Built with students at SUNY
You have a year of frontier tooling and a graduate curriculum.
You have two documents: a guide to the Google tools you get free for twelve months, and this curriculum, which teaches the method that outlives them. Read separately, one is a list of toys and the other is a pile of homework. This track is the connective tissue: nine units that take each portable idea, show it in the tooling you already have, then show you the version that still works in month thirteen. It was built with graduate students doing real technical work, but nothing in it checks your enrollment status.
This track exists because Dr. Martin Smythe worked with Internet Menace and let his students color outside the lines a little — making room in a real graduate curriculum for next-generation tooling, agentic systems, and AI coursework that shows up in job descriptions before it shows up in course catalogs. Thank you, Dr. Smythe.
How to use it
Nine units, self-paced. There is no calendar and no week numbers — each unit carries an effort estimate and its prerequisites, so you can sequence around whatever your term actually looks like. Unit 05 depends only on Unit 01, so if you need compute answers early you are not gated behind the specs units.
Every unit teaches the portable idea first, then shows it in both stacks: the Google tooling you have free for twelve months, and the Internet Menace method that outlives it.
How official is this?
Somewhat official, technically unofficial. This is a SUNY curriculum add-on in the sense that it was built with SUNY graduate students and a SUNY professor who made room for it. It is unofficial in the sense that no committee voted on it, and no university put its seal on it. Treat it accordingly: real work, done with real students, carrying nobody’s letterhead.
Not at SUNY?
Still useful. Many universities get cloud compute from a major provider — Google, AWS, or Azure — and the credits often sit unused because nobody knows to ask. Ask your computer science or data science professor, whoever runs the curriculum, whether your school gets resources from a major cloud provider you can experiment with. The answer is yes more often than you’d think.
The nine units
- 00Orientation — What You HaveActivate the offer and the credits, then set the guardrails before you spend anything.
- 01The New Foundation for ResearchersPick tools from first principles instead of habit, and know which tasks AI should not touch.
- 02Context Is the ProductGive the model your setup once, in a file, instead of retyping it every session.
- 03Specs Before PromptsSeparate what you want from what the machine needs, and review the plan before it runs.
- 04Agents in the TerminalInstall a terminal agent, give it persistent context, and wire it to your data.
- 05Compute, Models, and CostPick a GPU from VRAM requirements, not vibes, and know what your work costs in month thirteen.
- 06Trust, Verification, and Research IntegrityReview the plan, read the code, disclose the assistance, and know what you cannot upload.
- 07Two PipelinesChain the tools end to end — a literature review and an ML experiment, start to finish.
- 08Capstone — Ship SomethingTake a research need to a deployed artifact that runs while you sleep.