Data Sciences resources

This folder will hold the Data Sciences Hub’s learning resources, grouped by type. Nothing has been added yet. See the hub home page for what belongs here and how to add the first entry.

Planned categories

Each category becomes its own page under this folder once it has an entry. A maintainer creates the page when the first entry for that category arrives, so you never have to set up folders yourself.

Category	What will go in it
Courses	Structured, multi-module courses and certificate programs.
Tutorials and guides	Short how-to walkthroughs, cheat sheets, and written guides.
Tools and software	Software, platforms, and environments used to get work done.
Books and articles	Longer reading, papers, and reports.
Videos and talks	Recorded talks, lectures, and video series.
Community repositories	Full GitHub repositories shared by Penn State colleagues.

Hubs share this category list so the repository reads the same everywhere. A hub can add a category that genuinely fits its field; ask a maintainer and they will set it up. The AI Hub, for example, adds an “AI models” category.

How to read an entry

Every entry has a linked title, a line of plain-text tags (Level, Modality, Purpose), and one or more reviews. Each review names a real person and gives a recommendation, often with a sentence on why. Some entries link to a detail page under details/ with more depth.

How to add one

See CONTRIBUTING.md. There is a path for every comfort level with GitHub, including a pull request, a GitHub issue, or an email. Copy the entry template, fill it in, and a maintainer will place it under the right category.