I haven't tried with students, but I tried to get Jupyter setup on a Macbook for a researcher who was very keen on using it (he is a strong advocate of R) and after an hour or two we sort of gave up. We struggled with online documentation that was often inconsistent, incorrect, or incomplete. We found several installation tutorials online and we couldn't any of them to work. He later went back to it and eventually got it working, but no thanks to me. Sorry I cannot give a detailed report. This was half a year ago and I don't remember the details.
I had forgotten about JuliaBox. Now that you mention it, that should be a very good option. As for jupyterhub, I honestly had not heard of it until you mentioned it just now. The website says that it's a multi-user server. I definitely don't want to go down that route. I wouldn't want to be responsible for running a server where students are supposed to do their work. But I think JuliaBox is probably a good option. I guess my thoughts of Jupyter were tainted by the experience with the Macbook and R. Cheers, Daniel. On 15 April 2016 at 17:39, Cedric St-Jean <cedric.stj...@gmail.com> wrote: > > > On Friday, April 15, 2016 at 9:12:21 AM UTC-4, Daniel Carrera wrote: >> >> Cool stuff! >> >> From my point of view, the biggest obstacle is that Jupyter is not easy >> to install for most people, >> > > I'm surprised to read that. Any issue in particular? Between Anaconda, > jupyterhub and JuliaBox, there's a lot of possibilities out there. How are > your students set up? > > >> and PyPlot doesn't have much documentation. I keep telling myself that >> I'll add documentation for PyPlot but somehow I never seem to find the time. >> >> Cheers, >> Daniel. >> >> >> On Friday, 15 April 2016 04:17:40 UTC+2, Sheehan Olver wrote: >>> >>> >>> >>> I'm currently lecturing the course MATH3076/3976 Mathematical Computing >>> at U. Sydney in Julia, and thought that others may be interested in the >>> resources I've provided: >>> >>> http://www.maths.usyd.edu.au/u/olver/teaching/MATH3976/ >>> >>> The lecture notes and labs are all Jupyter notebooks. I've also >>> included a "cheat sheet" of Julia commands used in the course >>> >>> >>> http://nbviewer.jupyter.org/url/www.maths.usyd.edu.au/u/olver/teaching/MATH3976/cheatsheet.ipynb >>> >>> The course is ongoing (it's about half through) and will continue to >>> take shape, but any feedback is of course welcome! >>> >>> >>> Sheehan Olver >>> >>
