The Master Degree in Data Science of the University of Naples Federico II aims at connecting graduate students with the rich ecosystem of academic research and the wealth of job opportunities in different domains of the data science arena. The master leverages on the variety of skills and competences available in the University Federico II, which was established in 1224 and is the oldest non confessional university in the world .
The master coordinates faculties from many Departments in order to offer different learning curricula.
Courses of the First Year
The first year is in common to all curricula. The first year focuses on the acquisition of crucial methodological knowledge in statistics, data management, and informatics. The 12 CFU courses are split into two modules to ease the learning process. The exam, however, can be registered only after both modules have been passed.
1st Semester
| Code | Course | Module | CFU | Lecturer |
|---|---|---|---|---|
| U5383 | Mathematical Methods for Data Science | 6 | Prof. Salvatore Cuomo | |
| U5394 | Fundaments of Programming and Data Management | Fundaments of Programming (Module A) | 6 | Prof. Roberto Pietrantuono |
| Hardware and software for Big Data | Hardware for Big Data (Module A - code U5385) | 6 | Prof. Giancarlo Sperlì | |
| U5387 | Statistical Learning and Data Analysis | |||
| U5388 | Statistical Learning and Data Analysis - Module A | 6 | Prof. Roberta Siciliano | |
| U5389 | Statistical Learning and Data Analysis - Module B | 6 | Prof. Giuseppe Longo |
2nd Semester
| Code | Course | Module | CFU | Lecturer |
|---|---|---|---|---|
| U5390 | Data Mining and Machine Learning | |||
| U5391 | Data Mining and Machine Learning - Module A | 6 | Prof. Roberta Siciliano | |
| U5392 | Data Mining and Machine Learning - Module B | 6 | Prof. Giuseppe Longo | |
| U5394 | Fundaments of Programming and Data Management | Data Management - Module B | 6 | Prof. Elio Masciari |
| U5386 | Hardware and software for Big Data | Software for Big Data - Module B | 6 | Prof. Flora Amato |
| Theory and Ethics of Big Data and AI | 6 | To be assigned |
Total CFU - First Year: 60
Courses of the Second Year
The second year characterizes your specialization It requires the acquisition of an additional 60 CFUs, distributed accordingly to the following table.
| Course | CFU | Notes |
|---|---|---|
| Curricular course n. I | 12 | Specific to the selected curriculum |
| Curricular course n. II | 6 | Specific to the selected curriculum |
| 1-st Free Choice Course | 6 | Only constraint: the course must be coherent with the formative trajectory of the student (read below) |
| 2-nd Free Choice Course | 6 | Only constraint: the course must be coherent with the formative trajectory of the student (read below) |
| Internship-Stage or Project | 8 | Second semester |
| Other activities | 6 | Any Time |
| Thesis and Final Exam | 16 | Second Semester |
Total CFU - Second Year: 60
You can choose from 4 different curricula:
- DATA SCIENCE FOR PUBLIC ADMINISTRATION, ECONOMY AND MANAGEMENT: This curriculum is offered in collaboration with the Department of Economy and Statistical Sciences - DISES.
- DATA SCIENCE FOR INFORMATION TECHNOLOGIES: The curriculum Data Science for Information Technologies offers three different learning paths:
- Path 1 - Statistics and Robotics for Health
- Path 2 - Signal and Video Processing
- Path 3 - Data Security
- Path 4 - Industrial Applications
- Path 5 - Text and Speech Processing
- DATA SCIENCE FOR FUNDAMENTAL SCIENCES: The curriculum Data Science for Fundamental Sciences offers three different learning paths:
- Path 1 - Mathematical Methodologies
- Path 2 - Hard Sciences
- Path 3 - Life Sciences
- DATA SCIENCE FOR INTELLIGENT SYSTEMS: Methods and theories behind Artificial Intelligence and Quantum Computing.