Welcome to the Julia bootcamp
This repository contains the material for the “Julia bootcamp” at the Stat. Dept., UW-Madison, Fall, 2024 semester
- The goal for the bootcamp is to highlight the main features that make Julia an attractive option for data science programmers
- The workshop is intended for statistics/data science students with experience in R and/or Python who are interested in learning the attractive features of Julia for Data Science. No knowledge of Julia is required.
- Workshop materials in the github repository julia-bootcamp
Learning objectives for this bootcamp
At the end of the bootcamp, participants will be able to:
- Identify the main features that make Julia an attractive language for Data Science
- Set up a Julia environment to run their data analysis
- Efficiently handle datasets (even across different languages) through Tables.jl and Arrow.jl
- Communicate across languages (Julia, R, Python)
Schedule
In preparation for the bootcamp
Review the first part (Writing) of Modern Julia Workflows, abbreviated MoJuWo, which provides a general introduction to setting up a Julia development environment.
- That first part of MoJuWo mentions the VS Code editor; we suggest using Positron instead. It is the same editor but customized by Posit PBC for data scientists. Install Positron or VS Code.
- Install Julia using
juliaup, as described in section 2 of MoJuWo - Writing
- We will use Quarto, also from Posit PBC, for preparing slides and documents. Install quarto.
- Install the Julia extension in VS Code or Positron. The Quarto extension is pre-installed in Positron.
- Git clone the bootcamp repository:
git clone https://github.com/crsl4/julia-bootcamp.git
- Your cloned repository contains a file
Project.toml, which is described in section 7 of MoJuWo - Writing. Use “package mode” in the REPL to activate and update the environment.