# About this workshop ## Description: ### Week 1 – Intro to the shell (1 – 1.5H) In this lesson you will be learning about the command line, also known as the shell, terminal, bash, etc. You will learn concepts essential for using the command line for bioinformatics, such as navigating the file system, computationally manipulating your files (including copying, moving, and renaming), searching files, redirecting output, and writing shell scripts. **[Week 1 - Class Materials][1]** ### Week 2 - R introduction and R for data science and bioinformatics (1.5 - 2H) In this lesson you will be learning about R and how it is used for data science and bioinformatics. You will learn about R syntax, data types, and how to set up and use RStudio – a powerful and convenient environment in which to work with R. You will also be introduced to Bioconductor and R’s ecosystem for bioinformatics. **[Week 2 - class materials][2]** ### Week 3 - Python introduction and Python for data science and bioinformatics (1.5 - 2H) **[Week 3 - class materials][3]** In this lesson you will be learning about Python and how it is used for data science and bioinformatics. You will learn Python syntax and package management, using both a text editor and Jupyter notebooks to write and execute Python code. You will also get a glimpse of using Python within R using RStudio. ## Duration: 1 - 2 hr per session ## Prerequisites: There are no prerequisites for taking this class. An understanding of biological concepts and genomics will be helpful. ## Course Etherpad: https://pad.carpentries.org/UMB-Post-Docs-Bioinformatics-Training ## Related classes: * [Getting Connected to your Data – A Reproducible Workflow for Data Wrangling](https://osf.io/mwcve/) [1]: https://j-p-courneya.github.io/shell-genomics/ [2]: https://j-p-courneya.github.io/R-Bioinformatics/ [3]: https://j-p-courneya.github.io/Intro-Python-Bioinformatics/