Data science has recently flourished in academic research and in industrial applications as a multidisciplinary approach based on knowledge, data integration, development of algorithms and methods of analysis, software and hardware technologies for computation, and human interaction approaches for visualization and exploration of data.The approach is intrinsically interdisciplinary and therefore it's hardly experienced by the students of the Politecnico.For this reason, this fast and light crash course proposal has been designed to introduce the multidisciplinary aspects, the potential and the challenges that data science offers.The course is aimed mainly at students that are at the end of their B.Sc. at Politecnico (e.g., third year students), coming from any school and course, with the aim of promoting interdisciplinarity and the integration of skills.It consists in a compact and introductory treatment of the interdisciplinary themes that enable the modern academic research and industrial development activities related to data science, with some hands-on development sessions on realistic cases. Therefore it does not replace any of the traditional courses that deal with the disciplines covered. On the contrary, it aims at fostering interest and involvement in these subjects.The course consists of 15 hours of multidisciplinary lessons, organized in the following modules.1- Statistics and Mathematics: statistical foundations of data science, problems and risks, examples of some techniques applicable to real cases;2 - Computer science: architectures for open and scalable big data, techniques and tools for scalable data analysis;3 - Data Visualization: principles, role and impact of data visualization, exploratory and interactive approaches, description and storification.4- Hands-on: python practical development module covering examples of the three previous modules.5 - Applications: examples of disciplines that intervene to complement the technical capacity provided by the basic disciplines. This module covers two specific domains (in particular, sociology and epidemiology, introduced by external experts), and provides an introduction to the problems, requirements, applicable techniques and results that can be achieved by combining approaches from various disciplines.The lessons are covered by professors of the Politecnico for the first three modules:- Statistical module (3h): Simone Vantini- Data science module (4h): Marco Brambilla- Visualization module (2h): Paolo Ciuccarelli- Domain-specific module (2h): external teachers- Hands-on module (4h): doctoral students of the data-science labThe activity will be complemented by a group project, to be carried out by the students, in mixed teams (engineers, designers, architects, etc.).