Data Learning Resources

The increasing number of online resources for self-study in computer programing, quantitative methods and data management can be overwhelming. Beyond resources developed by SESYNC, we have compiled a list of resources that we often recommend to researchers looking for additional learning aids.

Programming Guides and Tutorials

Topic Link Environment
Basics/Syntax R for Journalists R
Basics/Syntax R Tutorial R
Basics/Syntax The Unix Shell Shell
Basics/Syntax Resources for Better Science in Less Time R
Language Hadley Wickam's Advanced R R
Language swirl; Learn R in R R
Language Programming with Python Python
Language How to Teach Yourself R R
Statistical Operations Mark Gardener's Statistics Tutorial R
Statistical Operations In-Depth Introduction to Machine Learning R
Visualizations Graphics Cookbook R
Visualizations Comprehensive ggplot Gallery R
Visualizations Producing Simple Graphs R
Geospatial Data Introduction to Rasters R
Geospatial Data Data Intensive Tutorials Various
Geospatial Data Earth ML Tutorials Python
Version Control git Tutorial Shell
Version Control Version control background Various
Version Control Git in RStudio R
Version Control Git setup Various
Web Scraping Requests and BeautifulSoup Python
Full Course Jenny Bryan's Stat 545 R
Full Course Transition to R; Free Online Course R


Software and Data Resources Oriented to Specific Disciplines

Topic Link Environment
Soil Science List of Open Source Software Tools Various
Environmental Science Quantitative Tutorials R
Environmental Science Environmental/Conservation Data Resources (NYU) R
Basic Fisheries Analysis Introduction to R and Tutorials R


Cheat Sheets

Topic Link Environment
Unix/Linux Unix/Linux Shell
RStudio IDE RStudio IDE R
R Markdown R Markdown R
R Markdown Reference Guide R Markdown Reference Guide R
Data Visualization Data Visualization R
Package Development Package Development R
Data Wrangling Data Wrangling R
RShiny RShiny R
More R Cheat Sheets More R Cheat Sheets R

Online Data and Statistics Communities  

Topic Link Environment
EcoDataScience Study Group Eco-Data-Science Various
R-bloggers News and Tutorials R-bloggers R
Stack Overflow Interactive Q&A Stack Overflow Various
SESYNC Github Page SESYNC Github Various

Many additional topics are available through the following websites or organizations. These are geared towards providing a lot of training material.

●    NEON #WorkWithData
●    Data Carpentry
●    Software Carpentry

If you are looking to participate directly with a larger network of scientific coders, good starting points are the R-bloggers and rOpenSci communities.