The Data Science Summer School offers a broad multi-disciplinary perspective on the different pillars of data science, including data mining and big data analytics, machine learning and AI, network science and complex systems, digital ethics, computational social science and applied data science, featuring lectures by high-level international scholars.
Data Science is emerging as a disruptive consequence of the digital revolution. It is based on the combination of big data availability, sophisticateddata analysis techniques, and scalable computing infrastructures. Data Science is rapidly changing the way we do business, socialize, conduct research, and govern society. It is also changing the way scientific research is performed. Model-driven approaches are supplemented with data-driven approaches. A new paradigm emerged, where theories and models and the bottom up discovery of knowledge from data mutually support each other.
Given the interdisciplinary nature of Data Science this summer school offers lectures by high-level scholars from different domains, giving to the students the skills to exploit data and models for advancing knowledge in different disciplines, or across diverse disciplines (e.g. biology, economics, medicine, etc).
The main topics of the summer school are related to big data analytics, i.e., extraction of knowledge from big data, machine learning, i.e., providing an overview of the main techniques used to automatically learn and improve from experience, and complex systems, i.e., methods and technologies particularly related to network science. Moreover, lectures will highlight the ethical implications that data science could lead and the countermeasures that each data scientist can apply to perform analysis with respect to the individuals involved in the data.