Course Information
Registration period
Year-round Recruitment
Course Level
Study Mode
Duration
12 Hour(s) 18 Minute(s)
Language
English
Taught by
Murad Elarbi
Rating
3 views
Course Overview
A Practical Approach to Understand the Numerical Methods
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 NumPy, SciPy 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
Course Content
- 7 section(s)
- 57 lecture(s)
- Section 1 Introduction
- Section 2 Roots of High-Degree Equations
- Section 3 Interpolation and Curve Fitting
- Section 4 Numerical Differentiation
- Section 5 Numerical Integration
- Section 6 Systems of Linear Equations
- Section 7 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.
Skills covered in this course
Reviews
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IIsmael Diaz Del Rio
Very complete course to remind numerical methods! Everything is very well explained and it's very easy to follow. Just missed some deeper explanation of the sense of the RK4 method (I'll search for it) and also a simplier integration method: sum the values in the middle of each division, simple and accurate. Great job!
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MMarcel Louis
Really great lecture
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AAdk
no
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GGuillermo Hernán Martín
IMHO the teacher can improve a little the way he explains lessons. He does it like the average math teacher, which is not great. Lots of reading equations with abstract names like 'x', 'y', 'u'... Very easy to get lost. On the other hand, the part of showing how it can be translated to computer code helps a lot to understand the concepts. I do encourage to do all the exercises. However, in the code part can also be improved, by making a little more effort to make the code more readble. Particularly, by using meaningful names and using divide & conquer strategy to make smaller, easier to understand functions.
