Jay Newby

MATH 381 - Numerical Methods

Approximation of functions by Taylor series, Newton's formulae, Lagrange and Hermite interpolation. Splines. Orthogonal polynomials and least-squares approximation of functions. Direct and iterative methods for solving linear systems. Methods for solving non-linear equations and systems of non-linear equations. Introduction to computer programming. Prerequisites: One of MATH 102, 125 or 127, and one of MATH 209, 214 or 217. Notes: (1) Credit cannot be obtained in MATH 381 in the same term as CMPUT 340 or if credit has already been obtained in CMPUT 340.(2) Extra classes may be held for students lacking a background in one of the major programming languages such as Fortran, C, C++ or Matlab.

MATH 509 - Data Structures and Platforms

Basic data analysis with R, SAS, and Python. Program development with Jupyter notebooks. Cloud computing, collaborative software development, docker containers, kubernets. Internet security, privacy and ethics. Technologies will be updated as new developments arise. Prerequisites: No programming skills are needed.

MATH 536 - Numerical Solutions of Partial Differential Equations I

Finite difference and finite element methods for boundary-value problems of elliptic equations. Numerical algorithms for large systems of linear algebraic equations: direct, classical relaxation, multigrid and preconditioned conjugate gradient methods. Algorithms for vector/parallel computers and the domain decomposition method. Prerequisites: MATH 337, 436 or equivalent and some computer programming.

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