There is a collaborative effort underway to translate to Julia the Python and Matlab code that accompanies Stanley H. Chan’s textbook Introduction to Probability for Data Science. This effort is authorized by Dr. Chan. The textbook is free to download as a pdf. Please see the page Introduction to Probability for Data Science for more information about the book.
My opinion is that this is a very nice probability and statistics textbook for undergraduate students of data science, and that it has the potential to be very widely used.
The code to be translated is quite basic (for the most part). This is an opportunity to participate in helping to make Julia visible to many people, even if your experience with Julia programming is not that great.
The code to be translated is in the Code and Data section of the web page mentioned above, at the bottom left.
If you are interested in translating the code for a chapter, please say so here, and I will edit this top message to keep track of who is working on which chapter. Please sign up only if you can get the work done in a couple of weeks, at the most.
Please make pull requests for completed work to GitHub - mcreel/IntProbDS.jl: Julia code to accompany https://probability4datascience.com/index.html
Regarding style, I suggest to follow the style used in the Julia code for Ch. 1, and the style of the Python and Matlab code: self contained blocks that can be pasted into the REPL, and which will run independently of other blocks.
Ch. 1: completed - mcreel
Ch. 2: no code for Ch. 2
Ch. 3: completed - vinicius_de_lima
Ch. 4: completed - rafaelchp
Ch. 5: completed - Elias Carvalho
Ch. 6: completed - j_verzani
Ch. 7: completed . Paul_Soderlind
Ch. 8: completed - mcreel
Ch. 9: completed - mcreel
Ch. 10: congUoM