Laurea Magistrale (MSc) in
Artificial Intelligence and Data Engineering
The University of Pisa, founded in 1343, has a strong international reputation. According to the latest edition of the Academic Ranking of World Universities (ARWU) 2022, the University of Pisa is ranked between 151st and 200th in the world and is 4th in Italy. According to the QS World University Ranking 2022, the University of Pisa ranks 388th worldwide and is 7th in Italy.
The MSc (laurea magistralis) provides a solid in-depth education that enables the graduates to design and implement, on the one side, systems for efficiently managing large amount of data and extracting useful knowledge from this data, and, on the other side, intelligent systems by exploiting artificial intelligence techniques. The MSc advances the student knowledge portfolio, in both computer infrastructures for intensive data management and methods for data analytics and artificial intelligence. These competences allow graduates to interact with professionals from different backgrounds in different domains and contexts, where data processing is required, as well as to complete their mastering of computer engineering.
The course is structured to receive not only students with a strong background in computer engineering, but also students coming from different disciplines with at least a proper knowledge of programming languages. Graduates in computer engineering will have the opportunity for going in-depth into engineering and methodological disciplines; the graduates in other disciplines will complete their knowledge of base methodologies of computer engineering, including operating systems, computer networks, databases, algorithms and advanced programming. Then, all the students are presented with the following subjects: optimization techniques and game theory, business processes and entrepreneurship, non-relational databases, distributed databases, query optimization, data warehouses, cloud computing and in-frastructures, multimedia information management, data mining and machine learning, computational intelligence and deep learning, process mining and intelligence, symbolic artificial intelligence, swarm and evolutionary intelligence. Each course is characterized by lectures and labora-tories, with particular attention to to-day’s applications that require to efficiently process big data.
Degree Programme class
LM-32 - Computer systems engineering
Department
Learning activities
Professional profiles
Big Data Engineer
Data Service/Platform Engineer/Manager
Data Analytics Engineer/Manager
Data Technologies Engineer
Big Data Infrastructure Engineer
Business Process Engineer/Manager
Artificial Intelligence Software Engineer/Architect
Machine Learning Engineer/Architect
Big Data/AI Consultant
Researcher in public/private labs
Why to enroll?
Be a leader in the progress of Big Data/AI technologies
Foster the culture of data-driven decision making
Actively driving data engineering industry strategies
Take managerial positions in companies working within Big Data/AI or with Big Data/AI technologies
Study in a challenging international environment, with strong focus on research and innovation and ties to the major international players in the ICT world
Pisa is a unique ICT district, one of the largest in Italy, hosting many hi-tech enterprises
"MENTORSHIP, diversity is our strenght!". To encourage the creation of university mentorship schemes supporting the social and academic inclusion of students with migratory background and refugees. Here’s our mentors!
(*) Language used in learning activities
Compulsory activities are in English and elective activities are in English or Italian. The total of ECTS given in English is sufficient to complete the programme and take the degree, hence knowledge of the Italian language is not a prerequisite. However, learning activities covering basic subjects in computer engineering, meant for admitted students not having a strong background in this field of study, are only taught in Italian.
For further information, contact us by sending an e-mail to didattica_INGINF@dii.unipi.it
Coming from abroad? Please get in touch with our international office (international@ing.unipi.it)