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Understand AI.
Build it yourself.

Discover how language models work. Short lessons, real exercises and a clear path from your first token to your own model.

  • 10sections
  • 250lessons
  • 1,608exercises
  • 4learning rooms
  • German & Englishcourse languages

Built for keeping at it.

  • A daily routine

    Your daily goal: one lesson. Your streak counts the days you learn in a row, XP your progress.

    Find your first step
  • Understand your next step

    Try it, get feedback and understand why. Exercises check your answers. Open tasks such as explanations are self-assessed.

    Try an example
  • A real project for your computer

    With Plus you download tiny-gpt-cpu: a Python project in 10 steps from tensors to a small GPT, checked with local CPU tests. Tested on macOS with Apple Silicon.

    Explore Plus

See what happens inside.

A sentence becomes tokens. Attention connects them. Follow each step and try the interactive example right here.

The model studio

From a sentence to the next token.

Interactive example

Sample input

KI lernt aus Daten.

5 tokensGerman sample

One sentence. Three steps. Explore the building blocks behind it.

„KI lernt aus Daten.“

  1. kiID 1
  2. lerntID 2
  3. ausID 3
  4. datenID 4
  5. .ID 5

The tokenizer splits the German sample into tokens and gives each one an ID.

What you learn here

Text becomes computable.

A language model works with numbers. Token IDs connect pieces of text to the vocabulary.

Simplified illustration with example values, not a trained model

Each idea builds on the last.

10 sections250 lessons

Free: sections 1–2With Plus: sections 3–10

  1. Language model foundations

    Free

    Capabilities, limitations and transformer architecture

    7 units, 21 lessons

  2. PyTorch foundations

    Free

    Tensors, automatic differentiation and training loops

    9 units, 27 lessons

    Learning room: A model learns Free, 18 min
  3. Working with text data

    Plus

    Tokenization, token IDs and embeddings

    8 units, 24 lessons

    Learning room: Text becomes tokens Plus, 12 min
  4. Implementing attention

    Plus

    Self-attention, causal masks and multiple heads

    11 units, 33 lessons

    Learning room: Who can see whom? Plus, 15 min
  5. Building a GPT model

    Plus

    Transformer blocks, normalization and text generation

    7 units, 21 lessons

  6. Pretraining on unlabeled data

    Plus

    Loss, evaluation and the training loop

    9 units, 27 lessons

  7. Fine-tuning for classification

    Plus

    Prepare labeled examples and adapt the model

    8 units, 24 lessons

  8. Fine-tuning for instructions

    Plus

    Instruction datasets, response generation and evaluation

    9 units, 27 lessons

  9. Efficient training and PEFT

    Plus

    Memory budgets, quantization and efficient adaptation

    10 units, 30 lessons

    Learning room: Will the model fit? Plus, 15 min
  10. Capstone: project plan and local checks

    Plus

    Plan your project and verify it in your own environment

    8 units, 16 lessons

Try each step for yourself.

Split text into tokens, build an attention mask, train a small set of weights or plan a memory budget. The 4 learning rooms turn course concepts into focused experiments.

These experiments run in your browser. For your own Python and PyTorch projects, you need a suitable local environment or notebook.

  • Tokenization

    Text becomes tokens

    Split text, trace token IDs, and repair a small vocabulary.

    12 minPlus

  • Causal attention

    Who can see whom?

    Build an attention mask and stop the model from seeing the future.

    15 minPlus

  • Model memory

    Will the model fit?

    Plan weights, runtime reserve, and context within a fixed memory budget.

    15 minPlus

  • Training & evaluation

    A model learns

    Train real weights in your browser and learn what a metric actually proves.

    18 minFree

Explore the rooms

Before you begin.

What experience do I need?

You can start without prior knowledge of LLMs. Basic Python helps with the later coding exercises. The PyTorch section introduces tensors, autograd and training loops.

Which languages can I learn in?

Choose English or German for your learning session. Keep quoted text and specified code values exactly as shown in an exercise, even when those values are in another language.

Can I run full PyTorch training here?

The course teaches Python and PyTorch through explanations and exercises. Selected JavaScript exercises and small experiments run in your browser. Full PyTorch training runs in your own environment.

What can I learn for free?

Free includes LLM and PyTorch foundations: 16 units and 48 lessons with their guides, plus the learning room “A model learns”. Plus opens the full path and all 4 rooms. View plans and availability

Start with the foundations.

The LLM and PyTorch foundations are free: 16 units and 48 lessons.

Tell me when Plus launches

One email when Plus can be booked, and one before it to confirm your address. No newsletter.