| title | Tutorials |
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The SCF and partners have prepared a number of online self-study tutorials. Anyone is welcome to use the materials, including as part of a class.
Most of the tutorials come as websites hosted on GitHub Pages with the content living in a GitHub repository. For some of the older tutorials that have not been updated recently, there is only a GitHub repository.
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:::{card} :header: The basics of UNIX and the command line :footer: Last updated January 2025. :link: https://computing.stat.berkeley.edu/tutorial-unix-basics
A basic introduction to the UNIX command line (including Linux and the Mac terminal).
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:::{card} :header: Using the bash shell :footer: Last updated April 2025. :link: https://computing.stat.berkeley.edu/tutorial-using-bash
In-depth coverage of UNIX utilities, shortcuts, shell scripting, job control, and regular expressions. :::
:::{card} :header: Parallel processing in Python, R, Julia, MATLAB, and C/C++, including GPU use :footer: Last updated April 2025. :link: https://computing.stat.berkeley.edu/tutorial-parallelization
In-depth coverage of basic parallel processing on one or more machines (including use with the Slurm scheduler). :::
:::{card} :header: Flexible parallelization using Dask in Python and future in R :footer: Last updated April 2025. :link: https://computing.stat.berkeley.edu/tutorial-dask-future
An overview of two of the most general and popular frameworks for parallelization, including using distributed datasets in Dask.
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:::{card} :header: Working with large datasets in SQL, R, and Python :footer: Last updated July 2025. :link: https://computing.stat.berkeley.edu/tutorial-databases
Using databases and Google BigQuery from R and Python, plus material on packages in R and Python for working with large datasets. :::
:::{card} :header: Dynamic documents with code chunks :footer: Last updated February 2025. :link: https://computing.stat.berkeley.edu/tutorial-dynamic-docs
A quick introduction to embedding R, bash, Python, and Julia code in PDF and HTML documents using Quarto, R Markdown, LaTeX based (knitr and Sweave) formats, and Jupyter notebooks.
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:::{card} :header: String processing :footer: Last updated August 2023. :link: https://computing.stat.berkeley.edu/tutorial-string-processing
An overview of string processing, including regular expressions, in R and Python. :::
:::{card} :header: Writing efficient R code :footer: Last updated September 2022. :link: https://computing.stat.berkeley.edu/tutorial-efficient-R How to assess the speed of your code and write code that will run quickly in R. :::
:::{card} :header: Debugging in R :footer: Last updated September 2022. :link: https://computing.stat.berkeley.edu/tutorial-R-debugging How to use R's debugging tools, handle errors, and avoid bugs, with an accompanying YouTube demo of debugging in R. :::
:::{card} :header: Introduction to LaTeX (deprecated) :footer: Last updated August 2015. :link: https://github.com/berkeley-scf/tutorial-latex-intro A quick introduction to LaTeX, focusing on a demonstration with a concrete example and an accompanying YouTube demo on LaTeX/LyX. :::
:::{card} :header: Introduction to Git and GitHub (deprecated) :footer: Last updated August 2017. :link: https://github.com/berkeley-scf/tutorial-git-basics
The basics of git, a version control system, and hosting git repositories on GitHub.
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:::{card} :header: Using make for workflows (deprecated) :footer: Last updated August 2015. :link: http://github.com/berkeley-scf/tutorial-make-workflows How to use make to automate workflows and make them reproducible, with an accompanying YouTube demo on make.