AI for All: Initiatives, Pathways, and Training Opportunities

Event Overview

In an era where Artificial Intelligence is rapidly reshaping decision-making processes, skills, and everyday practices, education plays a central role in enabling individuals to understand, critically assess, and responsibly engage with these transformations. This seminar, titled “AI for Everyone: Initiatives, Pathways, and Learning Opportunities,” explores how accessible and inclusive AI education can be developed to serve diverse audiences—from beginners to professionals already working in the field.

The event is delivered by Dr. Matteo Busso, postdoctoral researcher at the University of Trento and member of the DataScientia Foundation. His work focuses on person-centered AI, AI literacy, data literacy, and innovative educational approaches that translate research into scalable learning resources such as MOOCs, training programs, and practical tools for responsible AI and data use.

During the seminar, Dr. Busso will present key educational initiatives developed within the Department of Information Engineering and Computer Science at the University of Trento, in collaboration with the Knowdive group and DataScientia, as well as with European partners. Special attention will be given to two strategic projects—PNRR EDVANCE EAI and Erasmus+ AI4EVERYONE—which aim to expand access to high-quality AI education through modular, flexible, and accessible learning pathways.

Practical Information

✦ Event Location

Location: CLab – School of Innovation, Trento
Date: 23 April 2026
Time: 15:30 – 16:30
Format: In-person seminar (with online participation available)

✦ Event Registration

Participation is free and open to all, but seating is limited. We strongly recommend registering in advance to secure your spot.

Register here for in-person attendance
Join the webinar via Zoom (register here)

About the Speaker

Matteo Busso is a postdoctoral researcher at the University of Trento, specializing in person-centered artificial intelligence, AI literacy, data literacy, and education.

With a PhD in Computer Science and an interdisciplinary background combining sociology and intercultural communication, his work focuses on translating research into scalable and accessible educational resources, including MOOCs and course design, practical tools for responsible AI and data use, contributions to European projects (Horizon, Erasmus+) and development of GDPR-compliant data infrastructures. He is actively involved in initiatives that bridge research, education, and real-world applications of AI.