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
- 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
- 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
- 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
- Introduction to Generative AI Learning Path
- 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)
- Freecodecamp
- Learn LangChain.js - Build LLM apps with JavaScript and OpenAI YouTube – Approx. 1 hour 30 minutes
- DAIR.AI
- 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