Julia workshop for Data Science

This repository contains the notes of the Julia workshop taught at CIMAT in October 26-27, 2020.

In preparation for the course

• Bring a small dataset that you can analyze in class (preferably LMM-related, but not exclusively)
• Bring an R (or python) script with the code that you would normally use to analyze the dataset
• Read the syllabus below and checkout the resources in the "In preparation" column
• Download julia in your computer
• Clone this repo:

git clone https://github.com/crsl4/julia-workshop.git

http://mcd.eventos.cimat.mx/node/1534

Facebook live

* [Facebook live](https://www.facebook.com/groups/1118217978549782)

Syllabus

Day 1

Session	Topics	In preparation	At the end of the session
1:00-1:10 pm	Introduction	Clone and browse the github repo	You will know the plan for the workshop
1:10-1:30 pm	Why Julia?	Browse the main Julia page and read news1 and news2	You will be motivated to learn Julia
1:30-2:15 pm	Getting started in Julia	Read the basics of Julia here	You will have everything setup to do data science in Julia
2:15-2:25 pm	Coffee Break
2:25-2:30 pm	Questions check-in
2:30-3:15 pm	Introduction to MixedModels.jl	Browse the MixedModels docs and if possible, install VSCode with Julia extension	You will know the main functions to run LMM in Julia
3:15-3:30 pm	Final comments/remarks

Day 2

Session	Topics	In preparation	At the end of the session
1:00-1:30 pm	General tips for FAQ	Review the material from Day 1	You will have a list of Julia resources to check out
1:30-2:30 pm	Breakout groups to work in data analyses in Julia	Bring your data and R/python script	You will have your own Julia code for data analysis
2:30-2:45 pm	Presentation of some examples
2:45-3:00 pm	Final comments/remarks and exit feedback survey

Want to learn more?

Checkout the great resources in Julia learning.