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  Date/Time Pre-reading Synchronous Session Leader(s)
Week 1 Jan 29, 5-7 Install VS Code and attempt remaining installations Kickoff Event Lisa
Week 1 Jan 30, 10-12:30 Please review the pre-reading materials on the Command Line Curriculum page: https://curriculum.dhinstitutes.org/workshops/command-line/ Command Line Stefano, Olivia
Week 2 Feb 6, 10-12:30 Please review the pre-reading materials on Data Literacies. During our workshop we will be focusing on discussing the questions, challenges, and materials together to share our perspectives and experiences with each other: https://curriculum.dhinstitutes.org/workshops/data-literacies/ Data Literacies Di, Olivia
Week 3 (Python Track) Feb 13, 10-12:30 Please review the pre-reading materials on the Python curriculum page, and check out one or two sample projects linked on that page: https://curriculum.dhinstitutes.org/workshops/python/ Python Filipa, Rafa
Week 3 (R Track) Feb 13, 10-12:30 R Programing for Data Science is a useful handbook that can get you from a novice to an adept.
I recommend you read Chap 2 to get a basic understanding of R for now.
R Yuxiao, Connor
Week 4 (Python Track) Feb 20, 10-12:30 Please review the pre-reading materials on Text Analysis, in particular about using Jupyter-Notebooks: https://curriculum.dhinstitutes.org/workshops/text-analysis/ Text Analysis Rafa, Filipa
Week 4 (R Track) Feb 20, 10-12:30 This is a succinct summary of the main reasons for using R for your data analysis needs:
https://www.dataquest.io/blog/three-mighty-good-reasons-to-learn-r-for-data-science/
This is the explanation of the style of creating graphics in the R package ggplot2:
http://vita.had.co.nz/papers/layered-grammar.pdf
I recommend skimming it beforehand (especially sections 1-3) and using it as a reference once you start making your own plots.
Data Wrangling Connor, Yuxiao
Week 5 Feb 27, 10-12:30 More information forthcoming Project Planning Lisa