Tutorials
The following is a list of online self-study tutorials prepared by the SCF and partners. Note that a zip file with all the (non-screencast) materials for each tutorial can be found by following the (materials on Github) link and using the "Download ZIP" button in the lower right of the Github page.
- Basics of UNIX
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Provides a basic introduction to the UNIX command line (including Linux and the Mac terminal).
Last updated December 2021. Prepared by Chris Paciorek. - Using the bash shell
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UNIX utilities, shortcuts, shell scripting, job control, and regular expressions.
Last updated June 2022. Prepared by Jarrod Millman and Chris Paciorek. - Introduction to LaTeX
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A quick introduction to LaTeX, a powerful and flexible system for formatting documents, especially those using mathematical notation. Focuses on demonstration using a concrete example.
Last updated August 2015. Prepared by Chris Paciorek. - Dynamic documents with code chunks
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A quick introduction to embedding R, bash, and Python code in PDF and HTML documents using R Markdown, Quarto, LaTeX based (knitr and Sweave) formats, and Jupyter notebooks.
Last updated August 2023. Prepared by Chris Paciorek. - Introduction to git and GitHub
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The basics of git, a version control system, and hosting git repositories on GitHub.
Last updated August 2017. Prepared by Jarrod Millman. - String processing
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String processing, including regular expressions, in R and Python.
Last updated August 2023. Prepared by Chris Paciorek. - Parallel processing in Python, R, Julia, Matlab, and C/C++, including GPU use
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How to use threaded linear algebra and basic parallel processing on one or more machines (including use with the Slurm scheduler).
Last updated March 2024. Prepared by Chris Paciorek. - Flexible parallel processing using Dask in Python and future in R
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Parallel processing on one or more machines, including using distributed datasets in Dask.
Last updated October 2024. Prepared by Chris Paciorek. - Working with large datasets in SQL, R, and Python
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Using databases and Google BigQuery from R and Python, plus material on packages in R and Python for working with large datasets.
Last updated March 2024. Prepared by Chris Paciorek. - Using make for workflows
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How to use make to automate workflows and make them reproducible.
Last updated August 2015. Prepared by Chris Paciorek. - Writing efficient R code
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How to assess the speed of your code and write code that will run quickly in R.
Last updated September 2022. Prepared by Chris Paciorek. - Debugging in R
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How to use R's debugging tools, handle errors, and avoid bugs.
Last updated September 2022. Prepared by Chris Paciorek.
Last updated January 2023.