Topic outline

  • Julia

    In our course, we will refer to several examples implemented in Julia, using packages such as JuMP, Plots, among many others. Julia is a modern language that combines simplicity and remarkable performance. The main website for downloading the language is http://www.julialang.org. This is also the main place for finding the information you might need. 

    There are a few options to use Julia during this course (with no order of preference!).

    1. The first option is to use Aalto JupyterHub with Julia. The platform can be accessed from https://jupyter.cs.aalto.fi. Following this link, you will be able to log on with your personal Aalto account credentials and choose the Julia environment (Julia: General use (JupyterLab)) on the next page. In this case, all the necessary packages are preinstalled. This is a better option if you are not familiar with installing/ utilising open-source programming languages.   
    2. The second option is to install Julia on your personal device. The recommended version of Julia is 1.7.0 (or superior) with the most recent packages. You can find instructions on how to install it at http://www.julialang.org. This is a better option if you are familiar with installing/ utilising an open-source programming language (such as Python). We use Jupyter notebooks for exercises, and you will need to start by installing the IJulia package after you have installed Julia. For instructions on how to use the Julia package manager, see the documentation. After that, you will need to install the packages you need. 


    Resources

    We will show the basics of installing and using packages in the exercise session, but you will need to learn by yourself how to use the language for the purposes of the course. Below you can find some helpful links for self-studying. Please let us know if you find others worth including.

    • Aalto Scientific Computing Julia course (check for ongoing editions):
     
    • Julia Intro Tutorial (YouTube):
       


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