This repository is mainly working as a student project for Master of Data Science program at the University of British Columbia, we are open source projects, and we welcome contributions of all kinds: new lessons, fixes to existing material, bug reports, and reviews of proposed changes are all welcome.
By contributing, you agree that we may redistribute your work under our license. Before contributing to this repository, please discuss the change you intend to make via issue with the owners of this repository. Please kindly refer to the code of conduct when contributing to the project.
The easiest way to get started is to file an issue to tell us about a spelling mistake, some awkward wording, or a factual error. This is a good way to introduce yourself and to meet some of our community members.
Issues in this repository are labeled with labels by the maintainers, which you may find useful for navigating open issues.
There are many ways to contribute, from writing new exercises and improving existing ones to updating or filling in the documentation and submitting bug reports about things that don’t work, aren’t clear, or are missing.
Comments on issues and reviews of pull requests are just as welcome: we are smarter together than we are on our own. Reviews from novices and newcomers are particularly valuable: it’s easy for people who have been using these lessons for a while to forget how impenetrable some of this material can be, so fresh eyes are always welcome.
If you choose to submit a pull request, please review How to Contribute to Open Source.
In brief: