Content from many excellent resources went into the course. Let me point you to (and thank) the following addresses:
- https://julialang.org/blog/2017/01/moredots
- https://julialang.org/blog/2019/03/debuggers
- https://julialang.org/blog/2017/03/piday
- http://www.stochasticlifestyle.com/7-julia-gotchas-handle/
- http://www.stochasticlifestyle.com/comparison-differential-equation-solver-suites-matlab-r-julia-python-c-fortran/
- https://medium.com/@Jernfrost/defining-custom-units-in-julia-and-python-513c34a4c971
- https://github.com/MikeInnes/diff-zoo
- https://github.com/FugroRoames/RoamesNotebooks
- https://github.com/StefanKarpinski/MeetupDemos
- https://nbviewer.jupyter.org/gist/StefanKarpinski/b8fe9dbb36c1427b9f22
- https://github.com/mitmath/1806
- https://github.com/mitmath/18S096
- http://ucidatascienceinitiative.github.io/IntroToJulia/
- https://github.com/dpsanders/hands_on_julia
- https://julialang.org/learning/
- https://www.youtube.com/watch?v=vAp6nUMrKYg
- https://github.com/mfalt/juliacourse
- https://www.youtube.com/watch?v=S6Wx_J4Mk7U
- https://web.mit.edu/18.06/www/Fall17/1806/julia/Julia-intro.pdf
- https://github.com/mitmath/18S096/blob/master/lectures/lecture7/Metaprogramming.ipynb
- https://github.com/kshyatt/juliacon2017/blob/master/Workshop%20Part%202%20-%20Quantum%20Complications.ipynb
- https://book.sciml.ai/notes/02/
- https://juliafolds.github.io/data-parallelism/tutorials/quick-introduction/
- https://blogs.fau.de/hager/archives/8263
- https://github.com/maleadt/cscs_gpu_course/
Note: Unfortunately I don't remember all of the resources 😔. If you feel that you should be mentioned above, don't hesitate to contact me and I'll gladly add you to the list!