We build intuition from first principles, back it with honest mathematical derivations, and let you play with live neural network simulations. No dry manuals, no hand-waved proofs.
Traditional textbooks bury you in notation before you know why it exists. We move the other way around — intuition first, formalism as the payoff.
Every topic flows naturally — the problem that existed, the constraint that blocked it, and the creative leap that broke it open.
Interact with the equations themselves. Change learning rates, drag weights, and watch backpropagation adapt in real time.
No skipped derivations. Linear algebra, calculus and statistics are fully expanded, with every variable explained where it appears.
Skip Python packaging, driver mismatches, and notebook setup. Read, run and evaluate models straight from the browser.
The big picture before the equations
A gentle, big-picture course for absolute beginners — starting with why AI exists at all, and building up a clear, correct mental model of how Artificial Intelligence, Machine Learning, and Deep Learning actually relate to each other.
From a single neuron to a network that learns
A story-driven, from-first-principles walk through neural networks — starting with a single artificial neuron and ending with a fully trained multi-layer perceptron, backpropagation, optimizers, and everything in between.
From pixels to predictions — how machines learn to see
A story-driven, from-first-principles walk through convolutional neural networks — starting with why plain MLPs fail on images and ending with modern architectures, training pipelines, and the interview questions that test it all.
Open the syllabus and start building neural networks from scratch today. Nothing to install, nothing to configure.