THE BEGINNER LEARNING SERIES

Local AI,
one idea at a time.

Start with no technical knowledge. Learn one idea, see a diagram, watch an explanation, and try a small exercise. No coding is needed for the first five lessons.

Start lesson 1 →

Your learning path

The first five lessons are available. The remaining lessons show our planned teaching order and will be published later. Learn at your own pace.

  1. 01
    Local AIRead the lesson →
  2. 02
    AI modelRead the lesson →
  3. 03
    EngineRead the lesson →
  4. 04
    PromptRead the lesson →
  5. 05
    TokenRead the lesson →
  6. 06
    Context windowPlanned lesson
  7. 07
    Parameters and weightsPlanned lesson
  8. 08
    TrainingPlanned lesson
  9. 09
    InferencePlanned lesson
  10. 10
    RAMPlanned lesson
  11. 11
    CPUPlanned lesson
  12. 12
    GPUPlanned lesson
  13. 13
    VRAMPlanned lesson
  14. 14
    StoragePlanned lesson
  15. 15
    QuantizationPlanned lesson
  16. 16
    Model formats and GGUFPlanned lesson
  17. 17
    Open weights and licencesPlanned lesson
  18. 18
    EmbeddingsPlanned lesson
  19. 19
    Document chunksPlanned lesson
  20. 20
    RAG and citationsPlanned lesson
  21. 21
    Vision modelsPlanned lesson
  22. 22
    Speech recognitionPlanned lesson
  23. 23
    Text-to-speechPlanned lesson
  24. 24
    AvatarsPlanned lesson
  25. 25
    APIsPlanned lesson
  26. 26
    Tool callingPlanned lesson
  27. 27
    AgentsPlanned lesson
  28. 28
    HallucinationsPlanned lesson
  29. 29
    BenchmarksPlanned lesson
  30. 30
    Privacy and safe usePlanned lesson

How the lessons connect

Lessons 1–9 explain the basic ideas. Lessons 10–17 explain your computer and model files. Lessons 18–24 cover documents, images, voice, and avatars. Lessons 25–30 explain connections, mistakes, testing, and safe use.

An avatar is a digital character or face. We introduce it after voice and vision so you can understand what makes a talking character work.

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