9 free resources on this topic. Everything here is free and hand-picked. You can also search within this topic.
NVIDIA's organization page on Hugging Face, hosting publicly listed AI models, datasets, and related resources, including the Nemotron dataset family. Individual assets carry their own license terms.
NVIDIA's technical guide discusses capabilities that agent harnesses can provide to improve model performance in tool-using workflows. It is a practitioner-oriented developer article, not a peer-reviewed research paper.
Online hackathon from Nebius and NVIDIA on Devpost: build AI on open infrastructure. $50,000 in cash prizes. Submissions close October 30, 2026 at 10:00am Pacific.
NVIDIA research project introducing the first benchmark for full-duplex audio-visual conversation in AI agents, with leaderboard, arXiv paper, and Hugging Face dataset.
NVIDIA's technical reference for continuous in-silicon monitoring of AI agents: a safety enforcement layer spanning software and hardware that watches agent behavior at the chip level, aimed at securing agents running in production.
Open-source runtime from NVIDIA for running autonomous AI agents in a sandboxed, private environment. Code and documentation are on GitHub.
The official free download and documentation for CUDA, Nvidia's platform for running AI and scientific computing on its graphics chips. Includes compilers, libraries and learning guides.
Why I recommend it: The toolkit itself is free, but it only runs on Nvidia's own chips — learning CUDA ties your skills to one company's hardware. Nvidia dominates AI chips, so that trade-off is real but worth knowing about.
Politico report (Sept. 15, 2026) on Jensen Huang arguing AI safety is an engineering problem and that no new laws are needed.
Why I recommend it: Nvidia sells the chips AI runs on and gains from fewer rules. The site blocked my automatic check, so the title is my summary.
NVIDIA's catalog filtered to its free self-paced courses covering AI, deep learning, generative AI, data science, accelerated computing, and CUDA — with certificates of competency on many tracks.
In plain terms: This website offers a collection of free, self-paced online classes in artificial intelligence, data science, and computing. You can take lessons to build new technical skills and earn certificates to share with employers.
From the site: Browse NVIDIA self-paced and instructor-led training, including free courses in AI, deep learning, generative AI, data science, and accelerated computing.
Why I recommend it: Start with a free intro course and put it on your resume under a "Continued Learning" section. Hiring managers notice vendor-name training, and NVIDIA carries weight in AI and data roles.
