This contains some very interesting and challenging exercises related to "Global Warming I", which are fun to work on. It contains no real instructions about python, and I think it would be better to at least have some guidance there. However, the course info is at least totally up-front with that information.

Although this course is related to "Global Warming II", it is not correlated with it. It would be a mistake to take them concurrently, since GW-II moves much faster, and is a much shorter course. This was not clear to me when I signed up, and it should be made clear to students at the beginning.

I like Prof. Archer a lot, he seems like a good teacher. However, aside from brief introductory lectures (and the selection of great topics for simulation) he plays a rather small role in the course. The student is pretty much on his own. There is no TA or anyone monitoring Discussion questions. There are some places where the "Model Description" notes are incorrect and badly misleading (notably in Week 4). I pointed this out, with others, in the "Discussion Forum", but we got no response and there was no correction. There are other places where information is unclear, but there is no one to turn to for clarification.

Course Description: "This class assumes that you are new to Python programming (and this is indeed a great way to learn Python!), but that you will be able to pick up an elementary knowledge of Python syntax from another class or from on-line tutorials."

The week 3 assignment definitely did not feel like it was aimed at Python newbies like me. Minimal help with coding, I reluctantly have to quit...

The course was an interesting way to explore writing models to explore climate change. The way the assignments are written was sometimes confusing.

A very nice course! Thanks to the author(s)! I only find formulation of the problem a bit difficult to follow. At first we see a video of the code commented by the professor, but at that moment we know only vaguely what are the knowns and what the unknowns , so its a bit confusing. I think it would be nice to explicit that somehow and make formulation more fluent. Another thing, for some problems professor says that for Python is computationally hard to handle calculations with a big number of unit cells for example (if I understood well). What is hard for Python of course is to plot a lot of things in real time, for each step. If we plot only some number of iterations, or export results on another way its completely fine for python to do much more complex stuff. I'm sure professor knows this, but for new learners of Python its confusing what he says.

Nice opportunities for python coding of complex projects, which is wonderful. However, some of the specifications are rather unclear and it can be very hard to figure out why our code does not match the automatic grader's expectations! Also, the peer-marking system means that late comers might have to defer the end of their course indefinitely as they might not be able to get any other student to mark their work. This is a big flaw in the system. Not at all happy with that as it left a bitter taste at the end of a long waiting process to validate all my hard work.

Too few participants, cancelling my course

I had to wait three weeks to get my peer reviews (week 1). Thank you to the reviewers. But it's obvious to me that there are simply too few course participants to go forward with a reasonable pace. Cancelling this course. Wishing patience and success to all participants.

A great introduction to using python for numerical calculations and graph plotting. Level of course is pitched perfectly for someone with experience of computer programming but new to learning python. The course material is structured very well: the course writer clearly put in a lot of effort to create really interesting exercises which made learning python very engaging. There was a nice mix between the early weeks of the course which offered approachable exercises and later weeks which provided more challenging but very rewarding ones.

Really good course. Short, content-filled lectures and practical application!

Very good content, learned a lot, notably in Python. Practical.

Like others mentioned, it's a pity that the forums are no longer monitored (at least it was the case when I followed), because the instructions are sometimes hard to understand, even with the best effort to explain from the Professor. But don't let that discourage you - it's a great course where you can learn about basic climate process by DOING!

Really interesting and a good way to learn Python even if we don't have any experience with programming. Grecommended!

Great course for those who want to learn a little more about modelling, python and the climate!

I would love some more excercises, more modeling concepts. A great experience after all!

A challenging course that gives a basic insight to the world of climate modelling

Great class!

Great course, really interesting! The difficulty of the course didn't follow a linear growth, as week 4 was much more difficult than the others.

too few people in the course you can't learn anything if you don't get it immediately