Tracks

AI from zero

What AI is, how it learns from examples, and how a chatbot picks its next word.

Start with What is AI, really?

How machines learn

Loss, gradients, and generalization: the loop behind every trained model.

Start with The learning loop

Neural networks

Neurons, layers, and backpropagation, built up one piece at a time.

Builds on How machines learn

Start with Layers are matrix multiplications

Language as vectors

Tokens, embeddings, and similarity: how text becomes geometry.

Builds on How machines learn

Start with Tokens

Transformers and LLMs

Attention, the transformer block, and how large language models are trained.

Builds on Neural networks and Language as vectors

Start with Predicting the next token

Learning by trial and error

Rewards, exploration, and how agents learn to act, from bandits to RLHF.

Builds on How machines learn and Neural networks

Inside the model

Look inside a real language model, watch circuits form, and steer what it says.

Builds on Transformers and LLMs

Frontiers

Diffusion, multimodal models, agents, and reasoning.

Builds on Transformers and LLMs

Start with Diffusion: from noise to data