Master in Analysis and Engineering of Big Data

Education

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, currently generates continuous and increasingly large volumes of data, usually referred to as "Big Data", in key sectors such as health, public administration, media and social communications, marketing and e-commerce, finance, energy, environment and urbanism, telecommunications, pharmaceuticals and bioinformatics industries.

The technical field of Analysis and Engineering of Big Data is rapidly growing in demand and employability. Experts in the topics are bound to play an increasingly active and value-creating role in management and innovation processes in all fields of industry and services.

Objectives

The Master's Degree in Analysis and Engineering of Big Data aims to train specialists at the level of a 2nd cycle of studies in the emerging field of Data Science and Data Engineering, and is intended for candidates with a background at the level of a 1st cycle of studies including coverage of mathematical and programming fundamentals.

The course develops competencies on techniques and methods for processing and analysis of large volumes of data by advanced computational and mathematical methods, and methodologies to seek and find necessary answers to management, monitoring and optimization processes, or extract knowledge, trends, correlations, or predictions, in particular building on machine learning.

The goals of the course are aligned with the "National Digital Competence Initiative e.2030", in the areas of specialisation (item qualification and creation of added value in economics) and research (big data item).

Curriculum

Career opportunities

The Master's Degree in Analysis and Engineering of Big Data is aimed at educating analysts, project development leaders and innovation experts in the emerging field of Data Science and Engineering. Experts in Big Data are lacking and intensively looked after by companies and institutions where large volumes of data are generated or consumed, namely in health, public administration, e-commerce and marketing, finance, energy, environment and urban planning, telecommunications, media and social communication, and pharmaceutical or biotechnological industry. 

Schedule

(to be announced soon)

Tuition fee

Portuguese students: 1063,47 €/year

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

Applications

1st phase: 23rd April to 16th July 2018

2nd phase: 27th to 31st august 2018

Applications

Entrance requirements for the 2018/2019 academic year

Vacancies for 2018/2019:

25

Admission rules:

The following can apply:

  • 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:

  • Course classification;

  • Academic and scientific curriculum;

  • Professional curriculum;

  • Possible interview

Course coordinator:

Professor Pedro Barahona (Department of Informatics)

Professor Jorge Orestes Cerdeira (Department of Mathematics)

maebd.coordenador@fct.unl.pt

Registration and Accreditation

DGES

Registration number R/A-Cr 33/2017 on 17/04/2017

A3ES

Accreditation on 05/04/2017, for 6 years

About the Department of Informatics

The Department of Informatics is a pioneer institution in advanced education and research in Computer Science in Portugal, and has already graduated thousands of informatics engineers and computer scientists. We currently host around 800 students enrolled in various programs and courses.

Several of our academic staff are associated to the development of computer science and IT in Portugal, for instance, in the first national connection to the Internet in the 80s, in the graduation of the first PhD degrees, and in the development and consolidation of research and innovation in informatics and computer science.

More info

About the Department of Mathematics

The Department of Mathematics is responsible for one undergraduate course (1st cycle of study) two graduate courses (2nd cycle of study) which award a master’s degree, two postgraduate courses (3rd cycle of study) which award a doctorate degree, a one year post-graduate course and other short courses. The department academic staff also cooperates in other courses of all qualification levels taught at FCT NOVA.

The scientific activity of the majority of the faculty members of the Department of Mathematics is developed at the Center for Mathematics and its Applications (CMA). Its research work covers four major areas: Algebra, Differential equations and Numerical Analysis; Operational Research, Statistics and Risk Management. CMA is integrated into the Faculty of Science and Technology of the New University of Lisbon and is financed by the Foundation for Science and Technology. In addition to the researchers of the Department of Mathematics, this center has the collaboration of many researchers belonging to several Portuguese and foreign universities. In the last evaluation that have been done by the Foundation for Science and Technology, CMA has obtained the classification of Very Good. The other members of this Department develop its scientific activity integrated in other research centers or autonomously.

More info