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MATH 261 - Scientific Computing |

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, optimization methods; 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 3.000 Credit hours 3.000 Lecture hours Levels: Undergraduate Schedule Types: Lecture, Seminar Mathematics Department Course Attributes: Mean Grade is Calculated Prerequisites: MATH 137 and MATH 150 |

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