Class: LM-DATA - DATA SCIENCE
Duration: 2 years - 120 ECTS credits
President of the degree course: referente prof.ssa Rosanna Verde
Data Science (LM Data Science)
Master of Science Degree, 2 years, English language
Prepare for a Data Science career. Learn methods, skills, and tools to discover insights, communicate critical findings, and model and create data-driven solutions.
The Course
The Master of Science (MSc) Programme in Data Science at the University of Campania “Luigi Vanvitelli” offers the opportunity to graduates to deepen their knowledge of Statistics, Computer Science and Mathematics. The course, entirely delivered in English, is strongly connected to the research activities performed at the Department of Mathematics and Physics.
For data-driven problem-solving, Data Science integrates computational and statistical skills. This programme will provide students with the analytical skills they need to create complex technological solutions using contemporary computational approaches, with a focus on rigorous statistical reasoning.
The programme combines an entry level of statistical and machine learning technique instruction with a variety of optional courses covering more advanced statistical computing and modeling knowledge.For admission, a bachelor degree in Statistics, Engineering, Computer Science, Mathematics, Physics or related fields is required, provided that students have a sufficient statistics and mathematics background. English level B2, in the Common European Framework of Reference (CEFR), is also required.
During the 2-year Programme students will have ample opportunity to immerse themself in different areas of data science. The first two semesters (year 1) are devoted to acquiring a solid knowledge in statistics, machine learning, artificial intelligence, software engineering (see the study plan for details). During the third and fourth semesters (year 2), the students focus on a few specialised training modules, followed by a master thesis about an original research subject. Students can choose among two specializations:
i. Data Science for official statistics and business analytics;
ii. Data Science for scientific applications.
For the aims of the Programme, the MSc Teaching Board has established inter-institutional agreements with a some European universities. Students have the opportunity to spend a period of study (preferably the third semester) at one of the partner universities in Europe.
Professional skills
The MSC programme in Data Science aims to train specialists with technical mathematical-statistical-computer competeneces and basic knowledge in applied domains of physical, biological sciences, and in business administrations.
The working context within public and private companies and administrations, including scientific and technological research institutes and bodies, particularly in the management, commercial, financial, and general management staff sectors, as well as participation in interdisciplinary work and research groups where the DS graduate will be able to contribute to the analysis of data, even of large dimensions, effectively working alongside experts in specific application sectors.
The DS graduate with a path more oriented towards official statistics has expertise that can be used in national statistical institutes and national and supranational bodies and organizations that usually use data and information, including those of a transnational nature.
Opportunities for Data Scientists
Data science professionals are likely to be increasingly sought after as the integration of statistical and computational analytical tools becomes essential in all kinds of organizations and enterprises. A thorough understanding of the fundamentals is to be expected from the best practitioners. For instance, in applications in marketing, the healthcare industry and banking, computational skills should be accompanied by statistical expertise at the graduate level. Data scientists need a broad background knowledge so that they will be able to adapt to rapidly evolving challenges.
Master’s graduates in Data Science will be able to work in functions of high responsibility in one or more of the following areas:
- in the tertiary sector and public administrations, in governmental and non-governmental bodies, in national (ISTAT) or international/supranational statistical institutes (EUROSTAT), for example, in the development and management of innovative data-based services, such as those usable online or linked to social networks, in the definition of indicators and statistical analysis to support decision-making;
- in the industrial and business sector, for example, to manage projects and propose innovative solutions in the field of information and computer systems and decision-making processes at operational, strategic/directional level, and in all processes based on the processing of information coming from databases not only corporate;
- in the scientific and technological sectors, with particular reference to the biological and biomedical ones, as support figures to the specialists of the field for the activities concerning the management, processing and analysis of data and modeling.
Master’s graduates can hold roles as Data analyst, Data scientist, Data manager, as well as managers of departments for the development and management of data analysis methodologies and IT tools to support decision-making processes, or as technical figures in teams of analysis and treatment of physical, chemical, biological, health and more generally scientific-technological data.
DATA SCIENCE
Study Plan A.Y. 2022/2023
LM DATA SCIENCE 2022-2023 - Study plan
I YEAR 60 CFU - DATA SCIENCE (Single path in the first year) |
||||
|
SSD |
COURSE |
ETCS |
PROF |
A course to choose |
MAT/05 |
9 |
||
A course to choose |
MAT/09 |
6 |
4 ECTS 2 ECTS |
|
MAT/06 |
Inactive |
|||
A course to choose |
SECS-S/01 |
9 |
||
7 ECTS 2 ECTS |
||||
Mandatory |
SECS-S/01 |
6 |
||
Mandatory |
INF/01 ING_INF/05 |
12 |
Fiammetta Marulli(6 ECTS) - Anna Esposito (3 ECTS) + Gennaro Cordasco(3 ECTS); |
|
Mandatory |
MAT/08 |
9 |
||
A course to choose |
ING-INF/05 |
9 |
Mauro Iacono (3 ECTS) - Pasquale Cantiello (6 ECTS) (INGV) |
|
(3 ECTS) (6 ECTS) CONTRACT TEACHER |
||||
TOTAL |
60 |
|
II YEAR 60 CFU - DATA SCIENCE FOR SCIENTIFIC APPLICATIONS |
||||
|
SSD |
COURSE |
ETCS |
PROF |
Two courses to choose |
SECS-S/01 |
12 |
Antonio Irpino |
|
MAT/06 |
Bruno Carbonaro |
|||
SECS-S/01 |
Statistical And Machine Learning Methods For Information Technologies |
Rosanna Verde |
||
Mandatory |
IUS/01 |
6 |
Domenico Giovanni Ruggiero |
|
Two courses to choose |
FIS/04 |
12 |
Nunzio Itaco |
|
FIS/02 |
Eugenio Lippiello |
|||
Giovanni De Gregorio |
||||
MAT/08 |
Rosanna Campagna |
|||
BIO/10- BIO/18 |
(To be assigned) |
|||
Mandatory |
|
FREE |
8 |
|
Mandatory |
|
Linguistic skills |
2 |
|
Mandatory |
|
Seminars/training |
2 |
|
Mandatory |
|
Internships/Stage |
8 |
|
Mandatory |
|
Thesis |
10 |
|
TOTAL |
60 |
|
II YEAR 60 CFU - DATA SCIENCE FOR OFFICIAL STATISTICS AND BUSINESS ANALYTICS |
||||
|
SSD |
COURSE |
ETCS |
PROF |
Mandatory |
SECS-S/01 |
6 |
Antonio Irpino |
|
Mandatory |
SECS-S/01 |
Statistical And Machine Learning Methods For Information Technologies |
6 |
Rosanna Verde |
Two courses to choose |
SECS-P/07 |
6 |
Claudia Zagaria |
|
IUS/01 |
Domenico Giovanni Ruggiero |
|||
Two courses to choose |
SECS-P/08 |
12 |
Barbara Masiello |
|
SECS-S/01 |
Rosaria Lombardo |
|||
ING-INF05 |
Silvio Baccari |
|||
SECS-S/05 |
Ida Camminatiello |
|||
SECS-P/01 |
Enrica Carbone |
|||
Mandatory |
|
FREE |
8 |
|
Mandatory |
|
Linguistic skills |
2 |
|
Mandatory |
|
Seminars/training |
2 |
|
Mandatory |
|
Internships/Stage |
8 |
|
Mandatory |
|
Thesis |
10 |
|
TOTAL |
60 |
|