Tools
Learning Resources
A collection of self-guided learning resources created by others.
Git / GitHub
Best Practices Example from Utrecht University
Languages and Programming
Python
How to Learn to Code – A 5 minute video on how to approach programming, either learning theory, soliciting advice, OR (hint hint) problem solving.
Python Course: Programming for Everybody (Getting Started with Python) – A terrific free course by the University of Michigan to learn the basics of programming in Python, with no prerequisites.
Biopython Course: Bioinformatics with Biopython – A 1-hour YouTube course that covers some common uses of biopython. Biopython is a set of tools for biological computaiton that is written in Python. It has many useful functions for processing and working with sequence files.
Python Cheatsheet – A quick-reference, cheatsheet-styled website for common tasks/tricks in python. Helpful for beginners and power-users.
R
R Course: swirl - learn R, in R – Super cool way to learn R programming and datascience interactively, at your own pace, and in the R console. There is a library of courses you can learn from.
R Course: Data Analysis using R – A comprehensive and high quality YouTube based course by Dr. Danny Arends (with videos, access to lectures, assignments, and answers) for those within minimal to no previous programming experience. This might be one of the best courses available.
R for Data Science – A website for the “R for Data Science” book, with a focus on how to perform data science with R, from data exploration (visualization, workflow, working with tidy data, scripting), wrangling, modeling, and communicating results (R markdown).
R Cheatsheet – A quick-reference cheatsheet for R.
Unix and Bash
Unix Book: Unix Workbench – A website (book) for those new to Unix-like operating systems and working at the command-line. This book covers unix and command-line basics, as well as introductory bash programming concepts (math, variables, loops, input/output, arrays, pbraces, functions), and writing programs. As a nice bonus, it also gives brief introductions to Git, GitHub, and Cloud Computing.
Bash Reference: bash-guide – Common commands, with some minimal examples.
Julia
Julia Course: Zero-to-Hero Julia Workshop – Two day intensive, recorded (YouTube), workshop on the programming language, Julia. This workshop is intended for beginners. Julia is a programming language designed for scientific computing, to be quick, but also readable and high-level like Python.
Plotting and Visualizations
With Python
Introduction to Data Visualization in Python – A very simple introduction to data visualization in Python.
Python Data Visualization Tutorials – A set of tutorials for plotting with Python in Pandas, matplotlib, seaborn, and boken (interactive visualizations).
Interactive Visualizations with Plotly in Python – An introduction, for beginners, to interactively plotting in Python using Plotly.
With R
Data Visualization with R – A Web-based book focused on data visualization and plotting with R. It covers data importing, cleaning, using plotting libraries (ggplot2), customizing plots, interactive visualization, and more.
Shiny Cheatsheet – A quick reference cheatsheet for creating interactive web apps with shiny.