返回到 Computers, Waves, Simulations: A Practical Introduction to Numerical Methods using Python

4.7

26 個評分

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9 個審閱

Interested in learning how to solve partial differential equations with numerical methods and how to turn them into python codes? This course provides you with a basic introduction how to apply methods like the finite-difference method, the pseudospectral method, the linear and spectral element method to the 1D (or 2D) scalar wave equation. The mathematical derivation of the computational algorithm is accompanied by python codes embedded in Jupyter notebooks. In a unique setup you can see how the mathematical equations are transformed to a computer code and the results visualized. The emphasis is on illustrating the fundamental mathematical ingredients of the various numerical methods (e.g., Taylor series, Fourier series, differentiation, function interpolation, numerical integration) and how they compare. You will be provided with strategies how to ensure your solutions are correct, for example benchmarking with analytical solutions or convergence tests. The mathematical aspects are complemented by a basic introduction to wave physics, discretization, meshes, parallel programming, computing models.
The course targets anyone who aims at developing or using numerical methods applied to partial differential equations and is seeking a practical introduction at a basic level. The methodologies discussed are widely used in natural sciences, engineering, as well as economics and other fields....

創建者 NL

•Mar 14, 2019

Well thought out. The material is ordered logically and easy to follow. This online course compliments the book from which it is based on.

創建者 YH

•Apr 09, 2019

This is a great course for intro to numerical course with additional bonus on python code, although a little bit too fast pace.

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9 個審閱

創建者 Niels Christian Nielsen

•Apr 13, 2019

Heiner Igel is an excellent teacher and he stops Just before the real complications begin as he should at this introduction level. The format of the course is such that Heiner Igel explains to the viewer while hand-written equations and drawings appear absolutely synchronized in the background. Then there are programming exercises where you can run simulations in Python (using Jupyter Notebooks). The programs are well-structured and easy to follow and manipulate to test out the theories. Super well prepared - it has clearly taken a very long time to put this course together. The explanations are detailed enough to get a good feel for the numerical methods and their implementations, but not such that everything is painstakingly derived mathematically. Overall a good introduction to numerical methods without too many complications, but you do get a feel for how complicated it could quickly become.

創建者 Yitao Hu

•Apr 09, 2019

This is a great course for intro to numerical course with additional bonus on python code, although a little bit too fast pace.

創建者 ANKUR WAGH

•Apr 09, 2019

GOOD

創建者 ASHISH CHHABRA

•Apr 09, 2019

Had a great time learning the concepts of numerical methods and how to apply them using python. This course gave an insight into many real world problems and how their solution can be approached using numerical techniques.

Thank you very much sir.

創建者 Andrey Marcos Souza da Silva de Lima

•Apr 07, 2019

It was the greatest course that I have taken online because it asks you the main ideas through the video, so I only needed to take feel notes on the calculations. I finished it in 9 days and I will definitely recommend to my friends from my former university.

創建者 Vivek Kumar Giri

•Apr 02, 2019

The course was highly enlightening. Go to learn a great deal from the course. Thanks to coursera !!

創建者 Souvik Mukherjee

•Mar 28, 2019

GREAT COURSE

創建者 Noah Luna

•Mar 14, 2019

Well thought out. The material is ordered logically and easy to follow. This online course compliments the book from which it is based on.

創建者 New Diogo

•Feb 25, 2019

I already know that I will learn a lot even though I am an undergrad. ( FTD from Colorado School of Mines)