Many of the assignments in our course will be implemented in Julia, using packages, such as JuMP, Plots, among many others. Julia combines simplicity and remarkable performance, which is one of the reasons it has become the language of choice for many optimisation applications. The main website for downloading is http://www.julialang.org. This is also the main place for finding the information you might need.
Aalto Scientific Computing has previously offered an introductory course in Julia. Here is a link to the course and its materials: https://scicomp.aalto.fi/training/julia/julia-introduction/
There are a few options to use Julia during this course.
- The first option which is probably the easiest and recommended one is to use Aalto JupyterHub with the Julia 1.6.2 kernel. The platform may be accessed from here https://jupyter.cs.aalto.fi. Following this link, you will be able to log to with your personal Aalto account and choose the Julia environment (Julia: General use (JupyterLab)) on the next page. In this case, all the necessary packages are preinstalled.
- The second option is to install Julia on your personal computer. We recommend this option for those that feel confident about handling the installation themselves. In this case, the recommended version of Julia 1.6.2 with the most recent versions of the packages. By following this option, you will also have to manually install all the packages that will be required during the course.
For the coding interface (IDE), I recommend using Jupyter notebooks (you can open them in Julia by using the IJulia package). If you would like something more "advanced" then VS Code is the way to go.
Below you can find some helpful links. The first one has all the information you need for this course.
- Tutorial 1 (Julia Academy - great starting point): https://juliaacademy.com/p/intro-to-julia
- Tutorial 2 (youtube, very much like the above but in a single video):
- Aalto JupyterHub info: https://scicomp.aalto.fi/aalto/jupyterhub.html