ICDS Upskilling Resources

This repository collects learning materials that help Penn State researchers build computational and data science skills, whether they are just getting started or deepening existing expertise. It is organized around the five research hubs of the Institute for Computational and Data Sciences (ICDS).

Entries come from ICDS Upskilling Fellows and the wider ICDS community. Most are links to freely available resources that members have tried and found useful. Members are also welcome to submit materials they created themselves.

Each entry names a real person who tried the resource and says how useful they found it. Contributors are encouraged to offer their opinions. All opinions expressed are those of the contributor and not necessarily those of ICDS or Penn State.

The five hubs

Pick the hub closest to your work. Resources inside each hub are grouped by type, such as courses, tutorials, tools, and books.

Hub What you’ll find Go to
Artificial Intelligence Models, assistants, coding agents, prompting, and AI literacy ai
Computational Sciences Advanced computing, simulation, modeling, and high performance computing practice computational
Data Sciences Statistics, machine learning, data management, and visualization data
Digital Twins Virtual models of physical systems, sensor integration, and real-time simulation digital-twins
Quantum Sciences Quantum information science: computing, sensing, communication, and simulation quantum

The Artificial Intelligence (AI) Hub has the most entries today, because this collection started as the AI Upskilling reading list. The other four hubs are open and waiting for their first contributions. Adding the first entry to a hub is genuinely useful, not presumptuous.

Not sure which hub fits? Pick the closest one. A maintainer can move it later.

Using this learning repository

How entries are tagged

Every entry, in every hub, carries a few short, plain-text tags so you can judge fit at a glance. Tags are written as words, never as color alone, so they work with screen readers and in high-contrast settings.

Level (how much prior background it assumes): Beginner, Intermediate, Advanced, Expert.

Modality (what kind of content it deals with): Text, Code, Images, Audio, Video.

Purpose (what you would use it for): Coding, Critical Feedback, Learning Aid, Literature Search, Productivity, Research, Writing. An entry can have more than one.

Recommendation (the reviewer’s verdict): Highly Recommend, Recommend, Neutral, Do Not Recommend.

Date (when the recommendation was made): YYYY, or MM/YYYY for more precision.

See templates/resource-entry-template.md for the exact format, and ACCESSIBILITY.md for why we tag this way.

How the repository is organized

Each hub is a top-level folder with the same shape, so once you learn one you know them all:

Shared across all hubs: the entry templates, longer detail pages, and the contributing, accessibility, and community guidelines below.

Add a resource

You do not need to be an advanced user to use or contribute to this repository. Researchers from all disciplines are welcome to contribute. We welcome perspectives from people just getting started, as well as those who bring extensive experience.

There is a path for adding resources regardless of your comfort level with GitHub. Full instructions are in CONTRIBUTING.md. In short:

You do not need to write anything long. A title, a link, a couple of tags, and one sentence about how useful you found it is plenty.

License

Content in this repository is licensed under Creative Commons Attribution-ShareAlike 4.0 International (CC BY-SA 4.0). You are free to share and adapt the material, including for commercial purposes, as long as you give appropriate credit and share any adaptations under the same license. Linked external resources remain under their own licenses and terms.

Accessibility

We aim to meet WCAG 2.2 Level AA. If you find something that is hard to read or use, please open an issue, so we can fix it.

Maintainers

This repository is a community effort. Maintainers review and merge pull requests, and transcribe form and email submissions. Contributions come from individual researchers, primarily from the ICDS community. Claude created the structure and templates. Send questions to icds@psu.edu with the subject line “ICDS Upskilling Learning Repository: Question”