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https://github.com/dpsanders/learnjulia2020


https://github.com/dpsanders/learnjulia2020

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# Learn Julia via epidemic modelling

## Workshop at JuliaCon 2020

These are materials for the live workshop "Learn Julia via epidemic modelling" at JuliaCon 2020,
which will take place on Friday 24 July, 2020 online.
For access, please register for a free ticket at https://juliacon.org/2020

The versions of the notebooks in the top directory have no output.
The versions in the [`live`](live) subdirectory are the live versions produced during the workshop, with
solutions to some of the exercises.

I strongly suggest trying to solve the exercises before looking at the solutions!

## Setup

- Install the latest release (1.4.2) of Julia from [here](https://julialang.org/downloads/)

- Run Julia. At the Julia prompt, add the packages we will need as follows (copy and paste):

```julia
julia> using Pkg

julia> Pkg.add("IJulia")
julia> Pkg.add("Plots")
julia> Pkg.add("Interact")
```

- Once those packages have finished installing (which will install a collection of other packages that these depend on), type

```julia
julia> using IJulia
julia> notebook()
```

This should launch the [Jupyter notebook](https://jupyter.org) in your browser; this is a web application that provides a computational notegbook interface.

- Copy the notebook files (ending in `.ipynb`) from this repository to your computer by `git clone`-ing the repository or downloading the Zip file
(hit the green button which says `Code`).

- Navigate inside the file browser in the Jupyter notebook to the place on your computer where the files you just downloaded are. Load notebook number 1!

## Installation problems

- If you have installation problems you can also view the notebooks online at [nbviewer](https://nbviewer.jupyter.org/github/dpsanders/LearnJulia2020/tree/master) and use e.g. the online service [repl.it](https://repl.it) to write Julia code.

- If you are on the live call, you can try to describe your problem and ask for help via the chat; hopefully other attendees will be able to assist.

## MIT course 6.S083

For a more detailed, slower look at this and additional material, with much more discussion about mathematical modelling,
you may be interested in [MIT course 6.S083 from spring 2020](https://github.com/mitmath/6S083/blob/master/syllabus.md).
Videos are available on the [JuliaLang YouTube channel](https://www.youtube.com/c/TheJuliaLanguage/videos).

## License

Code in this repository is licensed under the MIT license, and text under the [CC BY-NC 4.0](https://creativecommons.org/licenses/by-nc/4.0) license. Copyright David P. Sanders 2020

## Author

David P. Sanders, Department of Physics, Faculty of Sciences, Universidad Nacional Autónoma de México (National University of Mexico, UNAM) & Department of Mathematics, MIT.