Classbaze

Disclosure: when you buy through links on our site, we may earn an affiliate commission.

Programming Numerical Methods in Python

A Practical Approach to Understand the Numerical Methods
4.4
4.4/5
(662 reviews)
3,590 students
Created by

8.7

Classbaze Grade®

7.2

Freshness

8.9

Popularity

9.5

Material

A Practical Approach to Understand the Numerical Methods
Platform: Udemy
Video: 12h 18m
Language: English
Next start: On Demand

Best Python classes:

Classbaze Rating

Classbaze Grade®

8.7 / 10

CourseMarks Score® helps students to find the best classes. We aggregate 18 factors, including freshness, student feedback and content diversity.

Freshness

7.2 / 10
This course was last updated on 1/2020.

Course content can become outdated quite quickly. After analysing 71,530 courses, we found that the highest rated courses are updated every year. If a course has not been updated for more than 2 years, you should carefully evaluate the course before enrolling.

Popularity

8.9 / 10
We analyzed factors such as the rating (4.4/5) and the ratio between the number of reviews and the number of students, which is a great signal of student commitment.

New courses are hard to evaluate because there are no or just a few student ratings, but Student Feedback Score helps you find great courses even with fewer reviews.

Material

9.5 / 10
Video Score: 9.5 / 10
The course includes 12h 18m video content. Courses with more videos usually have a higher average rating. We have found that the sweet spot is 16 hours of video, which is long enough to teach a topic comprehensively, but not overwhelming. Courses over 16 hours of video gets the maximum score.
The average video length is 7 hours 31 minutes of 1,582 Python courses on Udemy.
Detail Score: 9.5 / 10

The top online course contains a detailed description of the course, what you will learn and also a detailed description about the instructor.

Extra Content Score: 9.5 / 10

Tests, exercises, articles and other resources help students to better understand and deepen their understanding of the topic.

This course contains:

0 article.
13 resources.
0 exercise.
0 test.

In this page

About the course

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

What can you learn from this course?

✓ 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.

What you need to start the course?

• You should have a good background in algebra and calculus, in addition to the basic knowledge about computers
• A Python IDE and its libraries NumPy, matplotlib and SciPy should be installed on your computer.
• No previous experience in programming in Python is required.

Who is this course is made 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.

Are there coupons or discounts for Programming Numerical Methods in Python ? What is the current price?

The course costs $16.99. And currently there is a 81% discount on the original price of the course, which was $89.99. So you save $73 if you enroll the course now.
The average price is $20.1 of 1,582 Python courses. So this course is 15% cheaper than the average Python course on Udemy.

Will I be refunded if I'm not satisfied with the Programming Numerical Methods in Python course?

YES, Programming Numerical Methods in Python has a 30-day money back guarantee. The 30-day refund policy is designed to allow students to study without risk.

Are there any financial aid for this course?

Currently we could not find a scholarship for the Programming Numerical Methods in Python course, but there is a $73 discount from the original price ($89.99). So the current price is just $16.99.

Who will teach this course? Can I trust Murad Elarbi?

Murad Elarbi has created 1 courses that got 662 reviews which are generally positive. Murad Elarbi has taught 3,590 students and received a 4.4 average review out of 662 reviews. Depending on the information available, we think that Murad Elarbi is an instructor that you can trust.
Mechanical Engineer, Lecturer
I am a Mechanical Engineering Lecturer in the University of Benghazi, Libya since 2005. I taught courses of Strength of Materials, Theory of Machines, Machine Design Projects and Engineering Drawing. My research interest is the computational mechanics where numerical methods and computer programming are the main tools of solution in addition to theories of mechanics. I instructed several computer language training courses of BASIC, Fortran, C++ and MATLAB. Currently, I am in the USA for the Ph.D. degree.
Browse all courses by on Classbaze.

8.7

Classbaze Grade®

7.2

Freshness

8.9

Popularity

9.5

Material

Platform: Udemy
Video: 12h 18m
Language: English
Next start: On Demand

Classbaze recommendations for you