## Numerical Methods in Python Programming

### 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

Numerical Methods in Python Programming

- 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 descent/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’s 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. And 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.

**But…**

There is a limitation to numerical methods. They depend on iterative calculations. If for example, you want an approximation with a low error, for example, 0.001%, this will require a large number of calculations which can be sometimes impossible to do by hand not to mention tedious. This is where programming comes in.

In this course, I will walk you through not only the workings of each technique but a step-by-step process on how to program each of these techniques and perform hundreds if not thousands of calculations with a click of a button using one of the most popular programming languages – Python.

The **great thing** about programming languages is they all follow the same **programming structure, **sequence, repetition, and decision making.** **Meaning, if you know one language you can learn another very easily by just knowing how these structures are defined in the new language.

In this course, you’ll have a very good grasp of this structure so if you decide to learn another language afterward it will be **very easy.**

#### Who this course is for:

- Students enrolled in their first numerical Methods Class and interested in additional mentoring
- Who students interested to learn the most common Numerical Methods Techniques used in science and engineering
- Students interested in understanding how to program and create Numerical Modelling Techniques
- Last updated 8/2021

#### Numerical Methods in Python Programming

Content From: https://www.udemy.com/course/numerical-methods-in-python-programming/

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