Chapter 5: Components of AI

This chapter provides an in-depth exploration of the foundational components that enable artificial intelligence to function effectively. Students will examine the essential building blocks of AI systems, such as data, algorithms, models, training methods, evaluation metrics, and deployment infrastructures. Each concept is unpacked with beginner-friendly explanations and real-world examples to remove ambiguity and ensure clarity. Students will also explore core learning methods including supervised, unsupervised, and reinforcement learning, with direct application to real-world AI systems like spam detection, customer segmentation, and robotics. The chapter concludes with a hands-on lab using Google Teachable Machine to allow students to create, train, and test an AI model themselves, reinforcing the importance of quality data and responsible training processes.