Professional Data Analytics
These are set of common pages to help get started with professional data analytics, including GitHub, Git, Python, Markdown, VS Code, and more.
Our Goal
Our goal is to help you get productive quickly and effectively. We introduce the general landscape and terms, and provide a bit of what they do and why we think these tools are worth learning. Details are left to outside resources.
Requirements
Recommended choices are nearly always free and open-source. You will need a relatively modern machine and electricity to keep it running. Your curiousity, resourcefulness, and tenacity will be quite valuable.
Start Here
- First, sign up for a free account on GitHub.
Then, read about and install the following on your machine.
- Git - a system for tracking evolving code files and syncing between your machine and GitHub
- VS Code - a lightweight editor great for beginners and professionals alike
- Python - a popular, powerful language for working with data
Chapters
We organize our documentation into several main categories. Click the links below to explore each chapter:
Or browse the sidebar menu on the left.
Contributing
We welcome contributions to our documentation! If you’re interested in contributing, please see the CONTRIBUTING.md file for guidelines on how to get started.
Feedback
To provide comments or feedback, please use the Issues and Discussions tabs in the GitHub repo.
License
This documentation is licensed under the Creative Commons Attribution-ShareAlike 4.0 International license. Please see the LICENSE.md file for more information.