Artificial intelligence and data engineering
Course Description
Level: Second Level Degree
Degree Class: LM-32 - Computer systems engineering
Department: INFORMATION ENGINEERING
Admission: Free
CFUs: 120
Duration: 2 years
Website: https://computer.ing.unipi.it/aide-lm
English
Pisa
This course trains specialised engineers capable of creating, developing, analysing and integrating computer systems to efficiently manage large amounts of data and intelligent systems using the latest artificial intelligence methodologies and techniques.
The skills acquired during the course of study enable graduates to interact across various sectors and contexts that require data processing. The course focuses on the study of disciplines such as:- Data Mining and Machine Learning
- Large-scale and Multi-structured Databases
- Optimisation Methods and Game Theory
- Cloud Computing.
The curricular requirements for access to the Master’s Degree Course are as follows:
- Possession of a degree in the following classes:
--- L-8 Information Technology Engineering
--- L-30 Physics
--- L-31 Computer Science
--- L-35 Mathematics
- Possession of a degree in another class, having obtained
--- at least 36 CFUs in the following SSDs (academic disciplines): MAT/02, MAT/03, MAT/05, MAT/06, MAT/07, MAT/08, MAT09, FIS/01, FIS/03;
--- at least 9 CFUs in the following SSDs (academic disciplines): ING-INF/05, INF/01;
--- at least 9 CFUs in the following SSDs (academic disciplines): ING-IND/35; SECS-P/08
For candidates with a qualification obtained abroad and recognised as suitable, the verification of requirements is based on the candidate’s specific educational background.
Proficient knowledge of English at least at level B2, according to the Common European Framework of Reference for Languages, is also required.
The assessment of personal preparation is based on the candidate’s academic background and may include an oral interview.
For admission to the Master’s Degree Course in Artificial Intelligence and Data Engineering (Class LM-32) students require a Bachelor’s degree or another qualification obtained abroad and recognised as suitable. The applicant is required to submit an application along with attachments, including at least the degree certificate, or its equivalent, and the examination transcripts.
Based on the criteria illustrated below, the curricular requirements and the adequacy of personal preparation for access to the Master’s Degree Course are established in accordance with art. 6, paragraph 2, of Ministerial Decree 270/2004.
Admission to the Master’s Degree Course in Artificial Intelligence and Data Engineering Class LM-32 is decided on the basis of the existence of both (curricular and preparation) requirements. The Course Board appoints an Evaluation Instruction Panel (Commissione Istruttoria di Valutazione, CIV), consisting of two or more lecturers tasked with:
- reviewing applications for admission,
- assessing candidates’ CVs,
- checking whether candidates meet curricular and personal requirements,
- proposing to the Course Board the admission or non-admission of candidates,
- indicating how the missing requirements can possibly be met.
Alternatively, the candidate, who graduated from an Italian university, meets the curricular requirements if:
1) They possess a degree in the following classes: L-8 Information Engineering; L-30 Physics; L-31 Computer Science; L-35 Mathematics;
2) They possess a degree in another class, having obtained:
- at least 36 CFUs in the following SSDs (academic disciplines): MAT/02, MAT/03, MAT/05, MAT/06, MAT/07, MAT/08, MAT09, FIS/01, FIS/03;
- at least 9 CFUs in the following SSDs (academic disciplines): ING-INF/05, INF/01;
- at least 9 CFUs in the following SSDs (academic disciplines): ING-IND/35; SECS-P/08
If a candidate possesses a foreign degree, the CIV Panel will review the curricular requirements by considering the duration of each course and the content of the corresponding exams.
Proficient knowledge of English at least at level B2, according to the Common European Framework of Reference for Languages, is also required. The possession of such requirement can be certified by students at the time of enrolment or, if no certification is available, it will be verified during the admission application review when assessing the student’s personal preparation.
In accordance with the University Academic Regulations, the CIV Panel:
- may propose to the Course Board to either accept or reject the candidate’s application based on the evaluation of the documents submitted with the application for admission,
- may propose to the Course Board that the candidate be referred to the admission interview in accordance with the procedure described below.
Admission interview
The purpose of the admission interview is to confirm that the candidate has the required preparation to effectively undertake their Master’s studies, especially regarding fundamental knowledge of mathematics and computer engineering. The interview programme, as determined by the CIV Panel, will be communicated to the candidate in advance by the president of the Course of Study.
At the end of the interview, the selection board will formulate a final judgement on the candidate’s suitability for admission, highlighting any missing requirements.
Course Evaluations
Contacts
Presidente del Corso di Laurea
Marco Avvenuti
Email: marco.avvenuti@unipi.it
Referente didattico
Barbara Conte
Tel. (+39) 050 2217642
Email: barbara.conte@unipi.it
Unità Didattica del Dipartimento di Ingegneria dell'Informazione: https://www.dii.unipi.it/didattica
Orario di ricevimento: Previo appuntamento telefonico (+39) 050 2217642/692 o via e-mail: didattica@dii.unipi.it
Study Plan
For students enrolled in the academic year 2025/2026
Required
- Optimization methods and game theory (6 CFU) - Primo ciclo semestrale
- Business and project management (9 CFU) - Secondo ciclo semestrale
- Cloud computing (9 CFU) - Secondo ciclo semestrale
- Data mining and machine learning (12 CFU) - Primo ciclo semestrale
- Large-scale and multi-structured databases (9 CFU) - Primo ciclo semestrale
Gruppo a attivita affini o integrative (15 CFU)
- Internet law (6 CFU) - Secondo ciclo semestrale
- Performance evaluation of computer systems and networks (9 CFU) - Primo ciclo semestrale
- Statistics (6 CFU) - Primo ciclo semestrale
- Algorithms and data structures (6 CFU) - Secondo ciclo semestrale
- Databases (9 CFU) - Secondo ciclo semestrale
- Distributed systems and middleware technologies (6 CFU) - Primo ciclo semestrale
- Foundations of cybersecurity (9 CFU) - Secondo ciclo semestrale
- Innovation management (6 CFU) - Secondo ciclo semestrale
- Internet of things (9 CFU) - Secondo ciclo semestrale
- Methods of biomedical image formation and processing (6 CFU) - Primo ciclo semestrale
- Mobile and social sensing systems (6 CFU) - Secondo ciclo semestrale
- Programming laboratory (6 CFU) - Primo ciclo semestrale
- Computer networks (9 CFU) - Primo ciclo semestrale
- Robotics and intelligent machines (6 CFU) - Secondo ciclo semestrale
- Operating systems (9 CFU) - Primo ciclo semestrale
Required
Career opportunities
- Big 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
- Researchers
Enrolment
To enrol, you must hold:
- a university degree recognised as suitable under current legislation
- the curricular requirements specified in the regulations of the degree courses
- adequate personal preparation, assessed according to the procedures defined in the regulations of the degree course.
Pre-registration for the academic year 2026/2027