This foundational chapter provides a comprehensive exploration of Artificial Intelligence (AI) and
Machine Learning (ML) applications in educational contexts. Beginning with fundamental definitions
and historical perspectives, the chapter examines the evolution of intelligent systems in learning
environments, from early computer-assisted instruction to contemporary adaptive learning platforms.
The discussion encompasses core technological components including Natural Language Processing,
neural networks, and intelligent tutoring systems, while analyzing their pedagogical implications. The
chapter addresses the transformative role of AI in modern educational methodologies, emphasizing
data-driven decision-making and personalized learning approaches. Through examination of predictive
analytics, automated assessment systems, and behavioral tracking models, the chapter illustrates how
ML technologies are reshaping educational practices. Finally, it presents a balanced analysis of
implementation challenges and opportunities, providing insights into institutional readiness and digital
transformation strategies essential for successful AI integration in educational settings.