About DSEH
The use of the term “data science” is increasingly common, as is “big data.” But what does it mean? Is there something unique about it? What skills do “data scientists” need to be productive in a world deluged by data? What are the implications for scientific inquiry?
Vasant Dhar. 2013. Data science and prediction. Commun. ACM 56, 12 (December 2013), 64–73.
We have run out of adjectives and superlatives to describe the growth trends of data. The technology revolution has brought about the need to process, store, analyze, and comprehend large volumes of diverse data in meaningful ways. However, the value of the stored data is zero unless it is acted upon. The scale of data volume and variety places new demands on organizations to quickly uncover hidden relationships and patterns. This is where data science techniques have proven to be extremely useful. They are increasingly finding their way into the everyday activities of many business and government functions, whether in identifying which customers are likely to take their business elsewhere, or mapping flu pandemic using social media signals.
Vijay Kotu, Bala Deshpande. 2019. Data Science Concepts and Practice. Morgan Kaufmann.
The Master of Science in “Data Science for Economics and Health” (DSEH) aims to provide a modern, effective educational programme for students interested in data science issues, with focus on applications to Economics and Health.
The programme started in 2018 as “Data Science for Economics”, and it has been re-designed in 2022 to join the emerging “LM-DATA” CUN class. In 2025, the programme has been renamed to “Data Science for Economics and Health” with the inclusion of a new path on Health and additional elective courses on actual applications of Data Science to environment, sustainability and climate change.
The DSEH programme aims to provide advanced education on methodological methods and tools in computer science, statistics, and mathematics designed to interpret and analyze complex phenomena in the fields of economics and health. DSEH focuses on the analysis of the effects of economic policies, as well as the evaluation of actions and any other activity related to the sectors of economy, environment, marketing and business. Moreover, the programme aims to provide the foundations of epidemiology and biostatistics on which to graft the acquired knowledge of data analysis. The course of study enforces the construction of solid methodological bases by addressing topics of the economic theory, decision theory under uncertainty conditions, micro-econometric techniques and time-series analysis. It also fosters the study of emerging data management technologies and scalability of analysis systems in cloud environments, as well as machine learning techniques for the extraction and classification of information.
DSEH is conceived as a flexible educational programme with an important number of elective courses. Supported by the tutors, students customize the study plan according to their own inclinations, by choosing elective courses within three different educational paths focused on "Data Science", "Economic Data Analysis", and “Health”. The external stakeholders of DSEH are constituted by selected companies and organizations focused on data science missions with operational headquarters in Italy and Lombardy, and they are widely involved in the programme development in the form of lab and internship opportunities.
Given the multidisciplinary nature of the acquired knowledge and skills, the graduates of DSEH can work in a variety of professional areas: small, medium, and large IT companies and research centers, companies and public bodies focused on big data management, R&D labs, innovative start-ups, healthcare companies, biomedical and pharmaceutical industries, economic and financial consulting firms, Public Administrations, National Statistical Institutes, National Banks.
Given their solid methodological education, the graduates of DSEH can continue their academic experience in a PhD programme; possible scientific fields are Computer Science, Mathematics, Statistics, and Economics.