NVIDIA Deep Learning Institute – Self-Paced Courses
Free and paid self-paced online courses from NVIDIA's Deep Learning Institute covering generative AI, deep learning, and data science fundamentals, with hands-on GPU-accelerated labs and certificates of competency for select courses.
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Veritas AI Scholars
A Palo Alto-based introductory AI bootcamp for high school students in grades 9-12 with no prerequisites, covering key AI and data science concepts through live online instructor-led sessions culminating in a small-group mentored project.
Algoverse AI Research Program
A 12-week online AI research program pairing high school and college students in small teams with mentors from institutions like Stanford, OpenAI, Meta FAIR, and Google DeepMind to develop LLM-reasoning research submitted to venues such as NeurIPS and ICLR; requires Python experience and a $3,325 fee with need-based and merit scholarships.
IBM SkillsBuild for High School – Artificial Intelligence
A free, self-paced online platform from IBM offering high school students courses and digital credentials in AI fundamentals, covering machine learning, natural language processing, computer vision, chatbots, neural networks, and AI ethics.
Polygence – Artificial Intelligence Research
A 1-on-1 mentorship program pairing high school students with expert or PhD mentors to design and complete an original AI/machine learning research project of their choosing, culminating in a paper, GitHub portfolio, or conference-style presentation.
RISE Research – Machine Learning Research Mentorship
A 10-week 1-on-1 research mentorship program pairing high school students with PhD mentors from institutions like MIT, Oxford, and Carnegie Mellon to produce original, publishable machine learning research, with a stated 90% publication success rate.
AI4ALL@UW Data Science Workshop
A free 20-week introductory data science and machine learning workshop from the University of Washington's AI4ALL chapter for rising high school juniors/seniors and college freshmen, emphasizing collaborative learning and disability-informed perspectives on bias and fairness in AI.