Connect Data Tools Beyond R
Learning Objectives
After completing this material, an individual will be able to connect with other data science tools beyond R.
- use unix/linux shell to search and modify project
- initial steps toward reproducible research
- build a basic pipeline or workflow in the shell ⚠️
- Scaling up the split-apply-combine paradigm
Pages
- Computing Environments: Linux, Bash, Docker, and Tooling
- Reproducible Research, LaTeX & Scientific Writing
- Scaling R & Data Science Teams
- Professional Data Science Programs & Online Courses
- Stat 692 Fall 2014 Notes
References
-
[JuliaCon 2018 Keynote - The Rise of the Research Software Engineer Mike Croucher](https://www.youtube.com/watch?reload=9&v=8ZSaAM8hhJ4) (github slides) - Software Carpentry Unix Shell
- Software Carpentry Automation with Make
- Jenny Bryan pipeline automation ⚠️
- GNU Make Tutorial (Karl Broman)
- LaTeX Writing Language
- Reproducible Research Tools Links
-
Docker & Guix (build & run isolated containers of software)
- Going beyond R
- http://software-carpentry.org
- http://chtc.cs.wisc.edu
- history of teletype and relation to short Unix command names ⚠️