Artificial Intelligence

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Artificial Intelligence

Lead with AI. Real projects, real abilities.

Students working on 3D modeling projects in the Ace Acumen Heights computer lab
Students building a robotics project at the AI ThinkLabStudents working together on a hands-on problem-solving challenge in the AI Program

Overview

As AI takes on more of the world’s routine work, the abilities that matter most are deeply human: thinking a vague idea into a clear problem, organizing complex work, judging what is true and what is good, and turning ideas into something real. The AI Program is built around these four abilities.

Every term, students take one real problem from first idea to finished product — something you can open and try yourself. The abilities grow in the student, and the evidence grows in their portfolio. Over four years, that portfolio becomes one of the most distinctive things a student can bring to universities and employers.

In our classroom, AI plays the role a barbell plays in a gym: it is the equipment students train with, and the four abilities are what grow stronger.

Program Structure

  1. Open enrollment · placement by assessment

    Level 1

    Tiered project-based AI training (foundation / intermediate / advanced). Students are placed at the tier that fits their ability, so everyone works at the right level of challenge. This is where the four abilities are built, term by term, into a growing portfolio.

  2. Promotion by selection · external applicants welcome

    Level 2

    Competition training with Kaggle as the main track: real data, self-designed approaches, complete pipelines, and a public leaderboard that rewards iteration. Students progress through a ladder of competitions matched to their readiness, and each entry includes the student’s own write-up and presentation of their approach.

  3. By selection

    Beyond

    Students who excel at Level 2 become eligible for advanced real-world project work, with selection based on demonstrated ability and a strong portfolio.

Four Abilities We Train

Critical Thinking — Problem Definition — The Founder

Every great project starts with a sharp question. Before writing a line of code, students learn to ask: who is this for, where do they struggle, and which need are we serving? The clearer the question, the more powerful AI becomes as a partner — and the more valuable the person who asked it.

Organization — Decomposition & Architecture — The Architect

Students learn to take a large goal and shape it themselves: splitting it into modules, sequencing the work, defining inputs and outputs, and planning for the tricky parts — then directing AI to execute. It is often the first time they design the plan from start to finish, and it is a skill that carries into everything they do.

Judgment — Verification & Taste — The Scientist

Students learn to verify before they trust: ask for evidence, check the data, and test the result. And when AI offers ten possible solutions in a minute, choosing well takes taste — developed the way scientists and designers develop it, by building, comparing, and learning from real user feedback.

Creation & Resilience — Shipping & Iteration — The Entrepreneur

Student work ships to real settings, and feedback from real users drives each round of improvement. At Demo Day, students present what they built, why they built it, and how they worked through the hard parts — valuable practice for every interview and application essay ahead.

Program Highlights

One Real Problem Per Term

Every term ends with a working product families can open and try — a finished piece of real work.

Present and Explain

At Demo Day, students walk their audience through the problem, the architecture, and how they verified their results — proof of genuine understanding behind every project.

Abilities That Compound

Abilities compound in the student; results compound in their portfolio. One becomes their strength, the other their proof.

Tangible Achievements

A portfolio of real work that enriches university applications, interviews, and resumes.

Who It's For

Grade 7–12 students who are excited to define and build their own projects. No prior coding experience is required for entry levels — a placement assessment finds the right starting tier. Students already use AI every day; here, they learn to lead it.

Interested in the AI Program?

Book a personalized session or join an Open House to learn how this program fits your child's pathway.