Math for Programming & AI

For coders, machine learning & data

The math that powers software and modern AI — the algebra and logic foundations, then the linear algebra, probability, statistics, and calculus behind machine learning.

Assumes you're comfortable with Pre-Algebra. New to that? The School journey starts from the very beginning.

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1
Algebra0/38
Learn the language of math: why letters exist, what equations really mean, and how to solve them.
2
Discrete Math & Logic0/32
The math of computer science: logic, sets, counting, proofs, recursion, and graphs.
3
Number Theory0/32
The hidden patterns of integers: primes, modular arithmetic, cryptography, and unsolved mysteries.
4
Linear Algebra0/32
The math behind AI, graphics, and data: vectors, matrices, determinants, and transformations.
5
Probability0/32
The mathematics of chance: from coin flips to Bayes, distributions, expected value, and risk.
6
Statistics0/33
Make sense of data — from averages and spread to probability, distributions, and Bayes' theorem.
7
Calculus0/33
The mathematics of change: derivatives, integrals, and infinity — taught through intuition first.
8
Multivariable Calculus0/32
Calculus in higher dimensions: partial derivatives, gradients, multiple integrals, and vector fields — the math behind machine learning and physics.