Learn ML / Stage 1

1 · Foundations

The maths that machine learning and computational modelling are built on.

By the end of this stage, you can…multiply matrices and explain what an eigenvector is, take partial derivatives and use the chain rule, work with probability distributions, expectation and variance, update a belief with Bayes' theorem, explain what a confidence interval and a p-value tell you, and explain how gradient descent finds a minimum.

What you will learn

• Linear algebra Essential
• Calculus Essential
• Probability Essential
• Statistics Essential
• Optimisation Essential
• School maths refresher If you need it

Resources per subject

proof-based you learn by proving results · practical you learn by computing and applying