Calculus for AI — Derivatives, Gradients, and How Neural Networks Learn

This course is for those who want to understand the calculus and backpropagation formulas behind deep learning. Starting with functions and limits, you will learn derivatives, the chain rule, gradients, and gradient descent in sequence, then manually calculate the forward propagation, loss calculation, backpropagation, and weight updates of a small neural network. Explore the concepts through animations without coding or installation, and connect the formulas to the AI learning process.