This repository contains the notes of the Julia workshop taught at CIMAT in October 26-27, 2020.
- 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| 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 |
| 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 |
Checkout the great resources in Julia learning.