Computational neuroscience means one of two things: 1. analysis of neuroscientific data, whether it be fMRI imaging data, electrode recordings from a mouse running in a maze, statistical modeling of that data, or something else, and 2. simulation of neural systems, including modeling many compartments of a single neuron, or large networks of model neurons with simple individual behavior. These endeavors require expensive data from wet-lab experiments, but much of the work can be accomplished using everyday, consumer-grade laptop and desktop computers! Indeed, the biggest barrier to entry is not hardware, data, or expense, but rather time and passion to learn the tools needed for such computational science. Coupled with the great tools coming out of the modern Data Science movement, open data, open simulation models, and open analysis and simulation tools for computational neuroscience make it easier than ever to learn or even contribute to the study of the brain! The resources below should be more than enough to provide anyone with the means to begin learning or working in computational neuroscience, at no cost other than time and a modern computer. Note: This is intended as a list of resources to help with neuroscientific pursuits, as opposed to artificial intelligence pursuits. More broadly, I've made a similar repo-list of general open science resources here.