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

Date	Topic
Sept 26	Introduction to Julia
Oct 3	Generalized Linear Mixed Models in Julia
Oct 10
Oct 17
Oct 24

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.