Foundations of Scientific Computing

Catalog description

This course will introduce students to foundational concepts in numerical computation that are useful for engineering and the mathematical, computational, and physical sciences. Topics will include floating-point arithmetic, error analysis, linear and nonlinear equations, numerical solution of systems of algebraic equations, constrained and unconstrained optimization, polynomial interpolation, numerical differentiation and integration, numerical solution of ordinary differential equations, truncation error, and basic methods for sampling stochastic processes. Implementation of various numerical methods and solvers will be done in Python, MATLAB, and R. Connections to computational modeling of cognition will be made throughout the course as motivating examples for various key concepts and tools.