A number of Mathematics online courses are offered at the graduate level. These may be taken as part of a certificate or degree program, or by non-degree-seeking students on a course-by-course basis. For those interested in taking individual courses without enrolling in a degree or certificate program, you must first apply to be a non-degree studies (NDS) student. To learn more about enrolling as an NDS student or registering for courses, visit our Apply page.
Visit NC State’s Graduate Online and Distance Education tuition rates page for detailed information about the fee schedule for online and on-campus courses.
Our graduate-level Mathematics online courses are designed to provide convenient access to the training that is often required for career advancement. The application process is very simple, and online courses can be taken individually for continuing education or for the Online Masters Program. Find descriptions of our graduate-level Mathematics online courses below.
Click on links or scroll down for course descriptions, semester offered, and delivery method
This course will provide an overview of methods to solve quantitative problems and analyze data. The tools to be introduced are mathematical in nature and have links to Algebra, Analysis, Geometry, Graph Theory, Probability and Topology. Students will acquire an appreciation of (I) the fundamental role played by mathematics in countless applications and (II) the exciting challenges in mathematical research that lie ahead in the analysis of large data and uncertainties. Students will work on a project for each unit. While this is not a programming class, the students will do some programming through their projects. Prerequisite: MA 341 or MA 405 or MA 591 and some programming experience.
This course offers a rigorous treatment of linear algebra, including systems of linear equations, matrices, determinants, abstract vector spaces, bases, linear independence, spanning sets, linear transformations, eigenvalues and eigenvectors, similarity, inner product spaces, orthogonality and orthogonal bases, factorization of matrices.
This course covers topics from linear algebra and multivariable calculus. The computational and theoretical linear algebra topics includes linear transformations, matrix algebra, bases, eigenvalues and eigenvectors, and first and second order differential equations. Topics from multivariable calculus include multivariable functions, directional derivatives, tangent planes, Taylor’s theorem, optimization and Lagrange multipliers. This course is intended as a review of the aforementioned topics for students preparing for a return to studies in a STEM field (Science, Technology, Engineering and Mathematics). Prerequisite: good standing
Survey of mathematical methods for engineers and scientists. Ordinary differential equations and Green’s functions; partial differential equations and separation of variables; special functions, Fourier series. Applications to engineering and science.. Prerequisite: MA 341 or MA 591
Determinants and matrices; line and surface integrals, integral theorems; complex integrals and residues; distribution functions of probability. Prerequisite: MA 341 or MA 591
Topics in geometry of concern to secondary teachers in their work and provision for background and enrichment. Various approaches to study of geometry, including vector geometry, transformational geometry and axiomatics. Prerequisite: graduate standing
Real number system, functions and limits, topology on the real line, continuity, differential and integral calculus for functions of one variable. Infinite series, uniform convergence. Credit is not allowed for both MA 425 and MA 511.
Operations with complex numbers, derivatives, analytic functions, integrals, definitions and properties of elementary functions, multivalued functions, power series, residue theory and applications, conformal mapping. Prerequisite: MA 242
Vector spaces, linear transformations and matrices, orthogonality, orthogonal transformations with emphasis on rotations and reflections, matrix norms, projectors, least squares, generalized inverses, definite matrices, singular values. Prerequisite: MA 405 or MA 591
Algorithm behavior and applicability. Effect of roundoff errors, systems of linear equations and direct methods, least squares via Givens and Householder transformations, stationary and Krylov iterative methods, the conjugate gradient and GMRES methods, convergence of method. Prerequisite: MA 405; MA 425 or MA 511; high-level computer language.
This is a special topics course taught by Dr. Jessica Matthews as part of the 2017-2018 Program on Mathematical and Statistical Methods for Climate and the Earth System (CLIM) at the Statistical and Applied Mathematical Sciences Institute (SAMSI).