Demystifying AI: An Introduction to Machine Learning

Course Description

Machine learning (ML) powers the technologies that shape our world — from recommendation systems to autonomous vehicles. But how do machines actually “learn”? This course introduces the core ideas behind machine learning through accessible, hands-on activities designed for curious minds with no prior coding experience.

Participants will discover how machines use data to recognize patterns, make predictions, and learn through feedback. We’ll explore the main branches of ML — supervised, unsupervised, and reinforcement learning — through engaging classroom demonstrations and interactive projects.

In the lab, students will build and test their own models using the ML for Kids Scratch extensions, gaining experience with classification, clustering, and simple reward-based learning in a fun, visual environment. As their confidence grows, they’ll take their first steps into Python, experimenting with how real-world ML programs are structured and how data drives learning.

By the end of the course, participants will understand how machines can be “trained,” how models improve with experience, and how ML concepts appear in everyday technologies. More importantly, they’ll leave inspired to continue exploring how intelligence can emerge from data — one model at a time.