Calculus Practice
Cover single-variable foundations, multivariable differentiation, approximation, and optimization.
Recommended resources
- MIT 18.02SC Multivariable Calculus — MIT OpenCourseWare
Instructions
- State dimensions for vector and matrix derivatives.
- Separate method-selection errors from algebra errors.
Ordered items
- Limit, derivative, integral, and Taylor check
- Gradient, tangent plane, linearization, and directional derivative
- Jacobian and chain rule
- Critical points and constrained domain boundaries
- Multivariable chain rule under a change of variables
- Lagrange multiplier equations and tangent geometry
- Total differentials and implicit differentiation
- Matrix gradient and Hessian
Completion
Derive gradients, Jacobians, Hessians, and constrained first-order conditions without relying on source notation.