The full title of the course was "Core and advanced environmental statistics training: Quantifying the environment – Part II" at the University of Glasgow. As a NERC funded student I could attend the course for free - thank you NERC!
It was a week long course, it was rather intense and it covered three areas: flexible regression methods,
spatio-temporal modelling and functional data analysis (FDA). I was
particularly interested in the spatial modelling as I might do a chapter
on it for my PhD.
The course was very much aimed at statisticians and quite a bit of previous knowledge was assumed. For instance, on one of the days we had a set of lectures which were a condensed version of a 20 h long course for people doing Masters in statistics. As I have no real background in stats I found a lot of it rather hard. Keep in mind that I haven't attended Part I, maybe things would have been easier if I did.
What I found a bit suprising is that a lot of things we were doing were "at the edge of statistical knowledge and research". For some reason I have expected the field of statistics to be more advanced. This might sound silly, I guess, but I just never thought deeper about where our statistical knowledge is at. Now I know! It seems that some things I was planning to do might be harder than I thought, yet the majority of them should be doable, which is great. There were a couple of things that are not-so-doable yet, mainly due to lack of packages available - the knowledge is there, but there is no easy way to utilise it by an average non-statistician.
Yet despite the fact that the stats were hard, I found the course really informative. I think this was due to a clever delivery strategy. The lectures were clear and accompanies by practical sessions. All the R scripts for the practicals were provided. This way I could work through the material and focus on trying to understand it, instead of fighting with R. I think if I had to come up with R scripts by myself I would have been completely lost. Additionally, I have all the scripts for future reference and I can be sure that the code is decent and without errors.
All in all I'd recommend the course, but be prepared for a long week and quite a bit of work!