Degree number of credits: 90

Compulsory credits: 65

Final project: 15

Work placements/Internships: 10

Degree code: 2221

Years: 2

Teaching type: face-to-face

Knowledge branch: Engineering and architecture

Master degree website:

Places available for new students: 25

Minimum number of enrolment credits per student: 36

Price per credit [2018-2019 academic year]: 39,27 €

Management Centre: School of Engineering (ETSE)

Languages used in class: Spanish and Valencian

Participating universities: University of València

Academic coordinating commission Emilo Soria Olivas (Director)
Julia Carmen Amorós López
Carmen Armero Cervera
Vicente Cerverón Lleó
Jose Manuel Pavía Miralles
Consuelo Alandes López (PAS)

Academic, scientific or professional interest: 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.

Pre-enrolment information

Academic information:

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