Awesome LLM Courses [](https://awesome.re)

A curated list of awesome online courses about Large Langage Models (LLMs).

We try to monitor free available online courses about LLMs. Please open a PR or an issue if you want to suggest a list update 🤓

• 🤗 Hugging Face
  • NLP Course
  • Community Computer Vision Course (cf. Unit 4 about Multimodal & Vision Language Models 🌐📚👁️)
• CodeSignal – Selected LLM/NLP course paths with Cosmo, the AI tutor 🐶✨
  • Understanding LLMs and Basic Prompting Techniques — 5 lessons — 15 practices — Intermediate
  • Introduction to Natural Language Processing – 4 courses – 78 practices – Intermediate
  • Text Classification with Natural Language Processing – 4 courses – 110 practices – Advanced
• 🗣️ Large Language Model Course – Maxime Labonne
  • 🧩 LLM Fundamentals
  • 🧑‍🔬 The LLM Scientist
  • 👷 The LLM Engineer
• Udacity
  • Introduction to Large Language Models with Google Cloud – 45 Minutes – Beginner
  • Introduction to Gen AI Studio with Google Cloud – 20 Hours — Beginner
  • Introduction to Gemini for Google Workspace – 1 Day – Beginner
  • Introduction to Image Generation with Google Cloud – 1 Day – Intermediate
  • Generative AI Fundamentals with Google Cloud – 4 Days – Beginner
  • Gemini in Gmail – 1 Day – Beginner
  • Gemini in Google Docs – 1 Day – Beginner
  • Gemini in Google Meet – 1 Day – Beginner
  • Gemini in Google Sheets – 1 Day – Beginner
  • Gemini in Google Slides – 1 Day – Beginner
  • Gemini API by Google – 3 Days – Intermediate
  • LLMOps: Building Real-World Applications With Large Language Models – 11 Hours – Intermediate
  • Transformer Models and BERT Model with Google Cloud – 1 Day – Beginner
• DeepLearning.AI – Short Courses
  • Multimodal RAG: Chat with Videos – Intel – 1 Hour – Intermediate
  • AI Python for Beginners – 4-5 Hours – Beginner
  • Large Multimodal Model Prompting with Gemini – Google Cloud – 2 Hours – Beginner
  • Building AI Applications with Haystack – 1 Hour – Intermediate
  • Improving Accuracy of LLM Applications – Lamini and Meta – 1x Hour – Intermediate
  • Embedding Models: From Architecture to Implementation – Vectara – 1 Hour – Beginner
  • Federated Learning – Flower – 2 Hours – Beginner to Intermediate
  • Pretraining LLMs – Upstage – 1 Hour – Beginner
  • Prompt Compression and Query Optimization – MongoDB – 1 Hour – Intermediate
  • Carbon Aware Computing for GenAI Developers – Google Cloud – 1 Hour – Beginner
  • Function-Calling and Data Extraction with LLMs – Nexusflow – 1 Hour – Intermediate
  • Building Your Own Database Agent – Microsoft – 1 Hour – Beginner
  • AI Agents in LangGraph – LangChain, Tavily – 1 Hour – Intermediate
  • AI Agentic Design Patterns with AutoGen – Microsoft, Penn State University – 1 Hour – Beginner
  • Introduction to On-Device AI – Qualcomm – 1 Hour – Beginner
  • Multi AI Agent Systems with crewAI – crewAI – 1 Hour – Beginner
  • Building Multimodal Search and RAG – Weaviate – 1 Hour – Intermediate
  • Building Agentic RAG with LlamaIndex – LlamaIndex – 1 Hour – Beginner
  • Quantization in Depth – Hugging Face – 1 Hour – Intermediate
  • Prompt Engineering for Vision Models – Comet – 1 Hour – Beginner
  • Getting Started With Mistral – Mistral AI – 1 Hour – Beginner
  • Quantization Fundamentals with Hugging Face – Hugging Face – 1 Hour – Beginner
  • Preprocessing Unstructured Data for LLM Applications – Unstructured – 1 Hour – Beginner
  • Open Source Models with Hugging Face – Hugging Face – 1 Hour – Beginner
  • Prompt Engineering with Llama 2 & 3 – Meta – 1 Hour – Beginner
  • Red Teaming LLM Applications – Giskard – 1 hour – Beginner
  • JavaScript RAG Web Apps with LlamaIndex – 1 hour – Beginner
  • Efficiently Serving LLMs – Predibase – 1 hour – Intermediate
  • Knowledge Graphs for RAG – Neo4j – 1 hour – Intermediate
  • Serverless LLM apps with Amazon Bedrock – AWS – 1 hour – Intermediate
  • ChatGPT Prompt Engineering for Developers – OpenAI – 1 hour – Beginner to Advanced
  • Building Systems with the ChatGPT API – OpenAI – 1 hour – Beginner to Advanced
  • LangChain for LLM Application Development – LangChain – 1 hour – Beginner
  • LangChain: Chat with Your Data – LangChain – 1 hour – Beginner
  • Finetuning Large Language Models – Lamini – 1 hour – Intermediate
  • Large Language Models with Semantic Search – Cohere – 1 hour – Beginner
  • Building Generative AI Applications with Gradio – HuggingFace – 1 hour – Beginner
  • Evaluating and Debugging Generative AI Models Using Weights and Biases – W&B – 1 hour – Intermediate
  • How Diffusion Models Work – 1 hour – Intermediate
  • Building Applications with Vector Databases – Pinecone – 1 hour – Beginner
  • Automated Testing for LLMOps – circleci – 1 hour – Intermediate
  • LLMOps – Google Cloud – 1 hour – Beginner
  • Build LLM Apps with LangChain.js – LangChain – 1 hour – Intermediate
  • Advanced Retrieval for AI with Chroma – Chroma – 1 hour – Intermediate
  • Reinforcement Learning from Human Feedback – Google Cloud – 1 hour – Intermediate
  • Building and Evaluating Advanced RAG Applications – LlamaIndex – 1 hour – Beginner
  • Quality and Safety for LLM Applications – Whylabs – 1 hour – Beginner
  • Vector Databases: from Embeddings to Applications – Weaviate – 1 hour – Intermediate
  • Functions, Tools and Agents with LangChain – LangChain – 1 hour – Intermediate
  • Pair Programming with a Large Language Model – Google – 1 hour – Beginner
  • Understanding and Applying Text Embeddings – Google Cloud – 1 hour – Beginner
  • How Business Thinkers Can Start Building AI Plugins With Semantic Kernel – Microsoft – 1 hour – Beginner
• 🦜🔗 LangChain Academy
  • Introduction to LangGraph – 40 lessons – 4 hours of video content
• Cohere
  • LLM University by Cohere
• Become an AI Developer – DataCamp
  • Introduction to Large Language Models with GPT & LangChain
  • Prompt Engineering with GPT & LangChain
  • Building Multimodal AI Applications with LangChain & the OpenAI API
  • Semantic Search with Pinecone
  • Retrieval Augmented Generation with OpenAI API & Pinecone
  • Building Chatbots with the OpenAI API and Pinecone
  • Using Open Source AI Models with Hugging Face
  • Building NLP Applications with Hugging Face
  • Image Classification with Hugging Face
• EdX
  • Databricks: Large Language Models: Application through Production – 6 weeks – 4-10 hours per week
  • Databricks: Large Language Models: Foundation Models from the Ground Up – 4 weeks – 4-8 hours per week
  • IBM: Introduction to Generative AI
  • IBM: Introduction to Prompt Engineering – 3 weeks – 1-3 hours per week
  • IBM: Models and Platforms for Generative AI – 3 weeks – 1-3 hours per week
  • IBM: Developing Generative AI Applications with Python – 6 weeks – 1–2 hours per week
• Coursera
  • Introduction to Large Language Models – Google Cloud – Approx. 1 hour – Beginner
  • Encoder-Decoder Architecture – Google Cloud – Approx. 1 hour – Advanced
  • Build a Chat Application using the PaLM 2 API on Cloud Run – Google Cloud – Project – 90 minutes – Intermediate
  • Generative AI with Large Language Models – AWS – Approx. 16 hours – Intermediate
• Scrimba Courses Library – Artificial Intelligence
  • Build AI Apps with ChatGPT, DALL-E and GPT-4 – 4.6 Hours – Intermediate
  • Deploy AI apps with Cloudflare – 50 Minutes – Intermediate
  • Intro to AI Engineering – 90 Minutes – Intermediate
  • Intro to AI Engineering – 90 Minutes – Intermediate
  • Intro to Mistral AI – 84 Minutes – Intermediate
  • Learn LangChain.js – 94 Minutes – Intermediate
  • Learn OpenAI's Assistants API – 30 Minutes – Intermediate
  • Learn to code with AI – 4.5 Hours – Beginner
  • Prompt Engineering for Web Developers – 3.1 Hours – Intermediate
• W&B AI Academy
  • RAG++ : From POC to Production – 75 lessons – 2 hours of video content
  • Developer's guide to LLM prompting – 25 lessons – 1 hour of video content
  • LLM Engineering: Structured Outputs – 34 lessons — 1 hour of video content
  • Building LLM-Powered Apps – 31 lessons – 2 hours of video content
  • Training and Fine-tuning Large Language Models (LLMs) – 37 lessons – 4 hours of video content
  • Enterprise Model Management – Cover end-to-end model lifecycle. Include LLM Case Study – 25 lessons – 2.5 hours of video content
• Google Cloud Skills Boost
  • Introduction to Generative AI Learning Path
    • 01 Introduction to Generative AI – Introductory
    • 02 Introduction to Large Language Models – 8 hours – Introductory
    • 03 Introduction to Responsible AI – 8 hours – Introductory
    • 04 Generative AI Fundamentals – 8 hours – Introductory
    • 05 Responsible AI: Applying AI Principles with Google Cloud – 8 hours – Introductory
  • Generative AI for Developers Learning Path
    • 01 Introduction to Image Generation – 8 hours – Introductory
    • 02 Attention Mechanism – 8 hours – Intermediate
    • 03 Encoder-Decoder Architecture – 8 hours – Intermediate
    • 04 Transformer Models and BERT Model – 8 hours – Introductory
    • 05 Create Image Captioning Models – 8 hours – Intermediate
    • 06 Introduction to Generative AI Studio – 8 hours – Introductory
    • 07 Generative AI Explorer - Vertex AI – 4 hours 15 minutes – Introductory
    • 08 Explore and Evaluate Models using Model Garden – 1 hour – Intermediate
    • 09 Prompt Design using PaLM – 1 hour 30 minutes – Introductory
• Activeloop
  • LangChain & Vector Databases in Production – 40 hours of learning content
  • Retrieval Augmented Generation for Production with LangChain & LlamaIndex – 1 hour of high-level video content – 25 hours of learning content
  • Training & Fine-Tuning LLMs for Production – 1.5 hrs of high-level video content – 40 hours of learning content
• Full Stack LLM Bootcamp (Spring 2023)
  1. Learn to Spell: Prompt Engineering
  2. LLMOps
  3. UX for Language User Interfaces
  4. Augmented Language Models
  5. Launch an LLM App in One Hour
  6. LLM Foundations
  7. Project Walkthrough: askFSDL
  8. What's Next?
  9. Reza Shabani: How To Train Your Own LLM
  10. Harrison Chase: Agents
  11. Fireside Chat with Peter Welinder
• Freecodecamp
  • Learn LangChain.js - Build LLM apps with JavaScript and OpenAI YouTube – Approx. 1 hour 30 minutes
• DAIR.AI
  • LLMOps: Building Real-World Applications With Large Language Models – Intermediate
  • Prompt Engineering Course
• The Chinese University of HongKong, Shenzhen
  • CSC 6201/CIE 6021 Large Language Models – Slides from 10 lectures
• NVIDIA – Self-Paced Courses
  • Generative AI Explained – 2 Hours – Technical - Beginner
  • Augmenting LLMs using Retrieval Augmented Generation – 1 Hour – Technical - Beginner
  • Building RAG Agents for LLMs – 8 Hours – Technical - Intermediate
• Weaviate Academy
  • PY_101T: Text data with Weaviate – Python – Project-based
  • PY_101V: Your own vectors with Weaviate – Python – Project-based
  • PY_101M: Multimodal data with Weaviate – Python – Project-based
  • PY_220: Flexible data representation: Named vectors – Python – Project-based
  • PY_230: Vector indexes – Python
  • PY_250: Vector compression for improved efficiency – Python
  • PY_275: Text tokenization – Python
  • PY_280: Multi-tenancy – Python
  • TS_100: Intro to Weaviate with TypeScript (or JavaScript) – TypeScript – Project-based
• Web Security Academy by Portswigger (the creators of Burp Suit)
  • Web LLM attacks – Short course + 4 labs
• Neo4j Generative AI Courses
  • Neo4j & LLM Fundamentals – 4 Hours
  • Introduction to Vector Indexes and Unstructured Data – 2 Hours
  • Build a Neo4j-backed Chatbot using Python – 2 Hours - Feat. Langchain and Streamlit
  • Build a Neo4j-backed Chatbot with TypeScript – 6 Hours - Feat. Langchain and Next.js
  • Building Knowledge Graphs with LLMs – 2 Hours