Summer Camps · After-School Labs · Weekend Studios
AI for Youth Academy is a five-year journey for middle and high school innovators. Build foundational math, programming, and machine learning intuition, then apply it in a capstone project with guidance from mentors and college ambassadors.
A small extracurricular circle for standout students who want to geek out, go deeper, and build projects way beyond the usual curriculum.
Our Guiding Beliefs
Middle schoolers grasp AI faster when they build, train, and test real models.
Students who understand AI before eleventh grade are ready to lead clubs, volunteer on tech initiatives, or launch bold ideas.
Complex topics stick when students own their learning journey and stretch further with mentor support.
Five-year roadmap
Thanks for your trust; welcome to the journey. Over the next four years students build foundations in math, programming, machine learning, and neural networks. These topics sound graduate-level, so we focus on core ideas without formal derivations. Year 5 is a project capstone that applies the full stack.
2D vectors, matrix representations, and beginner Python
Spring term core foundations
Students build intuition for 2D space, matrix representations of vectors, and linear equations while learning Python basics through FIRST LEGO Challenge robotics.
Coding agent setup, app development, and team collaboration
Project-based learning across three semesters
Students make a coding agent their everyday build partner, develop real applications with it, and learn to work as a team from the first commit to a live site. Projects use real data, such as the Town of Cary budget, and ship through GitHub.
3D space, projection, and clustering
Year 3 core studio
Students move into 3D space, 2D projection, and linear algebra basics while exploring dimensionality reduction and unsupervised learning. They also build classification models with scikit-learn using the MNIST dataset.
CNNs, fine-tuning, and modern model stacks
Year 4 advanced studio
Students build pre-calc graph intuition, then dive into CNN structure, fine-tuning workflows, and foundation model applications. Programming includes AI-assisted PyTorch work and an optional transformer overview if time allows.
Build a complete project from idea to demo
Project year
Students plan and deliver a full AI project, combining math intuition, ML workflows, and neural network tools into a real-world prototype.
Learning experiences
Whether summer camps or weekend studios, every cohort blends collaborative play, rapid prototyping, and real-world mentorship. Students build confidence and community while solving meaningful problems.
Choose immersive week-long or multi-week camps that mix morning deep-dives with afternoon build sessions. Showcase nights bring families, educators, and community partners together to celebrate progress.
Weekly meetups keep the momentum going during the school year. Teams plan, prototype, and iterate with guidance from college ambassadors and industry coaches.
Students meet researchers, designers, and entrepreneurs who apply AI responsibly. Alumni get early access to internships, hackathons, and paid teaching-fellow roles.
Project showcase
Every project here was designed, coded, and deployed by students. Explore their live work.
2026–2027 Year Round · 5–7th grade students
A creature field-guide wiki where each student adds — and animates — their own creature in its own folder, built to practice pull requests with no merge conflicts.
2026 Summer Camp · Year 2 students
Interactive charts built from the Town of Cary's adopted FY2024–FY2026 budgets: total spending, where every dollar goes, category changes year over year, and a General Fund breakdown.
2025 Summer Camp · Kaylin
An interactive crochet learning site with an AI chatbot and project-photo analysis that gives personalized next-step feedback, powered by Google Gemini.
Track planner
We run two parallel tracks with the same five-year pacing. Years 1-2 are a shared core foundation. Starting in Year 3, students choose a volleyball or figure skating focus for projects and datasets.
A shared Year 1-2 core covers math, Python, and supervised learning. Starting in Year 3, projects and datasets focus on volleyball movement, gameplay, and team insights.
A shared Year 1-2 core covers math, Python, and supervised learning. Starting in Year 3, projects and datasets focus on figure skating movement, choreography, and performance insights.
Join the waitlist
Seats are limited and selection is highly competitive. Share your details to receive the program guide and get notified when enrollment opens. Students who are exploring on their own are always welcome to follow our self-paced study guides while they wait.