Skip to content

Latest commit

 

History

History
104 lines (70 loc) · 5.17 KB

README.md

File metadata and controls

104 lines (70 loc) · 5.17 KB
Raw

Introduction to Julia

This repository contains the content for the Introduction to Julia course at CSC.

Julia is a new emerging high-level, high-performance programming language. It aims to be simple to write and fast to run. In this course, we will introduce the basic concepts of programming with Julia. We will also discuss selected Julia packages and give an introduction to the Julia ecosystem. The course contains both lectures and hands-on exercises. All the material is provided as interactive notebooks.

The course is aimed for everybody with beginner to intermediate level of skills in programming. However, the notebooks and exercises also contain extra material marked with Advanced tags that are aimed for the more experienced users. Don't feel overwhelmed by them, some of them can be very specific to some particular field of science. Instead, if you find some of them interesting, feel free to just mess around with them and have some fun. That is the whole point of programming with a high-level language anyway!

Prerequisites

Participants are expected to have some experience in computer programming and to be familiar with the basic concepts (e.g. variables, statements, control structures, functions) but previous knowledge of Julia is not required.

Timetable

Monday Tuesday
09:00 45min Intro Development practices
09:45 45min Exercises Exercises
10:30 15min Coffee break Coffee break
10:45 30min Control flow Julia ecosystem
11:15 60min Exercises Exercises
12:15 60min Lunch Lunch
13:15 30min Functions Performance tips
13:45 45min Exercises Exercises
14:30 15min Coffee break Coffee break
14:45 30min IO Julia ecosystem II
15:15 60min Exercises End of course
16:15 End of day

Lecture material usage

Lecture material can be read directly from GitHub using your browser. Just click yourself inside the notebooks directory. However, for best experience, you should open the notebooks in the notebook environment. Installation of Jupyter notebooks and IJulia for this is described below.

For a quick introduction to the Jupyter notebook environment, see the 00_notebooks.ipynb.

Installation of Julia

CSC notebook environment

In the course we use the CSC notebook environment.

Once logged in, go to "Account" and "Join Group" by using the code provided to you.

After joining the group, you should see "Introduction to Julia" in the Dashboard.

All the hands-on exercises can be done in the cloud environment using the workstations in the training class (or using own laptop if you prefer so).

Quick start: using Julia on juliabox

The simplest way to use Julia is to go to juliabox.com. Once you log in (e.g. with a gmail account), you can run Julia code online (on Amazon Cloud servers) via the browser-based Jupyter notebook interface without installing anything on your computer.

Although you wouldn't want to run large computations on juliabox, it should be fine for simple homework problems.

To add our lecture material, click the Git button on the top left in the menu bar. Then insert the course material url

https://github.com/csc-training/julia-introduction.git

and type master for the branch. Folder name can be whatever you like, for example julia-csc.

Caveat: Packages can not be installed using the Julia package manager. You must install external packages by clicking the Packages button on the top menu. After that, just type the name of the package and hit install.

Installing Julia and IJulia

If you use Julia enough, you'll eventually want to install it on your own computer. Your code will run faster and won't require a network connection, but can still use the same browser-based notebook interface.

First, download the current release of Julia and run the installer. Then open the Julia application (double-click on it); a window with a julia> prompt will appear. At the prompt, type:

using Pkg
Pkg.add("IJulia")

You may also want to install these packages, which we tend to use in a lot of the lecture materials

Pkg.add("Plots")
Pkg.add("PlotlyJS")
Pkg.add("PyPlot")

Then you can launch the notebook in your browser by running

using IJulia
notebook()

References

Much of this material is based on different excellent content found around the web such as:

General topics

Parallelism: