Thứ Ba, Tháng Mười 26, 2021

## Description

Python Programming and Numerical Methods: A Guide for Engineers and Scientists introduces programming tools and numerical methods to engineering and science students, with the goal of helping the students to develop good computational problem-solving techniques through the use of numerical methods and the Python programming language. Part One introduces fundamental programming concepts, using simple examples to put new concepts quickly into practice. Part Two covers the fundamentals of algorithms and numerical analysis at a level that allows students to quickly apply results in practical settings.

Many of the Numerical Analysis courses focus on the theory and derivations of the numerical methods more than the programming techniques. Students get the codes of the numerical methods in different languages from textbooks and lab notes and use them in working their assignments instead of programming them by themselves.

For this reason, the course of Programming Numerical Methods in Python focuses on how to program the numerical methods step by step to create the most basic lines of code that run on the computer efficiently and output the solution at the required degree of accuracy.

This course is a practical tutorial for the students of Numerical Analysis to cover the part of the programming skills of their course

In addition to its simplicity and versatility, Python is a great educational computer language as well as a powerful tool in scientific and engineering computations. For the last years, Python and its data and numerical analysis and plotting libraries, such as NumPySciPy and matplotlib, have become very popular programming language and tool in industry and academia.

That’s why this course is based on Python as programming language and NumPy and matplotlib for array manipulation and graphical representation, respectively. At the end of each section, a number of SciPy numerical analysis functions are introduced by examples. In this way, the student will be able to program his codes from scratch and in the same time use the advanced library functions in his work.

This course covers the following topics:

• Roots of High-Degree Equations.
• Interpolation and Curve Fitting.
• Numerical Differentiation.
• Numerical Integration.
• Systems of Linear Equations.
• Ordinary Differential Equations.

## What you’ll learn

• Program the numerical methods to create simple and efficient Python codes that output the numerical solutions at the required degree of accuracy.
• Create and manipulate arrays (vectors and matrices) by using NumPy.
• Use the plotting functions of matplotlib to present your results graphically.
• Apply SciPy numerical analysis functions related to the topics of this course.

## This course includes:

• 12.5 hours on-demand video
• Access on mobile and TV
• Certificate of completion

## Who this course is for:

• The students who currently study their first course in numerical methods and need to understand how the methods are coded in detail.
• The students who need to create their own numerical analysis codes or use Python numerical libraries for their course, project or thesis works.

### Key Features

• Includes tips, warnings and “try this” features within each chapter to help the reader develop good programming practice
• Summaries at the end of each chapter allow for quick access to important information
• Includes code in Jupyter notebook format that can be directly run online

Source Course: Programming Numerical Methods in Python | Udemy

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