AMS 326 — Numerical Analysis
Numerical methods for the standard problems of scientific computing: root finding, interpolation, quadrature, linear systems, and ordinary differential equations.
Instructor: Prof. Tan H. Cao
Term: Spring
Location: SUNY Korea
🔗 Official course page (Stony Brook AMS): AMS 326 — Numerical Analysis
Course overview
An introductory course in numerical analysis. Students implement the core algorithms in Python (or MATLAB), analyze their convergence, and apply them to concrete scientific-computing problems.
Main topics
- Sources of error; floating-point arithmetic and conditioning
- Root finding: bisection, Newton’s method, secant method
- Polynomial and spline interpolation
- Numerical differentiation and integration (quadrature)
- Direct and iterative methods for linear systems
- Numerical solution of ordinary differential equations
Prerequisites
AMS 210 (Linear Algebra), AMS 161 (Applied Calculus II), and basic programming experience.
Materials
Provided through Brightspace.