Learn AI1

Last reviewed 28 October 2026

AI explained for lawyers.1

Your AI knowledge shouldn’t be a footnote.

Learn AI explains how modern AI works, and where it meets the law, for lawyers who need to use it, advise on it and spot where it goes wrong.

Start with Module 1See the whole course

Part 1: How the machine works

Tiles with a passing sheen turn over to show what each module covers.

Module 1 · about 20 minutesWhat a model isThe small amount of mathematics the course uses, what a trained model physically consists of, and how weights, biases and layers turn input numbers into an output.Inside this module
  • The mathematics used in this course
  • A file of numbers and a recipe
  • The artificial neuron
  • Layers and depth
  • What a parameter is
Open the module →
Module 2 · in preparationHow a model learnsLoss, gradient descent and backpropagation, why models generalise and memorise at once, and how training compute became a regulatory yardstick.Inside this module
  • Measuring error
  • Walking downhill
  • Backpropagation
  • Learning versus memorising
  • Chips and the two phases
Module 3 · in preparationWords as numbersHow text is cut into tokens, why tokenisation causes odd failures, and how embeddings turn meaning into position.Inside this module
  • Cutting text into tokens
  • Where tokens trip models up
  • Embeddings: meaning as position
Module 4 · in preparationThe transformerAttention, feed-forward layers, the residual stream and next-token prediction, with the costs of long context.Inside this module
  • Where it came from
  • Attention
  • Feed-forward layers and stored facts
  • Depth, order and the running total
  • Predicting the next token
Module 5 · in preparationFrom predictor to assistantPretraining at scale, scaling laws, the post-training that turns a text predictor into an assistant, reasoning models, experts and distillation.Inside this module
  • Pretraining: reading the library
  • Scaling laws
  • Post-training: from document completer to assistant
  • Reasoning models
  • Experts and students
Module 6 · in preparationSampling, hallucination and memorisationHow a model chooses each word, why it invents things, and what the research shows about models reproducing their training data.Inside this module
  • Choosing the next token
  • Why models make things up
  • Memorisation
CourseAll fourteen modulesFrom what a model is to the law that governs it, in four parts.The four parts
  • How the machine works
  • Deployment, inspection and testing
  • Where the technology meets the law
  • The road ahead
See the course →ReferenceGlossaryEach term of art used in the course, explained in a sentence.Open →AboutHow the site checks its factsSources, review dates and the disclaimer.Open →