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Udemy - Numerical Methods in Python Programming

Torrent: Udemy - Numerical Methods in Python Programming
Description:

Numerical Methods in Python Programming



MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz, 2 Ch
Genre: eLearning | Language: English + srt | Duration: 38 lectures (6h 4m) | Size: 1.54 GB
Learn the workings of the most common numerical methods and a step by step process on how to program each of them
What you'll learn:
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 addition to fourth order Runge Kutta Method
Find numerically the optimum min and max using Golden section Search method, newton Raphson Technique and finally the gradient decent/ascent method
Solve Systems of Equations using Gauss elimination
Perform curve fitting using regression analysis including linear and polynomial regression in addition to linearization for fitting more complex functions

Requirements
Computer & Access to Microsoft Excel
Knowledge of basic Algebra, Geometry & Calculus Concepts
Knowledge of basic Python Programming

Description
Numerical modeling is a very powerful branch of mathematics. It is capable to solve very complex problems using very simple techniques.

It is a branch that can differentiate and integral without the need to use any of the sometimes complex differentiation and integration rules. It can create best fit models with just knowing a data set. It can create functions where the only thing we know is its derivative and a condition. And best of all, it can generate approximations that have such a low percentage error that they are as good as the true value.

Downloads: 195
Category: Other/Tutorials
Size: 1.8 GB
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Added: 2021-08-22 11:10:24
Language: English
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