This course series introduces the fundamental concepts, foundations, and pedagogical approaches of Machine Learning (ML), while exploring its practical applications across educational and real-world contexts. Participants will engage with interactive activities and examples that demonstrate how ML systems function and how AI-related concepts can be taught effectively. The courses also examine ethical considerations and promote a human-centered mindset, particularly in early childhood education, emphasizing fairness, inclusion, privacy, and responsible technology use. Finally, participants will learn how to transform ML concepts into meaningful classroom experiences by designing and implementing creative, learner-centered, ML-inspired projects that foster critical thinking, collaboration, and digital literacy.

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 ...

2. ML Applications and Activities

This module explores practical applications of Machine Learning across various domains, including healthcare, finance, education, transportation, ...

3. Ethics of ML and a Human-Centered Mindset in Early Childhood Education

This module examines the ethical dimensions of Machine Learning (ML) and the importance of adopting a human-centered approach in early childhood ...

4. From Concept to Classroom: Designing and Implementing ML-Inspired Projects

This module focuses on the design and implementation of Machine Learning-inspired educational projects within classroom settings. Participants will...