Course Structure:
Ages: 14-18 Assignment Type: General Total Time: 230 minutesLessons:
This foundational unit introduces neural networks, datasets, and machine learning models. Through case studies, creative projects, and simulated activities, students explore the different types of learning (supervised, unsupervised, and reinforcement), simulate a neural network, and examine how human decisions shape algorithmic fairness.
Summary:
High school students uncover how AI works and how it influences daily life.
Lessons
1. What is AI? (40 minutes)
Distinguish between AI and non-AI systems using real-world examples.
2. Can Machines Really Learn? – (40 minutes)
Explore data-driven predictions through Google's Quick Draw and identify biases in datasets.
3. What Is an Algorithm? (40 minutes)
Design and test algorithms that guide decision-making, and discuss how algorithms are optimized for user experiences.
4. How Do Machines Learn? (40 minutes)
Investigate different learning types (supervised, unsupervised, and reinforcement)
5. Neural Networks Explained (40 minutes)
Simulate how neural networks process and refine information.
6. Bias in Artificial Intelligence (30 minutes)
Analyze causes of algorithmic bias and propose ethical solutions.