Teaching machines

An introduction to Artificial Intelligence for curious young minds.

Teaching Machines is a beginner-friendly AI course for learners aged 14–18. Through hands-on activities and accessible programming tools, students explore how machine learning works—and what it means for their future. The course also emphasizes ethical thinking and responsible tech use.

Across the globe, AI is transforming economies, communication, and decision-making – but most young people don’t know how it works. For students in crisis-affected or under-resourced contexts, this gap is even wider. Teaching Machines introduces foundational concepts in artificial intelligence and machine learning in a hands-on, age-appropriate way.

Rather than treating learners as passive users of AI tools, the course empowers them to:

Experiment with building simple models

Understand how data informs predictions

Critically evaluate ethical implications

By demystifying how machines “learn” and showing how systems can reflect human biases, Teaching Machines helps students think both like scientists and like citizens – equipping them with the awareness and confidence needed in an AI-driven future.

Learning outcomes

Students completing Teaching Machines will:

Understand how supervised machine learning systems work

Learn the basics of training and testing simple models

Explore key concepts such as data patterns, neural networks, and prediction

Reflect on ethics, bias, and real-world implications of AI technologies

Lesson overview

Lesson 1

What is AI? Exploring basic definitions and use cases

Lesson 2

Understanding supervised learning and classification

Lesson 3

Building and training a simple model

Lesson 4

Testing, debugging, and evaluating results

Lesson 5

Introduction to neural networks

Lesson 6

Ethics, bias, and responsible AI

PROGRAM OVERVIEW

Course goal
Introduce the fundamentals of AI and machine learning through hands-on, ethical engagement
Content
6 lessons (~10–12 hours total)
Duration
3–5 sessions or up to 2 weeks, depending on context
Instruction method
Project-based, facilitator-led sessions (in-person or hybrid)
Student ages
14–18 years old