Computer Science (Curriculum: Data Science - *taught in Italian*)
Study location | Italy, Florence |
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Type | Graduate, full-time |
Nominal duration | 2 years (120 ECTS) |
Study language | Italian |
Application fee | €20 one-time Application fee is non-refundable |
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Entry qualification | Undergraduate diploma (or higher) The entry qualification documents are accepted in the following languages: English / French / Italian / Spanish. Often you can get a suitable transcript from your school. If this is not the case, you will need official translations along with verified copies of the original. |
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Language requirements | Italian Non-EU applicants living abroad are required to have a valid certificat of Italian language proficiency at level B2 awarded as determined by the CLIQ (Italian Quality Language Certification) quality system, which unites in one association the current certification bodies (University for Foreigners of Perugia, University for Foreigners of Siena, Rome Tre University and the Dante Alighieri Society) and University for Foreigners “Dante Alighieri” of Reggio Calabria, as well as in convention with Italian Institutes of Culture abroad or other institutions. |
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Other requirements | At least 1 reference(s) should be provided. More information on the admission requirements are available here |
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More information |
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Overview
The M.Sc. Degree in Computer Science aims to develop deep knowledge on the theoretical, methodological, and technical foundations in the main field of computer science and ancillary disciplines. In details, the M.Sc. will include extensive studies on algorithms, distributed systems, programming languages, data and systems analysis. The main learning objectives that shall be developed are here summarized:
- Deep knowledge and understanding of the principles of computer science, as well as of the research frontiers for selected topics.
- Ability to combine theory and practice to solve computer science problems, being able to reason at the appropriate abstraction level, also exploiting technologies and techniques from ancillary disciplines.
- Ability to apply the state of the art or innovative methods for the solution of problems in the real world, possibly including related disciplines and developing novel approaches or methods.
Reach an adequate level of autonomy in exercising professional activities, and good team leadership and team management skills
- Ability to work and communicate effectively in National and International contexts.
Programme structure
The Data Science Curriculum aims to provide a sound grounding on the techniques, and the underlying theoretical principles, which make data analysis possible. To this end, the curriculum combines and applies competences from different disciplinary areas active at our University, mainly from the areas of Computer Science, Information Engineering and Statistics. In particular, courses are offered focusing on the following aspects:
- algorithmic techniques for data analysis, with specific attention to structures for large data sets and related theoretical and practical aspects;
- data mining algorithms for searching regularities and patterns in data, and data structures necessary for their organization;
- cryptographic methods for protecting the privacy of individuals, during data collection, transmission and analysis;
- basic and advanced algorithms for statistical learning, basics of computational learning theory, the design of solutions to real problems;
- parallel and high performance programming techniques;
- statistical bases of regression, Bayesian classification and inference, which are at the core of automatic learning;
- numerical methods to acquire those computer aided geometric design skills useful for the implementation and use of specific algorithms for data visualization;
- optimization methods, necessary to effectively conduct data analysis in the presence of constraints on hardware and software resources.
Career opportunities
In the Information Society, Data Scientist is naturally emerging as one of the most sought after professions. According to a frequently cited study (McKinsey Global Institute, 2011), the demand for data scientists in 2018 could exceed their actual availability by 1.5 million.
Graduates in Data Science will have the necessary skills to apply to be employed by: companies that, on locally or globally operate in the field of market data analysis and “business intelligence”; institutions that process large collections of (medical, financial, census,…) data; small and large companies that rely on complex information systems to manage their activities.
Here are some examples of emerging professions that fall within those areas:
- Data Management Professional: deals with the collection and management of data, and infrastructures that support these activities, similar to what the administrators do for traditional databases;
- Data Engineer: deals with the design and development of the infrastructure;
Business Analyst: a role closely related to analysis – both in the traditional and Big Data sense – and data presentation, including the generation of reports and views, and everything that is generally referred to as “business intelligence”;
- Machine Learning Analyst: responsible for creating and applying prediction and correlation tools that extract knowledge, rules and forecasts from data;
- Data-oriented Professional: at a higher level, identifies useful data for a given problem, chooses the appropriate analysis tools and selects from the extracted information what may be useful for solving the problem.
Graduates in Computer Science can enrol in the Italian Register of Information Engineers (Professional Register – Section A of Engineers – Information Sector) and apply for the PhD programmes in Computer Science.
GMT
Applicants with a bachelor's degree awarded in Italy cannot apply via DreamApply. They have to contact the School of their intended master program.
GMT
Applicants with a bachelor's degree awarded in Italy cannot apply via DreamApply. They have to contact the School of their intended master program.