Introduction to Julia

Introduction to Julia course at Imperial College

3 × 2 hour classes

Part 1: Getting started, Functions, Conditionals, Data Structures
Part 2: Packages, Plotting, Types, Multiple Dispatch
Part 3: Benchmarking Julia, Linear Algebra, AutoDifferentiation

Tutors :

Jay DesLauriers

Past Tutors :

Yiannis Simillides
Evripides Georgiades

Acknowledgements :

The course materials come from Julia Academy lessons, and are being adapted for teaching at the Graduate School.

On completion of this workshop you will be able to:

Use Jupyter Notebooks to execute Julia scripts and install packages.
Apply fundamental components of the Julia language including variables, loops, conditionals and functions.
Create programs designed to solve simple problems.
Interpret common errors and use these to help debug a program.
Understand advanced concepts, such as Multiple Dispatch and custom data types.

There will also be an opportunity to explore domain specific packages used for:

Data Frames
Basic Linear Algebra
Factorisations and SVD
Ordinary differential equations

Prerequisites

No programming experience is required
Binder runtime will be provided
Feel free to install Julia using the instructions below

Useful (Julia) Links

Feedback

This is the third time this course is running, so please feel free to let us know if anything needs changing / any feedback / difficulties or if there is anything that you particularly enjoyed!

Preparing Your Environment

In this course we'll be using the latest and greatest Julia v1.8.5 via a Jupyter Notebook. This section will help you get set up with Julia.

The fastest way to get started with the course material is with Binder.

Binder

Binder is a cloud based platform for reproducible programming environments. It is a free service, so don't expect the same performance as RCS, or even your local device. However, it is a great solution for quickly getting started with Julia! Simply click the icon below depending on the day of the course.

Day 1:

Day 2:

Day 3:

Be aware that load times may vary and timeout. Please try again in case of failure

All days in one binder (may be very slow)

Julia Elsewhere

If you are keen on using Julia more regularly, we have outline various options below.

Imperial College RCS

The Research Computing Service runs JupyterHub. If you have access to RCS, this can be a great way to run Julia easily, with some power behind it. Navigate to jupyter.rcs.imperial.ac.uk and select a resource to get started. **For this course, the smallest resource is sufficient (1 core / 8GB RAM).

An old version of Julia is provided, so it is best to install the latest version. RCS provides instructions here (be sure to change the version numbers to 1.8 / 1.8.5). We have adapted and copied the steps below for convenience.

Via the Jupyter Launcher or File menu open a Terminal.

Download, extract and run Julia

curl https://julialang-s3.julialang.org/bin/linux/x64/1.8/julia-1.8.5-linux-x86_64.tar.gz | tar xz
julia-1.8.5/bin/julia

Install the IJulia kernel

using Pkg
Pkg.add("IJulia")

Download the course materials

curl -L https://github.com/imperialcollegelondon/rcds-introduction-to-julia/tarball/day1 | tar xz

Next time you create a new Notebook, you should see Julia 1.8.5 as an available Kernel.

Julia Locally

First, download the appropriate installer for your system here, and run it to install Julia (if prompted, we recommend to Add Julia to PATH).

Now run Julia. On Windows machines you can find Julia in the start bar. On a Mac, you might need to open Terminal and type julia.

Next we'll intall IJulia so we can access Julia via Jupyter.

using Pkg
Pkg.add("IJulia")

If you already have a Jupyter environment, open it and you should see Julia 1.8.5 as an available Kernel! Otherwise, read on.

Jupyter

We recommend Anaconda for a quick and easy Jupyter interface. It is available via the Software Hub.

Or you can download it locally from the official website

Once installed and running, you can open a new Jupyter Notebook backed by Julia 1.8.5.

Note with the Software Hub Anaconda on the Training Room computers, after ignore the application that starts, and instead search and run Jupyter Notebook (Anaconda 3)

Notebook Downloads

If you are working locally, download the notebooks used each day below!