝗘𝗡𝗚𝗜𝗡𝗘𝗘𝗥𝗜𝗡𝗚 (2h 0m) Zero/one/few-shot, chain-of-thought, self-consistency, generated knowledge, prompt chaining, ReAct Resources: 📺 60m: PE Overview (ESarav) https://lnkd.in/eFF2Yc7C 📖 90m: Prompt Eng (DAIR) https://lnkd.in/eaqPT63j 📖 30m: PE Guide (Brex) https://lnkd.in/etPjrkvw ⚒️ 0m: LangChain Hub https://lnkd.in/e_pt2cVx --- 𝗣𝗔𝗥𝗧 𝟰 - 𝗖𝗛𝗔𝗜𝗡𝗜𝗡𝗚, 𝗥𝗔𝗚, 𝗩𝗘𝗖𝗧𝗢𝗥 𝗗𝗕𝗦, 𝗔𝗚𝗘𝗡𝗧𝗦 (2h 30m) Langchain, RAG, vector databases, LlamaIndex, Open AI functions Resources: 📺 30m: LngCh ckbk1 (GKam) https://lnkd.in/eRTUH3rZ 📺 30m: LngCh ckbk2 (GKam) https://lnkd.in/ehXZNsRg ⚒️ 0m: LngCh tutorials (GKam) https://lnkd.in/eSyFQwhm 📖 30m: Adv RAG (HugFace) https://lnkd.in/eSqe-UCD 📺 5m: Vector dbs (Fireshp) https://lnkd.in/et3Zz8-k 📺 10m: LC+Pinecone (GKam) https://lnkd.in/e5E6Fv46 📺 20m: LlamaIdx (engprmpt) https://lnkd.in/eYRFG-wg 📺 30m: OpenAI fn/agnt (auto) https://lnkd.in/esZa7c3s --- 𝗣𝗔𝗥𝗧 𝟱 - 𝗙𝗜𝗡𝗘𝗧𝗨𝗡𝗜𝗡𝗚 (1h 30m) Feature-based finetuning, LoRA, RLHF Resources: 📖 15m: Finetuning (SRasc) https://lnkd.in/eTdFHQS5 📖 15m: FT v PrmpEng (NBant) https://lnkd.in/ekeHKWPe 📺 30m: RLHF intro (HugFac) https://lnkd.in/etsH53ri 📖 15m: RLHF guid (Lblerr) https://lnkd.in/e57dsuEp 📖 15m: LoRA (HugFac) https://lnkd.in/ervJK9C7 --- Cheers 🍻 #ai #machinelearning #aiengineering #genai