Programming Numerical Methods in Python (Udemy.com)

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.

This was a good introduction into a massive subject. The instructor's work was great, and thanks to his efforts, the course was amazing and very enjoyable. an area of improvement or advancement (in a second course maybe) is to focus on numerical methods but in a way that goes deep into the numpy and scipy functions from their references directly, like going with the logic of "teach me how to fish is better than having the fish caught already", also diving into PDE's and more complicated systems that represent real life applications such as the infamous heat equation, etc. all in all, very amazing and advisable course for beginners in numerical methods like myself.

It's an interesting course but I can't give 5 stars because: - If I remember well, in Roots of High-Degree Equations you didn't mention what could happen if in the interval we choose there are more than one root (in some cases, like bisection, if in the interval there is an even number of roots, we could think there's no root. In other cases, it could give us one of the roots, ignoring the others, or even never converge).... - In the examples for Gauss elimination on Systems of Linear Equations, you showed that, to avoid a 0 on the diagonal, we must flip two rows... ¿but what if even doing that we find always again a 0 on the diagonal? (If I remember well, you didn't say that perhaps we need to find another different method). - There was a mistake in one of the examples in the videos (It was corrected on the resources .py file, indicated with #corrected) - Too slow. I did the course at 1.75 and sometimes at 2 speed. So, all in all, it's a good course, thanks. I liked it, but sorry, not as good as 5 stars.

It is a quite helpful course for me. I have learned a lot from this course. And also, the python codes which are practiced here were amiable to me. But some practice problems should be given for us to solve for more interactive learning otherwise it is overall a great experience for me to complete the course. Thank you.

I think it is a complete course to start learning about numerical methods. But I think it can be improved by adding challenges for every section. The last section can be also expanded. Or maybe create another course about numerical methods to solve PDEs.

This is an interesting crash-course on different numerical methods solved both in plain Python and with Numpy/Scipy. The short code snippets give a good starting point to use it in own programs or to search for advanced material where needed. The beginning was a bit lengthy as no prior programming knowledge was assumed. I would have liked more information about limitations of the methods or speed considerations, but I guess I'm not exactly the target audience :)

I enjoyed the course very much, it was easy to follow and I learned a lot about Python and numerical methods, just as advertised in the title

I'm new to python, but was previously a math major so I find the combination helpful in exposing me to the world of python. Great course so far!

Very few things are explained carefully before being used....

I have learned a lot from this course and the examples were also very helpful.

This was an interesting learning. I could learn the methods quickly, especially the Numpy, Scipy solver. Thank you Murad Elarbi and Udemy.

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