1. General Introduction to Machine Learning (ML), Foundations & Pedagogy

This course provides a broad introduction to the fundamental concepts, methods, and educational approaches of Machine Learning (ML). Students will explore the theoretical foundations of ML, including supervised and unsupervised learning, model evaluation, data representation, and ethical considerations in AI systems. In parallel, the course examines pedagogical strategies for teaching and communicating ML concepts effectively across diverse learning environments. Emphasis is placed on conceptual understanding, critical thinking, and practical applications rather than advanced mathematical implementation.