Overview
This service offers training events on data science and AI. They gather PhD students, early career researchers, and practitioners to learn methods for data analysis, machine learning, and responsible AI, with a strong focus on ethics, governance, and European data policies. Mornings feature lectures and keynotes; afternoons are dedicated to hands‑on group projects evaluated by experts.
Themes encompass information, political, and social dynamics, as well as open science, sustainability, and data altruism, all set within a collaborative environment that integrates technical work with networking and cultural activities.
Purpose and Objectives
Our Summer Schools equip participants with the knowledge, skills, and perspectives needed to address complex societal challenges using data and AI. 
Specifically, our programs aim to:
- Provide advanced training in data science, machine learning, and AI
- Foster interdisciplinary understanding of social, political, and technological systems
- Promote responsible and ethical data use, aligned with European policies
- Encourage collaboration and networking among participants and experts
- Bridge the gap between theoretical knowledge and real-world applications
By combining technical excellence with societal awareness, our Summer Schools support the development of responsible data professionals.
Interdisciplinary and Thematic Structure
Our schools are typically organized around thematic tracks addressing key domains such as:
- European data frameworks and open science policies
- Information and disinformation dynamics
- Political and social dynamics
- Health, sustainability, and societal applications of AI
- Ethics, privacy, and trustworthy AI
- Responsible data science
This structure ensures an understanding of data-driven phenomena, combining technical, social, and policy perspectives.
