MATH-261 Scientific Computing
Fall for 2016-2017
The primary objective of the course is to develop the understanding of the construction of numerical algorithms to solve common problems in science and engineering. Topics include the following:
-root finding for nonlinear equations,
-solving systems of linear equations,
-interpolation and approximation of functions by simpler computational building blocks (for example - polynomials and splines).
-numerical differentiation and divided differences
-numerical quadrature and integration,
-numerical solutions of ordinary differential equations,
An important component of numerical analysis is computational implementation of algorithms which are developed in the course in order to observe first hand how the algorithm work. Programming language used is Python, a widely used high level general purpose language which is more readable and easy to learn. Prior programming experience is not required, though preferred.
prerequisites: Linear Algebra and Calculus III
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