Data Science

To determine the importance of this master’s degree we have to go to the competences that data scientists have to face; they have to be able of: a) Collecting and restoring information optimally. This information can be of any type (numeric, text, images, videos,...). It also can be affected by the 5 V of the known as Big Data (velocity, variety, volume, value and veracity). b) Visualising this information in order to extract behaviour patterns in the data. c) Stablishing repetitive groupings/patterns and behaviour rules in the data. d) Determining prediction models to stablish future behaviours. All these characteristics define a data scientist, therefore by analysing them we observe that it is needed a multidisciplinary training that comprises different knowledge areas. It has to be noted that these professionals work in all the industry areas, from the pharmaceutical industry until the videogames industry, going through consultancy firms, banks, firms based on Internet, etc. Nowadays there is an important demand of data scientists under the umbrella of what is known as “business intelligence”, “customer experience”, “customer experience”, “business analytics” and “big data”. These four terms comprise a great part of the demand for data analysts oriented to business applications. Given this demand in this master’s degree it is considered towards these topics so that the graduated can have a quick labour incorporation. This orientation will be always carried out from the point of view of an eminently practical and of direct application of the advanced data analysis methods to this kind of problems training.

Compulsory subjects

• Análisis de señales
• Exploratory data analysis
• Web analytics
• Machine Learning (I)
• Machine Learning (II)
• Big Data
• Data science in biomedicine
• Data science in business
• Statistics and optimisation
• Management and manipulation of information
• Introduction to data science
• Advanced visualisation of data
• External internships
• Seminars
• Master's final project

Elective subjects

• Informatics
• Mathematics I

The recommended entry profile to take the University Master’s Degree in Data Science of the Universitat de València is that of graduates with basic skills in mathematics (algebra and calculus) and statistics (probability) both at a theoretical level and at a practical one in the use of computer tools to solve practical cases. The most adequate profiles correspond to the following graduates (at a Degree or Llicenciatura level):

• Informatics Engineering, Electronic Engineering, Telecommunications Engineering or Engineering in any of its specialties.
• Mathematics, Physics.
• Economy, Business Management and Administration.

Regarding personal aptitudes, we recommend that students applying for this master’s degree have an interest on the treatment of information at different levels: collection and storage, visualization, analysis and development of prediction models to establish future behaviours. The ability to identify prblems on data analysis in real applications (industrial areas, business, management, administration, health, etc.), and in other personal skills such as creativity, an innovative ability and interest for an ongoing learning process which is highly recommended for the training of a data scientist with a professional projection in fields with a high dynamism.

It is required that the students that enter this official degree have taken undergraduate degree or higher studies (graduated, engineer or llicenciatura) preferably in Maths, Physics, Engineering (Informatics, Electronics, Telecommunications and Industrial Engineering), Economy and Business Management and Administration.
The Academic Committee of the Master’s Degree will value, in accordance with the admission process we will describe next, that students who apply for the admission have acquired enough competence in mathematics and statistics, have used  in some subject of their training programming tools (such as R, C, Matlab, Python or similar) and who know the basics of the foundations of programming and data bases.
If those knowledges were insufficient, students should take the complementary training established in the 4.6 section of this memory.
For students of non-Spanish speaking countries, B2 Certification of Spanish language is required.

The admission applications will be valued by the Committee for Academic Coordination of the Master’s Degree in accordance to the following criteria: suitability to the profile (50%), the academic record (40%), professional experience related to data analysis (years of professional experience, personal interview by the Academic Committee, letters of recommendation of the jobs exercised, etc. (5%) and other academic and training merits such as additional degree or postgraduate degree qualifications related to the field of knowledge of the Master’s Degree, community languages with B1 or higher level, attendance to courses and semiars, etc. (5%).