Intuitive visual lessons explaining derivatives, integrals, and fundamental calculus concepts.
Before computing gradients across deep computational graphs, you need an intuitive grasp of rates of change, tiny nudges (`dx`), power/product/exponential rules, and the chain rule. This visual series builds calculus from geometric principles so you feel how small parameter perturbations affect model loss.
Course status is tracked independently from roadmap topic checkboxes so you can mark external courses without altering your topic mastery percentage.
Phase 1 Visual Intuition for Module 1.2 (Calculus)
All video chapters and interactive text versions are freely accessible.
Status: Verified (2026-11-09)
Review these foundations before starting so you get the most out of this material:
In Phase 1: Mathematics for AI
Watch at the start of Module 1.2, paying special attention to the episodes on the Chain Rule, Exponential derivatives, and Taylor series.
Comprehensive MIT OpenCourseWare Scholar course covering differentiation, the chain rule, optimization of single-variable functions, and integration.
University course on vectors, matrices, partial derivatives, gradient vectors, directional derivatives, and multivariable optimization.
Visual explanations of vectors, transformations, matrix multiplication, eigenvectors, and the intuition behind linear algebra.