Resources#
Coding#
Anaconda distribution - easy way to install Python together with the most popular data science packages (e.g.,
NumPy,Matplotlib,pandas)Programming and Data Science for Kinesiology (textbook, course materials)
The Good Research Code Handbook by Patrick Mineault
Matlab for Psychologists by Antonia Hamilton
Math#
NYU’s Math Tools for Neural and Cognitive Science - linear algebra, regression, linear systems theory, and probability and statistics
Mathematical Tools for Neuroscientists - similar content as the NYU Math Tools course that uses Python and Jupyter notebooks
Modeling#
Bayesian models of perception and action textbook by Wei Ji Ma, Konrad Kording, and Daniel Goldreich
Neuromatch Academy - summer school in computational neuroscience
Statistics#
Statistical Rethinking by Richard McElreath
Doing Bayesian Data Analysis by John Kruschke
bayes-toolbox - Python package for Bayesian analyses (from the CCM Lab)
YouTube reading course on E.T. Jaynes’ Probability Theory: The Logic of Science taught by Aubrey Clayton
Git and GitHub#
Version Control with Git from Software Carpentry
The Turing Way - online book covering best practices in data science; also has specific chapter on version control
Unix Shell#
The Unix Shell from Software Carpentry
\(\LaTeX\)#
Overleaf - user-friendly LaTeX editor