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Bioinformatics and Computational Biology: R and Python Resources

Free Online Courses

CMU has a subscription to Lynda which provides tutorials on a large variety of software, including R, Python, and MATLAB. If you prefer a longer format for learning, check out Udacity for free courses on data science that are meant to take a month or so to complete.

 

Tools for R

R: a free software environment for statistical computing and graphics. It compiles and runs on a wide variety of UNIX platforms, Windows and MacOS

RStudio: makes R easier to use and includes a code editor, debugging, and visualization tools

R and Rstudio online learning resources: a wealth of tutorials, articles, and examples to help you learn R and its extensions

R Statistics Guide: a repository of open access learning resources for R for beginners and more advanced users

Quick-R: a website for both current R users and experienced users of other statistical packages (e.g., SAS, SPSS, Stata) who would like to transition to R

Using R for statistical analyses: a course by Dr. Mark Gardener on his webpage “Gardener Sown” 

Tools for Python

Python: a popular programming language commonly used for data science

Python for Beginners: how to get started from the developers of Python

Learn Python the Hard Way: a good resource for beginners with no programming experience.  Available in our library

Practice Python: a set of simple but practical exercises intended to teach Python to beginners. Each one comes with a short discussion about a specific topic and also a link to the solution later on.

Think Python: a free book that is an introduction to Python programming for beginners. It starts with basic concepts of programming, and is carefully designed to define all terms when they are first used and to develop each new concept in a logical progression. 

Python Crash Coursea fast-paced, thorough introduction to Python that teaches by having users work through projects. Available in our library.

Google's Python Class: a free class intended for anyone who wants to learn Python and has some programming experience. It includes lecture videos and written material, as well as plenty of coding exercises to practice Python coding.

Bioinformatics and Computer Science

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Huajin Wang
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