Numerical Methods for Data Science

Catalog description

This course introduces a broad range of numerical techniques that are widely used in mathematics, science, and engineering. The topics covered in this course include basic direct and iterative methods for linear systems; classical root-finding methods; Newton’s method and related methods for nonlinear systems; fixed-point iteration; polynomial, piecewise polynomial, and spline interpolation methods; least-squares approximation; orthogonal functions and approximation; basic techniques for numerical differentiation; numerical integration, including adaptive quadrature; and methods for initial-value problems for ordinary differential equations. Python, or similar software, will be used to implement the methods covered in the class.