Week 5 and 6 where harder to follow and the projects where more complicated to understand (even though it shows that effort were put into them)

Very systematic and detailed introduction. Good way to start off into the science of simulation and modelling.

Introduce many interesting topics. The Lattice Boltzmann Model is the most challenging one. Implementation examples are demonstrated all through the class and there are chances to experiment and execute the code. However, the projects are already half-finished. Although building the code from scratch is a bit hard, I still think it's a really crucial step.

It would be better if more challenging questions and topics are introduces and there should be more explanations on a more fundamental level. The homework is somewhat ambiguous in some weeks and guessing the REAL meaning of the problem was quite annoying.

Pretty good introduction to the various techniques in scientific modeling but could have been done better. Might be too difficult for people who do not have a solid background in vector calculus, algorithms, and programming. Yet if you already have such a background, you are probably already familiar with most of the material covered, as the models discussed in this course are all toy/classroom examples given during a typical undergrad treatment of these CS/Math topics.

There are a frustrating number of mistakes in the questions and sometimes in the lecture slides. I think the course gives a good grounding in the types of simulation required for different problems and I like the examples used. I'm not a huge fan of the style of lectures as it's incredibly different to learn from flicking through slides. Lectures where examples are worked through in a more interactive way (such as on white boards) are far more effective for teaching.

The topics covered in the course are extremely interesting and its a great place to get the fundamentals right. Special mention to the cell automata and the LB method. Although, I feel extra exercises would be needed to further deep the material. Overall, a great course if you are looking to learn fundamentals but exercising what is show is much dependent on your own imitative.

I believe this course has a great content. I had almost none background on this subject and I was able to go through the end and learn new things. I don't think it has as many errors in language as the other ratings make you think. But the course is abandoned. No interactions from the tutors.

The course is useful, but there're too many mistakes in the quiz and assignments

This is one of the best courses that I have ever seen. It's well organized and detailed. My major interest was to learn programming/Simulation but the course is beyond that.

Thanks to the Instructors who have gently introduced me to programming/simualtion world. Though, the course is challenging but the skills worth the challenge.

Thanks.

This is a very nice course: many model examples are given. However, they aren't explained in detail. I wish the authors created a Specialisation in this subjet where it would be possible to go in depth of different types of models. Mass-movement dynamic models could be of a particular interest then as well.

Difficult but manageable. I liked Python programming exercises. Material is very interesting and could not be taught in a single course, but one gets a flavor of the topics discussed. Thanks to all the instructors for their hard work.

Excellent course for people who love math, physics and simulations ! I choose it to get an insight on Lattice Boltzmann Method, I was happy to apply it and extend it to other cases.

A perfect course learning you exactly what you want step by step

very good。Every teacher 's classes are very clear.

I find this course very useful for me

Really great as an introduction.

It's a nice course,I like it.

GOOD

good

good

Very enjoyable course split up into lots of smaller modules. Video content from several tutors was very professional. There was a variety of worked examples to complete after each week of the course. Great opportunity to learn python programming language and apply your knowlege to some realistic applications. Some of the multiple choice questions were very tricky and take several attempts to get right. Some the the computing assignments required a specific number to be entered for the final answer. This was sometimes quite difficult because there was not much room for error. There is a forum which you can browse for each week of the course which was useful to obtain some tips for answering these questions. I particularly enjoyed learning about the Lattice Boltzmann method in week5. The demo python exercise for this was very interesting and useful too (flow over cylinder).

An excellent MOOC, thank you! The subject is of great interest and I loved the balance between practical Python exercises and theory. To further improve the MOOC, I suggest:

- Provide more complementary materials as conditional readings (e.g. good books and articles on the topic),

- Don't try to teach Python in 1 hour, rather make it a prerequisite for the MOOC instead and use that module to deepen the real subject: modeling,

- Review the coverage of ODEs and PDEs, the explanations provided are either too confused or high-level. What is the learning objective? Probably not to teach ODEs and PDEs in 1 hour, right?

- At the end of the MOOC, propose a tough modeling challenge. The last challenge is so childishly easy.

I would recommend this course for those who want to gain a non-trivial introductory insight into this subject and also who want to look into doing object oriented programming for simulations. The algorithms are clearly stated and codes are good. The annoying issues are the team is not very supportive (no intention to offend) and you need to look into discussion forum to get pass some quizzes for which the key is Wrong. Overall, nice course. I would probably study these codes on my own after completion

The content of the course is very extensive especially for someone with no prior background to modelling of natural processes. The build-up during the first 3 weeks moves at quite a reasonable pace. I would say that later weeks could be more informative when it comes to material and accessibility of example cases. Having said that the amount of example cases overall, for code implementation is very satisfying. All in all a course that gives you the ability to take back a lot if you invest time.

Good introduction to various techniques of modeling natural processes. Audio can be improved a bit as there are several places where it is not clear (audible) which gets further pronounced with instructors (they are great in their knowledge!) accent! Would welcome more examples, references and quick refresher/note on related math. A advanced (part 2) version with recent updated techniques (including using of ML) would be welcome as well.