Master in Data Science and Engineering

Data Science and Engineering is a graduate field that combines statistical analysis, computer science, and engineering methods to extract insight from large and complex datasets. Coursework typically includes machine learning, database systems, data mining, statistics, and software engineering, alongside subjects addressing how data infrastructure is designed and managed at scale. Students learn to collect, process, and analyze data, build predictive models, and design systems capable of handling large volumes of information, often working with real datasets to develop practical technical skills. The field also frequently covers topics such as data visualization and the ethical and privacy considerations involved in working with data about individuals and organizations. This master's degree in Data Science and Engineering is offered by Politecnico di Torino, located in Torino, Italy, is taught in English, and spans two years. Graduates typically pursue careers as data scientists, data engineers, machine learning engineers, and analysts across industries including technology, finance, healthcare, and manufacturing, wherever organizations rely on data to inform decisions. Some move into roles focused specifically on building and maintaining the infrastructure that supports large-scale data processing, while others focus more on analysis and modeling to solve specific business or scientific problems. Because nearly every sector now generates and relies on data, graduates from this field find opportunities across a wide range of organizations, from established corporations to technology startups and research institutions. The combination of statistical, computational, and engineering skills equips graduates to work on the full pipeline of data-driven projects, from raw data collection through to actionable insight.