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学生对 路德维希马克西米利安慕尼黑大学 提供的 Computers, Waves, Simulations: A Practical Introduction to Numerical Methods using Python 的评价和反馈

279 个评分
107 条评论


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....


Dec 20, 2021

Would have like more "empty" cells in notebooks for trying to establish loop one self and then having a "correct" output to aim for. Maybe followed by a solution cell with a correct implementation.

Nov 26, 2019

A fascinating teaching technique, delivering quality content with a well-thought quizzes system! It' hard to find better courses in the domain of Finite Difference and Spectral Element methods


101 - Computers, Waves, Simulations: A Practical Introduction to Numerical Methods using Python 的 106 个评论(共 106 个)

创建者 Saul M

Apr 27, 2021

Great, learner-friendly introduction to the subject

创建者 Vanesa M R

Nov 10, 2021


创建者 Amine O

Mar 15, 2021

some parts of the courses should be broken down into smaller steps or at least add links to a pdf document where the demonstration /solution is broken down into easy-to-follow steps. so videos had mistakes that were corrected after they were played, I found this distracting, you could just redo the video or edit it on the spot rather than later.

I liked the tone and clarity of Heiner explanations, I loved the visual interpretations of the mathematical concepts. I can see that there was much more knowledge he could deliver which was outside of the scope of this course. and I think he should, the beauty of online courses is that it could branches to as much fundamental concepts as the leaner is willing to take.

创建者 Hasan M

Nov 30, 2021

Good Introduction to some of the more popular numerical methods used in Computational Science and Engineering. It shouldn't have "Practical" in the title because these are 1-D toy problems and you don't get involved in coding yourself although you are free to change and play around with his code. It doesn't build your intuition of how to implement Numerical Methods in computer programs efficiently. This course is good for those looking for an Introduction to the Numerical Methods listed: FD, FEM, Pseudo-Spectral, Spectral-Element Method. It is not suitable for those who want to learn how to program AS WELL.

创建者 Martin F J

Jan 10, 2021

There should be some PDF notes of the equations, you cannot expect people to memorize and learn all the quiz topics. With PDF notes I would have given 2-3 stars more, sorry, but that's how it is. As an engineer with some background in the field and some training, I however completed. But this is what you need to do, if you want better satisfaction, sorry.


Feb 1, 2021

The course could have been extended for longer duration so that the topics could have been explored in detail, specifically the math behind the Spectral element method. Further, having no coding background makes it really hard to implement the math into codes. Hence, the coding part also requires extended focus.