Computer vision
Deepfake detection
Tells whether a face in a video was filmed or generated by AI, even when it looks convincing.
Students 10+學生
Students learn what AI can do by building with it.
They learn the theory behind how AI works, then use the same tools AI engineers use to build agents, creative projects, and prototypes of their own.
Our approach教學理念
English is the new programming language.
Most coding schools start with months of Python syntax. At AI School, students learn agentic engineering: directing AI to write code instead of writing it themselves.
The skill that matters now is knowing what to ask for, how to give the right context, and how to judge what comes back. Students leave able to make working software, with the taste to know when AI is wrong and the habit of giving it the kind of brief it can act on.
Curriculum課程
What ten sessions look like.
A flexible ten-session arc, adapted to each student. The first five build the foundation in Python and how AI works. The last five turn it into a project the student can present.
Session 1
Orientation and AI Builder's Map
Mini Vibe Coding Hackathon
Python and Exploring Data
Session 2
Machine Learning Foundations
Training an Image Classifier
Classification and Bias Auditing
Session 3
Neural Network and Computer Vision
Interactive Neural Network Model
Build a Computer Vision App
Session 4
Natural Language Processing
Prompt Engineering Challenge
Build an NLP App
Session 5
AI Agents and Agentic Systems
AI Agent Demo and App Design
Build and Deploy Your Own Agent
Session 6
AI Ethics and Decision-Making
Data Exploration
Pick a project, explore data
Session 7
Where AI is going next
AI Model Building
Building together
Session 8
Debugging and improving your project
Evaluation and Iteration
Building together
Session 9
Positioning Your Project (CV, GitHub, LinkedIn)
App Deployment
Building together
Session 10
Final Project Presentations
Project showcase with parents
First half · Sessions 1 to 5前半
Foundations.
During the first half, students explore applications, foundational AI concepts, and AI programming skills. They take part in group discussions about modern AI, work on hands-on assignments individually, and share what they make with each other.
- Applications
- Each session starts with applications. For example: How does ChatGPT actually work? How is AI being used in science, business, or daily life?
- Conceptual Intuition
- We cover the intuition, and some of the math, behind the important machine-learning ideas. Examples include neural networks, decision trees, and logistic regression.
- AI Programming Skills
- We guide students through small projects in Python. For example: classifying images, sorting reviews as positive or negative, or training a small model on real data.
Second half · Sessions 6 to 10後半
Project.
During the second half, students apply what they learned to a project they choose themselves and build session by session with the instructor. Alongside the technical work, they take part in discussions about AI ethics and present their finished project at a parent showcase.
- AI Project and Custom App
- Students work one-on-one or in small groups with the instructor to build a hands-on, useful project, ending with something deployable they can share. They choose from a range of project paths and build a portfolio they can show to parents and use in the future.
- Career and Portfolio Workshops
- Workshops include instructor spotlights on AI research and industry experience, and how to position project work on platforms like GitHub and in a portfolio. Older students aiming for university or internship applications get specific guidance on showing their work.
Recent projects近期項目
Things students have made.
Example tracks課程例子
Lessons are shaped around each student.
Two recent examples below. Every new student gets their own mix, built around their interests and what they want to make.
A younger student exploring AI through study and creativity
For example, a younger student (typically 10 to 14) using AI as a study and creative tool.
They learn to use AI as a study partner rather than an answer machine. They practise asking better questions, work with the Socratic method (AI gives hints, asks questions, quizzes them), and create with AI through visual storytelling, characters, mini comics, writing, and simple websites.
A possible final project: a personal study agent that helps them revise a school subject, alongside a creative project like a story, a visual world, a website, or an art piece.
A teenager focused on founder skills and their own projects
For example, an older teen (typically 14 to 18) interested in founder skills, projects of their own, and using AI seriously.
They learn context engineering: giving AI the right background, examples, and feedback so it works at a higher level. They explore AI for pitch decks, founder narratives, outreach, and market research, and learn how AI agents work and how to use them to plan, test, and improve projects.
A possible final project: an AI-assisted founder workflow around one idea they care about. A pitch deck, a landing-page outline, customer outreach, social content, and a simple prototype.
How lessons work課程詳情
What every term includes.
- Format
- Private 1:1 or small group up to 4
- Prior experience
- None required. Interest in AI helps.
- Session length
- 60 to 90 minutes
- Term length
- 10 sessions
- Final project
- A personal AI workflow each student keeps using
- Location
- Causeway Bay, Hong Kong, or online
Pricing學費
What lessons cost, by the hour.
Home visit
Most popular
From HK$1,200 / hour
Causeway Bay classroom
HK$1,000 / hour
Online
HK$1,000 / hour
Group classes by enquiry. HK$400 to HK$700 per person depending on group size.
For parents家長
Small classes, careful feedback, clear next steps.
The first lesson gives us a read on how the student thinks. They make something, explain their choices, and leave with a recommended next step.
Classes are small and structured.
Book a trial lesson