AIVAST Machine Learning Basics
An approachable intro to machine learning: data, features, supervised vs unsupervised learning, evaluation, and fairness. No-code first with optional Python extensions.
What students will learn
- Train a simple classifier and evaluate it
- Understand accuracy, precision, recall, and bias
- Visualize data and reason about model behavior
Course structure
8 modules · 34 lessons · 6 weeks
Module 1: Core concepts & practice
4–6 lessons · Watch → Learn → Try → Think → Quiz → Create
The first lesson of Module 01 is unlocked for everyone — no sign-in required.
Module 2: Core concepts & practice
4–6 lessons · Watch → Learn → Try → Think → Quiz → Create
Module 3: Core concepts & practice
4–6 lessons · Watch → Learn → Try → Think → Quiz → Create
Module 4: Core concepts & practice
4–6 lessons · Watch → Learn → Try → Think → Quiz → Create
Module 5: Core concepts & practice
4–6 lessons · Watch → Learn → Try → Think → Quiz → Create
Module 6: Core concepts & practice
4–6 lessons · Watch → Learn → Try → Think → Quiz → Create
Module 7: Core concepts & practice
4–6 lessons · Watch → Learn → Try → Think → Quiz → Create
Module 8: Core concepts & practice
4–6 lessons · Watch → Learn → Try → Think → Quiz → Create
Safety & academic honesty
Every course includes safety reminders, prompts students never share, and a clear academic-honesty framework that aligns with most school policies. Students are taught to disclose AI use appropriately.