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For upcoming international students
For upcoming international students
(academic year 2025/2026)
(academic year 2025/2026)
The University of Pisa proposes a series of webinars dedicated to the procedures to follow after receiving the admission letter, to better support your entry process.
The meetings will be held on the Unibuddy platform from 28 to 30 April 2025 in five different languages.
Registration is required via the following link:
https://events.unibuddy.co/universita-di-pisa/virtual/67d853d56d9f8c00284ab49a
Webinar schedule:
April 28, 2025 – 12:30 pm: Chinese language
April 28, 2025 – 1:15 pm: Portuguese language
April 28, 2025 – 2:00 pm: Turkish language
April 29, 2025 – 1:30 pm: Arabic language
April 30, 2025 – 2:00 pm: English language
Topics covered: Post-admission procedures, Pre-enrolment process, Q&A session
For international students
For international students
International students can refer to a Telegram group called internationalstudentsclubunipi (https://t.me/internationalstudentsclubunipi), which is dedicated to information and initiatives dedicated to them. We suggest using this opportunity for better integration into the University community.
Moreover, they can contact our “Ambassadors” for any question through the Unibuddy service at https://unibuddy.unipi.it/
FoReLab Degree Certificate
FoReLab Degree Certificate
As part of the educational initiatives of the FoReLab project of the Department of Information Engineering (winner of the Call for Departments of Excellence of the MUR 2023/2027), an excellence training course is activated mainly, but not exclusively, for students who have interests in the research topics of the project.
As part of the educational initiatives of the FoReLab project of the Department of Information Engineering (winner of the Call for Departments of Excellence of the MUR 2023/2027), an excellence training course is activated mainly, but not exclusively, for students who have interests in the research topics of the project.
To get the FoReLab degree certificate, a student enrolled in the MSc in Artificial Intelligence and Data Engineering (AIDE) must:
include in her/his study plan as "Elective course - free choice (attività a scelta dello studente)" a 9 CFU activity chosen from the "FoReLab group" (selected from the study plan of the MSc provided by the Department of Information Engineering, for the relevance of their respective objectives and contents to the FoReLab topics);
develop a thesis work aimed at addressing and solving a state-of-the-art research problem that is relevant to the FoReLab project topics;
write the thesis in English.
The suggested FoReLab group from which the interested student can choose an activity is as follows:
Advanced Computer Networking (aka Advanced Network Architectures and Wireless Systems) - 9 CFU
Dependable and Secure Systems (aka Formal Methods for Secure Systems) - 9 CFU
Foundations of Cybersecurity - 9 CFU
Industrial Applications – 9 CFU
Internet of Things - 9 CFU
Performance Evaluation of Computer Systems and Networks – 9 CFU
System and Network Hacking – 9 CFU
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
Degree Programme class
LM-32 - Computer systems engineering
Department
Department
Learning activities
Learning activities
Professional profiles
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?
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
(*) 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)
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