Note: This material is a little outdated, see michael-herbst.com/learn-julia for my most recent workshop.
This introductory course into Julia is presented in the form of Jupyter notebooks, which discuss the key concepts of the language from the angle of performing molecular simulations or linear algebra operations. It also provides an overview of existing packages and projects based on Julia.
This material was originally prepared for the Julia day at Sorbonne Université on 13.12.2019 (details), but was also presented at 36c3 in Leipzig.
Using the tutorial online
If you don't want to install Julia just yet, just run the tutorial on binder, which allows you to work with the material directly from your browser.
Installing Jupyter and IJulia
For working with the material you need a working IJulia setup, this means you need to install Jupyter and integrate it with Julia. Roughly this boils down to:
- Install Jupyter notebook. For Linux choose your favourite package manager, like
apt install jupyter jupyter-notebook
for debian or
pip install jupyter
if you prefer PyPi packages. For Mac use
brew install jupyterlab.
IJuliainside Julia. For this run
/path/to/juliafolder/bin/julia -e 'import Pkg; Pkg.add("IJulia")'
in your terminal, where
/path/to/juliafolder is the path
into which you unpacked the
Getting the files and starting the notebooks
For getting the course files to your computer, the simplest is to use git:
git clone https://github.com/mfherbst/course_julia_day
After the command is finished you can start the notebooks as usual:
cd course_julia_day jupyter notebook .