Università di PISA

Master in ARTIFICIAL INTELLIGENCE AND DATA ENGINEERING

Pisa, Italy 2 years Taught in English Open to international students

Why students choose this program

  • Taught in English
  • No application fee

About the Program

This two-year master's programme at Università di Pisa, taught in English, sits within the fields of artificial intelligence and data engineering, which together address how large volumes of data are collected, processed, and used to build intelligent systems. Artificial intelligence as a discipline studies methods for building systems that can learn from data, reason, and make predictions or decisions, drawing heavily on machine learning, statistics, and optimization. Data engineering complements this by focusing on the infrastructure and pipelines needed to collect, store, and process data at scale, a necessary foundation for any practical artificial intelligence application. Students in programmes combining these areas typically study machine learning and deep learning, natural language processing or computer vision, database and distributed systems, and the software engineering practices needed to build and deploy data-intensive systems. Coursework often includes hands-on work with real datasets, building and evaluating models, and designing the data pipelines that support them, reflecting the practical, systems-oriented nature of the field alongside its theoretical foundations in mathematics and statistics. Graduates from this area of study pursue roles such as machine learning engineer, data engineer, artificial intelligence researcher, and data scientist across technology, finance, healthcare, and manufacturing sectors, among others. Some move into research positions in academia or industry laboratories, contributing to advances in machine learning methods, while others focus on the engineering side, building the scalable systems that make large-scale data processing and model deployment possible. The combination of algorithmic and infrastructure skills is increasingly sought after as organizations look to move artificial intelligence projects from experimentation into production, making this an area of growing relevance within computing education and industry.

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