https://github.com/esciencecenter-digital-skills/awesome

Awesome list for eScience Academy related materials
https://github.com/esciencecenter-digital-skills/awesome

List: awesome

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Awesome list for eScience Academy related materials

• Host: GitHub
• URL: https://github.com/esciencecenter-digital-skills/awesome
• Owner: esciencecenter-digital-skills
• Created: 2020-09-16T10:25:10.000Z (about 4 years ago)
• Default Branch: master
• Last Pushed: 2020-10-05T09:52:44.000Z (almost 4 years ago)
• Last Synced: 2024-04-23T11:15:01.335Z (5 months ago)
• Homepage:
• Size: 8.79 KB
• Stars: 0
• Watchers: 3
• Forks: 1
• Open Issues: 0
• Metadata Files:
  • Readme: README.md

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README

        
# Awesome list of pedagogy and training related resources

## Generic materials

### Lessons

- [Data Carpentry Lessons](https://datacarpentry.org/lessons/). Some are worth being highlighted:

  - [The Unix Shell](http://swcarpentry.github.io/shell-novice/).

  - [Version control with git](http://swcarpentry.github.io/git-novice).

  - Programming with Python. [1](http://swcarpentry.github.io/python-novice-inflammation) and [2](http://swcarpentry.github.io/python-novice-gapminder).

  - Programming with R. [1](http://swcarpentry.github.io/r-novice-inflammation) and [2](http://swcarpentry.github.io/r-novice-gapminder).

### Books

- [Effective computation in Physics](http://physics.codes/). Although the examples use physical problems and `Python` code, this book is probably the best introduction to scientific computing.

### Scientific literature

- [Best Practices for Scientific Computing](https://doi.org/10.1371/journal.pbio.1001745).

- [Good enough practices in Scientific Computing](https://journals.plos.org/ploscompbiol/article?id=10.1371/journal.pcbi.1005510).

- [Ten quick tips for teaching with participatory live coding](https://doi.org/10.1371/journal.pcbi.1008090).

### Tools

- [Witeboard](https://witeboard.com/). A shareable whiteboard app.

## git-specific materials

### Graphical User Interfaces

- [Official list](https://git-scm.com/downloads/guis). Some of our favourites are:

  - [GitKraken](https://www.gitkraken.com/).

  - [SourceTree](https://www.sourcetreeapp.com/).

  - [GitHub Desktop](https://desktop.github.com/).

  - [RStudio git client](https://rstudio.com/resources/webinars/managing-part-2-github-and-rstudio/).

## R-specific materials

### Lessons

- [RStudio educational material](https://education.rstudio.com/).

- [Interactive tutorials with `learnr`](https://rstudio.github.io/learnr/).

- Carpentries courses on R:

  - [Programming with R](http://swcarpentry.github.io/r-novice-inflammation).

  - [Programming and plotting with R and Gapminder data](http://swcarpentry.github.io/r-novice-gapminder).

### Books

- [R for Data Science](https://r4ds.had.co.nz/).

- [Advanced R](https://adv-r.hadley.nz/). Don't let the title scare you. This is probably the best written R book ever.

- [R Packages](https://r-pkgs.org/).

- [ggplot2: Elegant Graphics for Data Analysis](https://ggplot2-book.org/).

### Scientific literature

- [Tidy data](https://vita.had.co.nz/papers/tidy-data.pdf). The basic 3 principles data frames are based on.

### Other

- [RStudio cheatsheets](https://rstudio.com/resources/cheatsheets/). A collection of brilliant cheatsheets. The ones below are particularly relevant:

  - [RStudio](https://raw.githubusercontent.com/rstudio/cheatsheets/master/rstudio-ide.pdf).

  - [Data import](https://raw.githubusercontent.com/rstudio/cheatsheets/master/data-import.pdf).

  - [dplyr](https://raw.githubusercontent.com/rstudio/cheatsheets/master/data-transformation.pdf).

  - [ggplot2](https://rstudio.com/wp-content/uploads/2015/03/ggplot2-cheatsheet.pdf).

  - [RMarkdown](https://raw.githubusercontent.com/rstudio/cheatsheets/master/rmarkdown-2.0.pdf).

- [Unit testing in R](https://testthat.r-lib.org/).