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Video course · 15 chapters · 704 min · certificate

Learn Generative AI: Free Full Course on LLMs, RAG, and Agents

A full generative AI course: AI history and types, agentic AI, the GenAI value chain, hands-on APIs, transformers, Hugging Face and inference pipelines, RAG with LangChain, prompt templates, open-source models and AI agents with tools.

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What you'll learn

  • Explain AI types and the history of generative AI
  • Distinguish generative and agentic AI
  • Call models through APIs in Python
  • Explain the transformer architecture
  • Use Hugging Face models and pipelines
  • Build RAG with LangChain and agents with tools

Chapters

15 chapters · 704:07
  1. 9:23 01Foundations Members AI fundamentals What AI is, its history and evolution, and the types of AI.
  2. 15:07 02Agents Members Agentic AI Agentic AI goes a step beyond generative AI by taking actions toward goals.
  3. 38:06 03GenAI Members Introduction to generative AI Splitting AI into parts, where applications stand, and how we get to more general systems.
  4. 19:13 04Industry Members The GenAI value chain Who builds what: model makers, platforms and applications.
  5. 48:54 05Hands-on Members Hands-on with APIs Calling models through the OpenAI API in Python.
  6. 107:05 06Transformers Members Transformer architecture How transformers work and how GenAI can automate workflows like customer service.
  7. 6:22 07Tools Members The Transformers library Multi-head attention and stacked blocks, and the Transformers library.
  8. 112:53 08Hugging Face Members Hugging Face Accessing models on Hugging Face and reading model cards.
  9. 103:33 09Pipelines Members Inference pipelines Using inference pipelines to apply models to real tasks.
  10. 26:24 10RAG Members Introduction to RAG Why models state wrong facts and how retrieval-augmented generation helps.
  11. 37:41 11RAG Members How RAG works Embedding documents and queries, retrieving similar articles, and generating grounded answers.
  12. 32:44 12LangChain Members RAG with LangChain Building RAG with LangChain loaders and chains.
  13. 36:11 13LangChain Members Prompt templates Using prompt templates with variables and chaining steps.
  14. 10:11 14Open source Members Open-source models Accessing free open-source models locally or through the cloud.
  15. 100:20 15Agents Members AI agents and tools Building AI agents that use tools, and installing what's needed.

Jobs this course suits

Our AI checked this course against 500 jobs; these get the most out of it. Each job links to its learning path.

Software DevelopersComputer Science StudentsSoftware EngineersData ScientistsIT ConsultantsWeb DevelopersWebsite DevelopersData AnalystsSystems AnalystsIT SpecialistsBioinformaticiansBlockchain Developers