Master in Analysis and Engineering of Big Data


Master in Analysis and Engineering of Big Data

The number of credits needed to obtain the degree is 120 (4 semesters).

The digital transformation of society, the explosion of the Internet and the popularization of social networks, led to the generation of huge volumes of digital data in key sectors such as health, public administration, media and social communication, marketing and e-commerce, finance, energy, environment and urbanism, telecommunications, pharmaceutical industry and bioinformatics.

The area of Big Data Analysis and Engineering focusses on the development of methodologies to handle large volumes of data, in order to extract useful information. Acquiring, storing, managing and organizing data are the issues that arise in this area of study. There is a growing demand and employability of specialists in this area who will play an increasingly intervening and value-creating role in management and innovation processes in all areas of industry and services in the coming years.



The Master on Analysis and Engineering of Big Data is aimed at training analysts, project development leaders and innovation experts in the emerging field of Data Science and Data Engineering.
The course develops competencies for processing and analysing large volumes of data by advanced computational and mathematical methods, and methodologies for searching and finding answers to management, monitoring, and optimisation processes, or for extracting knowledge, trends, correlations, or forecasts through automatic machine learning.
The objectives of the course are aligned with the "National Digital Competence Initiative e.2030", in the areas of specialization (item qualification and creation of added value in economics) and research (big data item).


Target Audience 

Candidates with training at the level of a 1st cycle of studies, with strong mathematical and programming bases.


Career opportunities

Specialists in this area of Big Data are especially sought after by companies and institutions where large volumes of data are generated or consumed. In addition to the companies that collaborate in the organization of the master's degree, there are several companies and institutions in the areas of health, public administration, e-commerce and marketing, finance, energy, environment and urbanism, telecommunications, media and media, pharmaceutical industry or biotechnology, among others, which are interested in professionals with this profile.


Registration and Accreditation


Registration n.º R/A-Cr 33/2017 in 17/04/2017


Accreditation in 06/04/2017, for 6 years



The Master in Analysis and Engineering of Big Data is jointly organised by the Departments of Informatics and Mathematics, with the collaboration of several companies, namely in the Seminar curricular unit and in the Dissertation.


Course coordinator:

Prof. Doutor João Carlos Gomes Moura Pires  (Coordenador - Departamento de Informática)

Prof.ª Doutora Paula Alexandra da Costa Amaral (Co-Coordenadora - Departamento de Matemática)


Office hours: Tuesday at 4:00 p.m. - 5:00 p.m.
Students should send an email indicating the subject and requesting the appointment.


 Empresas Parceiras


Access Conditions for the academic year 2022/2023

Number of places (Numerus Clausus): 25

Access Rules:

To apply, candidates should be:

Holders of a 1st degree (licenciado or legal equivalent) in the areas of Engineering, Exact Sciences, Natural Sciences or Economy, subject to curricular appreciation of the candidate. The program requires mathematical bases and notions of computation and programming at the level of a first general engineering cycle ;

Holders of a foreign higher academic degree conferred after a 1st cycle of studies organized in the above areas, in accordance with the principles of the Bologna Process by a State adhering to this Process;

Holders of a foreign higher academic degree, in those areas, that is recognized as meeting the objectives of the degree of licenciado by the Scientific Council of the Faculty of Sciences and Technology;

Holders of an academic, scientific or professional curriculum recognized by the Scientific Committee of the programme, as testifying the ability to carry out this programme.

Ranking Criteria:

Candidates will be ranked according to:

  • GPA;
  • Academic and scientific curriculum;
  • Professional curriculum;
  • Interview (if needed)


The master's classes are given in daytime working hours. However, to facilitate the attendance of “student workers”, it is expected that:

  • First semester classes take place at the end of the day (every week day from 4 pm to 8:00 pm), and that in the second semester most UCs are also scheduled at this time, although some optional UCs may take place at other times.
  • The course can be done in part-time. According to FCT / NOVA rules, students can take the course in twice the normal duration, completing half of the curricular units planned in each semester and paying half the tuition fees per semester.


National students (including European Union): € 2000.00 / year

International students: € 7000 / year (60% reduction for CPLP students)

Deadline for Application:

1st phase: 1st May to 15th June 2022

2nd phase: 1st to 16th July 2022

3rd phase: 25th July to 28th August 2022

4th phase:1st to 15th February 2022