AI for Youth Academy Future Scholars Research Initiative

Summer Camp · Coming Summer 2026 · Weekend Studios

Build world-changing ideas with AI, one year at a time.

AI for Youth Academy is a four-year journey for middle and high school innovators. Explore, engineer, and launch responsible AI projects with guidance from FSRI mentors and college ambassadors.

4-Year Pathway
Curated curriculum from first AI experiments to venture launches.
Mentor Network
College ambassadors and industry coaches in every cohort.
Future Focused
Ethics, creativity, and impact baked into every project milestone.

Why This Academy Exists

We keep AI learning affordable and hands-on so motivated students can start building real projects, grow confidence early, and lead with purpose.

Our Guiding Beliefs

Three principles shape every AI for Youth session

  1. Hands-on practice beats theory alone. Middle schoolers grasp AI faster when they build, train, and test real models without waiting on advanced math.
  2. Early foundations unlock high school opportunities. Students who understand AI before ninth grade are ready to lead clubs, volunteer on tech initiatives, or launch bold ideas.
  3. Self-motivated learners thrive. Complex topics stick when students own their learning journey and stretch further with mentor support.

Five-stage progression

Every season unlocks a new layer of AI mastery.

Students can jump in at the level that fits their experience, then follow the guided track of summer camps and school-year studios to keep momentum going.

  1. Year 0 · Python for First Lego League

    Twelve-week bridge from block coding to competition-ready SPIKE Prime runs

    Ideal for FIRST LEGO League teams in grades 5-7

    Convert LEGO robotics momentum into Python confidence while targeting UNEARTHED™ missions with disciplined testing habits.

    Key Themes

    • Python control structures for reliable autonomous runs
    • Sensor-driven calibration and mission alignment habits
    • Competition discipline through testing, menus, and reset routines

    Hands-on Moments

    • Weeks 1-4: Calibrate straight drives, gyro turns, and sensor triggers with Python fundamentals.
    • Weeks 5-8: Layer line following, distance sensing, and attachment automation for UNEARTHED™ missions.
    • Weeks 9-12: Chain launches, add testing menus, and polish showcase-ready full runs.

    Tools

    • LEGO SPIKE Prime
    • Python via SPIKE App
    • UNEARTHED™ mission field attachments

    What Students Walk Away With

    • Move from block-based coding to Python programs that hold calibration across matches
    • Use reusable configs, asserts, and logs to document tunings for the whole team
    • Run disciplined 2:30 cycles with launch menus, reset roles, and debrief notes
  2. Year 1 · AI Explorer

    Curiosity-driven introduction to machine intelligence

    Ideal for middle school grades 6-7

    Two-weeks camp $1000 Now $700

    Start with playful experiments that demystify artificial intelligence. Students build intuition about how machines learn by training models they can see and tweak in real time.

    Key Themes

    • How computers recognize patterns
    • Ethics and responsible AI features
    • Designing fair training datasets

    Hands-on Moments

    • Use Google Teachable Machine to create image, sound, and pose models
    • Rapid model prototyping with everyday sports moments most middle schoolers experience, grounding AI in their daily routines
    • Group challenges that highlight bias and model tuning

    Tools

    • Google Teachable Machine
    • Scratch extensions

    What Students Walk Away With

    • Confidently explain AI concepts using everyday language
    • Understand the importance of quality data and testing
    • Document learning with a reflective mini-portfolio
  3. Year 2 · AI Engineer I

    Build and train your first computer vision models with PyTorch

    Designed for returning grade 7-8 students

    Students transition from block-based experimentation to real code. They learn the building blocks of neural networks and train convolutional models to recognize custom datasets.

    Key Themes

    • Neural network fundamentals
    • Iterative model improvement and evaluation
    • Responsible dataset curation and augmentation

    Hands-on Moments

    • Code-along labs that train CNNs in PyTorch
    • Image classification challenges built from student photo sets
    • Model performance dashboards and reflection journals

    Tools

    • Python · PyTorch
    • JupyterLab
    • Gradio for demos

    What Students Walk Away With

    • Train, test, and iterate on convolutional neural networks
    • Interpret confusion matrices and accuracy metrics
    Summer Studio Three-week intensive · 3.5 hours/day with paired programming Weekend Lab 14-week cohort · Project milestones every month
  4. Year 3 · AI Engineer II

    Solve real problems with foundation and language models

    For advanced middle school and early high school students

    Learners accelerate by orchestrating powerful pre-trained models. They test vision systems like YOLO and OpenPose and unpack MiniMind language models to power applications in sports, safety, and creative tech.

    Key Themes

    • Transfer learning and fine-tuning
    • Vision AI for motion-rich community challenges
    • Language model fundamentals with MiniMind (tokenization, embeddings, prompting)

    Hands-on Moments

    • Run YOLO and OpenPose pipelines to analyze sports and stage footage in real time
    • MiniMind labs that demystify tokenization, word embeddings, and conversational behaviors
    • Design critique rounds with mentors from industry

    Tools

    • YOLOv8
    • OpenPose
    • MiniMind
    • Google Colab

    What Students Walk Away With

    • Select the right foundation model for a target problem
    • Optimize inference for speed, accuracy, and fairness
    • Explain how word embeddings and prompts shape language model outputs
    Summer Studio Four-week accelerator · Mentors + field research days After School Residency 24-week residency · Community partner capstone with monthly showcases
  5. Year 4 · AI Creator

    Student-led ventures that tackle real-world challenges

    Open to high school leaders and alumni

    The final year empowers students to scope, build, and launch original AI solutions. Alongside mentor guidance, they explore retrieval-augmented generation (RAG), multimodal workflows, and agent design to choose the right approach for their venture.

    Key Themes

    • Product thinking and UX research
    • Ethics reviews and stakeholder interviews
    • Intro to RAG, AI agents, and multimodal systems

    Hands-on Moments

    • Project incubator sprints with weekly mentor check-ins
    • Mini-labs on agent flows, retrieval pipelines, and multimodal prototyping
    • Designing pilots with local partners and user testers
    • Showcase pitch night with judges and community leaders

    Tools

    • Full Firebase suite
    • Cloud Functions
    • RAG stacks (e.g., Pinecone + MiniMind)
    • Multimodal APIs

    What Students Walk Away With

    • Ship a polished MVP with measurable community value
    • Lead teams through agile planning and retrospectives
    • Explain when to apply RAG, agents, or multimodal techniques to their solution
    Launch Lab Semester-long incubator · Weekly strategy labs + mentor office hours Summer Venture Five-week sprint · Field immersion + demo day showcase

Learning experiences

Designed for curious creators who learn by doing.

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.

Studio-powered summer camps

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.

  • Daily design sprints and lightning talks from guest mentors
  • Hands-on labs with maker kits, cameras, and edge AI devices
  • Reflective journals and demo booths to document growth

After school & weekend labs

Weekly meetups keep the momentum going during the school year. Teams plan, prototype, and iterate with guidance from college ambassadors and industry coaches.

  • Community-centered problem statements sourced from partners
  • Peer code reviews and showcase standups every other week
  • Pathway badges that recognize technical and leadership growth

Mentor moments & future pathways

Students meet researchers, designers, and entrepreneurs who apply AI responsibly. Alumni get early access to internships, hackathons, and paid teaching-fellow roles.

  • Portfolio coaching and college-ready recommendation letters
  • Connections to national AI competitions and showcase events
  • Alumni network with year-round learning and leadership opportunities

Track planner

Choose the learning pace that fits your student leaders.

We currently run two themed tracks so families can align progression with school commitments. Each track covers the same four program years, but the timing and storytelling themes differ.

Students playing volleyball

Track A

Accelerated Track

Theme: Volleyball · Recommended for students in 8th grade and above

A rapid pathway for motivated students who want to experience every program year within four consecutive seasons.

Figure skater practicing on ice

Track B

Foundations Track

Theme: Figure Skating · Recommended for students in 6th grade and above

A steady progression that gives younger learners time to deepen skills between program years while staying connected to a shared theme.

Join the waitlist

Ready to bring AI for Youth Academy to your community?

Seats are limited and selection is highly competitive. Share your details to receive the program guide, schedule a planning call, 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.