Courses

Electric charge and fields, Gauss's law, electric potential, capacitance, current and circuits, magnetic fields and forces, and electromagnetic induction.

Functions and their graphs: notation, domain and range, rates of change, composition, transformations, absolute value and inverse functions.

Systems of equations, matrices, determinants, vector geometry, and their use in Leontief models, Markov chains and linear programming.

Probability, multivariate calculus and the mathematics behind modern machine learning, from linear regression to diffusion models.