Courses

Numerical Methods in Python Programming

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Learn the workings of the most common numerical methods and a step by step process on how to program each of them

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Approximate integrals using Trapezoidal rule, Simpson’s 1/3 rule, and Romberg integration

Find roots of equations using bisection, False position, newton Raphson, and secant methods

Find analytically the optimum min and max of a function

Solve Ordinary Differential Equations using Runge Kutta Methods (i.e. Euler, Heun’s, Midpoint, and Ralston Methods in

Find numerically the optimum min and max using Golden section Search method, newton Raphson Technique, and finally the

Solve Systems of Equations using Gauss elimination

Perform curve fitting using regression analysis including linear and polynomial regression in addition to linearization

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