Analyzing complex networks and developing machine learning and graph neural network models with Python and NetworkX, from static graphs to temporal networks and responsible AI.

Reading, cleaning, visualizing, and interpreting data with Python: a practical journey from raw tables to informed decisions, with no prior programming or statistics knowledge required.

MOOC helps participants understand how to design and evaluate interactive systems, combining HCI fundamentals with emerging AI-driven interactions.

This MOOC equips participants with the knowledge to understand, evaluate, and apply AI technologies across marketing and business functions, enabling data-driven decision-making and responsible AI adoption.

This MOOC teaches participants how to strategically apply AI as part of a broader digital innovation journey, transforming promising opportunities into practical, value-generating organizational solutions.

Criteria and good practices for integrating artificial intelligence into university communication: clarity, consistency, inclusion and institutional responsibility.

Dai grafi complessi alle Graph Neural Networks: Machine Learning per reti reali con Python

Come utilizzare l’Intelligenza artificiale per percorsi creativi con le artiterapie

Quando il gioco diventa apprendimento, innovazione e futuro

Leggere, capire e usare i dati nel mondo reale