Sources & independence.
The Study Lab is built from the open courseware below — we learn from it, then write our own lessons, our own code, and measure our own results. We link to the originals; we do not rehost their materials.
Plasmient is an independent project. It is not affiliated with, sponsored by, or endorsed by Stanford, MIT, CMU, or any institution. Course and instructor names appear here for factual reference only. All course materials belong to their respective owners and remain under their own licenses (e.g. MIT OpenCourseWare is CC BY-NC-SA). We use no institutional logos and claim no partnership.
Curriculum sources
- Stanford CS229 — Machine Learning— Andrew Ng
- Stanford CS336 — Language Models from Scratch— Stanford
- MIT 6.5940 — TinyML & Efficient Deep Learning— Song Han
- CMU 10-714 — Deep Learning Systems— Zico Kolter, Tianqi Chen
- Stanford CS149 / MIT 6.172 — Parallel & Performance— Stanford / MIT
- GPU MODE — kernel & CUDA community— GPU MODE
- NVIDIA DCGM / CUPTI / Nsight docs— NVIDIA
What is ours
The interactive lessons, the synthesis write-ups, the measurement code in the labs, and any numbers we publish from running it. That original work is the proof — not anyone else's brand.