Student's Guide

The programme comprises 120 CFU over two years. The first year (60 CFU) is common to all students. In the second year (60 CFU), each student selects one of four curricula and, where applicable, one of the study paths defined in the Manifesto degli Studi. Each path includes 18 CFU of curricular courses, consisting of one 12-CFU course and one 6-CFU course. The remaining credits comprise 12 CFU of free-choice courses, 6 CFU of Other Knowledge, 8 CFU for an internship/stage or project, and 16 CFU for the final examination. 

First Year (common to all curricula) — 60 CFU 

1st semester 

• Mathematical Methods for Data Science — 6 CFU (MAT/08; MATH-05/A). 

• Statistical Learning & Data Analysis — 12 CFU (SECS-S/01; STAT-01/A). 

• Fundamentals of Programming & Data Management— 12 CFU (ING-INF/05; IINF-05/A). 

2nd semester 

• Hardware and Software for Big Data — 12 CFU (ING-INF/05; IINF-05/A). 

• Data Mining & Machine Learning — 12 CFU (SECS-S/01 and INF/01; STAT-01/A and INFO-01/A). 

• Theory and Ethics of Big Data and AI — 6 CFU (M-FIL/03; PHIL-03/A). 

Second Year — 60 CFU 

Students complete the 18 curricular CFU associated with one of the curricula and study paths listed below. The 12-CFU and 6-CFU courses shown for each PdS form one curricular combination and must be selected together. 

Curriculum Fundamental Sciences 

Referenti: Prof. Giuseppe Longo (Department of Physics) and Prof. Roberta Siciliano (DIETI). This curriculum comprises three study paths; students select one: 

• Physics inspired Methodologies: Advanced Statistical Learning and Modeling (12 CFU) + Physics Informed Machine Learning (6 CFU). 

• Mathematical Methodologies: Algorithms and Parallel Computing and Computational Complexity (12 CFU) + Operational Research (6 CFU). 

• Life Sciences: Biochemistry and Computational Biochemistry (12 CFU) + Cell and Molecular Biology (6 CFU). 

Curriculum Information Technologies 

Referente: Prof. Vincenzo Moscato (DIETI). This curriculum comprises five study paths; students select one: 

• Text and Speech Processing: Information Retrieval and Text Mining (12 CFU) + Speech Processing (6 CFU). 

• Signal and Video Processing: Information Theory and Signals Theory (12 CFU) + Image and Video Processing for Autonomous Driving (6 CFU). 

• Robotics and Statistics: Robotics (12 CFU) + Advanced Statistical Learning (6 CFU). 

• Industrial Applications: Advanced Statistical Learning and Modeling (12 CFU) + Statistical Methods for Industrial Process Monitoring (6 CFU). 

• Design and Security of AI Systems: Algorithm Design and Methods of AI (12 CFU) + Data Security (6 CFU). 

Curriculum Public Administration, Economy and Management 

Organized in collaboration with the Department of Economics and Statistics (DISES). Referente: Prof. Antonio D’Ambrosio (DISES). This curriculum comprises one study path: 

• Computational Statistical Inference and Categorical Data Analysis (12 CFU) + Financial Time Series Analysis (6 CFU). 

Curriculum Intelligent Systems 

Referente: Prof. Giovanni Acampora (Department of Physics “Ettore Pancini”). This curriculum comprises one study path: 

• Quantum Computation and Computational Intelligence (12 CFU) + Generative Artificial Intelligence (6 CFU). 

Activities common to all curricula 

• Free-choice courses (a scelta autonoma dello studente) — 12 CFU — either two 6-CFU courses or one 12-CFU course. The courses listed in Table 2 of the Manifesto are automatically approved. 

• Other Knowledge (Ulteriori conoscenze) — 6 CFU — awarded to international students upon obtaining an Italian-language certificate through the University Language Centre (CLA), or to Italian students for approved technical skills acquired outside the programme, such as seminars, conferences or tutoring activities. 

• Internship / Stage or Project — 8 CFU — carried out either within a University research laboratory (intramural) or at a company, research centre, public body or private organisation in Italy or abroad (extramural), under appropriate supervision. 

• Final Examination (Prova finale) — 16 CFU — discussion of an original dissertation, written and presented in English. 

The complete, officially approved study plan for A.Y. 2026/2027, including course codes, semesters, scientific-disciplinary sectors and the full list of automatically approved free-choice courses, is available on https://data-science.dieti.unina.it/images/Documents/Manifesto_FINALE_Data_Science_LM_26-27_1_en-US.pdf.  

Additional Study Plan Information 

Students must always refer to the Manifesto degli Studi approved for the academic year in which they enrolled. Compulsory and restricted-choice courses do not normally change from year to year unless the Regulations are revised; what may change is the list of suggested free-choice courses. 

The choice of curriculum (and, where applicable, of thematic path) is expressed by regularly registering the corresponding exams; a preventive study plan is not required if the free-choice CFU are obtained exclusively among the courses suggested for the chosen curriculum. If a student instead wishes to use (in whole or in part) the 12 free-choice CFU for courses not included in the suggested lists, an individual study plan must be submitted to the Coordinator of the Degree Programme (cdsm.datascience@unina.it) before the exam is taken, so that the Teaching Coordination Committee (CCD) can verify its consistency with the educational project. In the absence of a submitted study plan, the Student Administration Office will validate only the courses foreseen for the chosen curriculum. 

Students who, on the basis of a project agreed with the internship host, prefer a single, more substantial experience may opt for the “extended internship” pathway (22 CFU, about 550 hours) in place of the standard 8-CFU internship plus 16-CFU thesis; in this case the final examination consists in the discussion of the results of that extended internship. Details are available on the programme’s Thesis/Internship page. 

An 8-CFU internship/project (or, alternatively, a 22-CFU extended internship replacing the standard internship-plus-thesis path — see above) can be carried out at companies, research institutes or public bodies (extramural) or within University laboratories (intramural), normally in the second semester of the second year. A formal agreement between the University and the host institution is required; for institutions with no existing agreement, the Degree Programme Coordinator must be notified in advance so that the agreement can be signed (the process typically requires 20-30 days). 

Detailed procedures, agreement templates and the activity booklet are available on the dedicated section related to “Thesis and Internship” (https://data-science.dieti.unina.it/index.php/studying-with-us/thesis-intership). The Internship Coordinator is Prof. Silvia Rossi (DIETI).

Erasmus+ is the European Union’s mobility programme, allowing students to spend a study period at a partner foreign university with an EU grant, following courses, taking exams and using local facilities without paying additional tuition; activities carried out abroad are recognised, in terms of both credits and grades, by Federico II. Students may also apply to Erasmus Italiano, the national inter-university mobility programme, to spend a period at another Italian university, attend courses and develop part of their thesis in a different academic environment. 

The Erasmus Referente of the Degree Programme is Prof. Roberta Siciliano. Interested students should discuss the available agreements and the compatibility of foreign courses with their study plan with the Referente well before applying. 

Calls, deadlines and further information: “Erasmus and national mobility for Data Science students” section (https://data-science.dieti.unina.it/index.php/13-useful-information-for-the-students/88-erasmus-italiano-national-mobility-opportunities-for-data-science-students) or visit the unina web site dedicated page https://www.unina.it/it/servizi-e-opportunita/opportunita-e-iniziative/erasmus/mobilita-per-studio  . 

Special Educational Paths 

Besides the four curricula described above, no further ad-hoc special paths are currently active. Pursuant to Art. 9 of the Didactic Regulations, contract-based enrolment (“iscrizione a contratto”) remains possible according to the general rules established by the University. 

Customizing the Study Plan 

Pursuant to Art. 9, paragraph 5, of the Didactic Regulations, a student with well-founded reasons may request an individual study plan that also includes training activities different from those listed above, provided they are consistent with the Degree Programme’s educational project for the year of enrolment. The request is submitted to, and approved by, the Teaching Coordination Committee (CCD). 

Requests and questions on study-plan customization should be addressed to the Degree Programme’s mailbox: cdsm.datascience@unina.it.

The final examination consists of the discussion, in English, of an original dissertation presenting the results of work carried out in a University laboratory, a company, a research organisation or a Public Administration; a committee of 7 CCD members evaluates the work. Students cannot start the graduation procedure before completing all but three of the required exams; the dissertation must be prepared using a template provided by the Degree Programme and be uploaded at least 15 days before the graduation session, together with the online graduation request and payment of the graduation fee. 

The graduation calendar and all procedures are published on the “Thesis and Internship” section and it is also available on the website of the Polytechnic and Basic Sciences School (https://www.scuolapsb.unina.it/).

The Degree Programme takes part in DIETI’s orientation initiatives for prospective students — Open Days, presentations of the department “in numbers”, PCTO (school-university pathways) and dedicated advice for prospective students — organised in coordination with the other DIETI programmes and the University’s central orientation services. 

Information for prospective students and the initiatives calendar: “DIETI Orientation” (https://www.dieti.unina.it/index.php/it/studenti/orientamento-2) and the programme’s own “Why Federico II” (https://data-science.dieti.unina.it/index.php/studying-with-us/why-federico-ii) and FAQ pages (https://data-science.dieti.unina.it/index.php/studying-with-us/faq).

Enrolled students are supported through individual academic advising (Student Advising Coordinator: Prof. Roberta Siciliano) and a tutoring service coordinated by Prof. Silvia Rossi, aimed at guiding students through their studies and removing obstacles to attendance and learning. Enrichment activities — lectures, seminars, and simulated interviews with data-science professionals —can  complement the curricular teaching and are announced on the Degree Programme website. 

Seminars and Lectures will be available https://data-science.dieti.unina.it/index.php/courses/extracurricular-activities/seminars-and-tutorials.  

The Degree Programme supports students’ transition to the job market through the compulsory internship (see Study Plan), contacts with partner companies and research institutes, and participation in the University-wide UNINA Career Day. Job-market information and industry contacts are published on the Degree Programme’s own pages. 

Job opportunities and industry partners: https://data-science.dieti.unina.it/index.php/job-opportunities/partners. 

Enrolment (immatricolazione) and re-enrolment for subsequent years normally take place, as a rule, from July to 31 October each year, according to the procedures published in the University’s orientation web site https://www.orientamento.unina.it/.  

For the Data Science programme, first-year lectures for A.Y. 2026/2027 start on 15 July 2026. Late enrolments are in any case accepted up to the University’s general deadline (end of March), although enrolling after the start of lectures makes it harder to keep up with courses taught in two integrated modules across the two semesters. 

Further deadlines (curriculum/free-choice communication, Erasmus Italiano applications — 30 June each year — etc.) are announced on the Degree Programme website in the “Data Science — Studying with us” section (https://data-science.dieti.unina.it/index.php/studying-with-us/information-to-apply).

The general calendar of teaching and examination periods for all Degree Programmes of the Scuola Politecnica e delle Scienze di Base (Collegio di Ingegneria) is set by the School and published, together with the guaranteed number of ordinary and make-up exam sessions each year, on the School’s website. 

Detailed, continuously updated calendari is on the dedicated setion of Scuola Politecnica e delle Scienze di base web site (https://www.scuolapsb.unina.it/calendario-delle-attivita-didattiche/. ). Exam schedules for the Data Science programme are available on the  “first-year exam schedule”  section (https://data-science.dieti.unina.it/index.php/studying-with-us/timeschedule/first-year) and on the “second-year exam schedule” section (https://data-science.dieti.unina.it/index.php/studying-with-us/timeschedule/ii-year) . 

Graduation sessions are scheduled several times a year according to the calendar published at the start of each academic year on  the website of the Polytechnic and Basic Sciences School.