Julia Workshop for Data Science

ISMB 2022, Madison

Author

Claudia Solis-Lemus and Douglas Bates

Published

2022-07-30

Welcome

  • Welcome to the Julia workshop for Data Science!
  • The goal for the workshop is to highlight the main features that make Julia an attractive option for data science programmers
  • The workshop is intended for any data scientist with experience in R and/or python who is interested in learning the attractive features of Julia for Data Science. No knowledge of Julia is required.
  • Workshop materials in the github repository julia-workshop

Learning Objectives for Tutorial

At the end of the tutorial, 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
  • Fit (generalized) linear mixed models with MixedModels.jl
  • Communicate across languages (Julia, R, python)

Intended audience and level: The tutorial is intended for any data scientist with experience in R and/or python who is interested in learning the attractive features of Julia for Data Science. No knowledge of Julia is required.

Schedule

Time Topic Presenter
11:00 - 11:30 Session 1: Get Started with Julia Claudia Solis-Lemus
11:30 - 12:30 Session 2a: Data Tables and Arrow files Douglas Bates
12:30 - 1:00 Session 2b: Interval Overlap Douglas Bates
1:00 - 2:00 Lunch break
2:00 - 2:30 Session 3a: Linear Mixed-effects Models Douglas Bates
2:20 - 3:00 Session 3b: Generalized Linear Mixed Models Douglas Bates
3:00 - 4:00 Session 4: Hands-on exercise Sam Ozminkowski and Bella Wu
4:00 - 4:15 Coffee break
4:15 - 5:00 Presentation of selected participants’ scripts and Q&A
5:00 - 5:30 Session 5: Other important Data Science tools Claudia Solis-Lemus
5:30 - 6:00 Session 6: Conclusions and questions Claudia Solis-Lemus

In preparation for the workshop

Participants are required to follow the next steps before the day of the workshop:

  1. Git clone the workshop repository: git clone https://github.com/crsl4/julia-workshop.git

  2. Install Julia. The recommended option is to use JuliaUp:

  • Windows: winget install julia -s msstore

  • Mac and Linux: curl -fsSL https://install.julialang.org | sh

  • Homebrew users: brew install juliaup

After JuliaUp is installed, you can install different Julia versions with:

juliaup add release  ## installs release version
juliaup add rc       ## installs release candidate version
juliaup st           ## status of julia versions installed
juliaup default rc   ## make release candidate version the default
  1. Choose a dataset along with a script to analyze it written in another language (R or python) as we will spend part of the workshop translating participants’ scripts to Julia.