{"id":34489,"date":"2021-07-28T13:22:11","date_gmt":"2021-07-28T12:22:11","guid":{"rendered":"https:\/\/www.ipleiria.pt\/en\/?post_type=course&p=34489"},"modified":"2026-03-20T20:15:53","modified_gmt":"2026-03-20T20:15:53","slug":"data-science","status":"publish","type":"course","link":"https:\/\/www.ipleiria.pt\/en\/course\/data-science\/","title":{"rendered":"Data Science"},"content":{"rendered":"\n
<\/div>\n\n\n
\n

Data Science<\/h1>\n
\n
Course Type: <\/div>\n
Master\u2019s Programme<\/div>\n <\/div>\n <\/div>\n\n\n
<\/div>\n\n\n\n
\n
\n\n
\n

Programme Introduction<\/h2>\n
\n

The master degree in Data Science comes up as an answer to the increasing need, felt by the region companies, of expertsin Data Science with skills on the most recent technologies and analytic techniques for acquiring, processing andanalysing large volumes of data. It is intended that the study program is multidisciplinary and that it potentiates a set ofsynergies between information systems, computation science and statistic, covering applications in several areas ofknowledge as, for example, Management, Engineering, Health, Business Sciences, among others.<\/p>\n\n\n\n

The study cycle aims at achieving the following general objectives:
1) To broaden the 2nd cycle educational offer in the region;
2) To form qualified professionals in the Data Science area;
3) To develop Data Science skills in professionals already integrated in the market;
4) To develop connections with the region companies through internships, projects and dissertations that allow knowledge extraction and the creation of added value in the companies;
5) To develop applied research in the Data Science area, namely through the development of projects and dissertations;
6) To promote knowledge transfer to the organizations in the Data Science area;
7) To promote autonomous lifelong learning.<\/p>\n\n\n\n

In this context, this study program allows an undergraduate to acquire advanced skills in the Data Science area. The teaching methodology focus on the resolution of problems, with the development of several projects aiming at the resolution of everyday real problems of companies, industries and services. <\/p>\n<\/div>\n

<\/div>\n<\/div>\n\n
\n

Programme Coordinator<\/h2>\n
\n

Maria Beatriz Guerra da Piedade
coord.mcd.estg@ipleiria.pt<\/a> <\/p>\n<\/div>\n

<\/div>\n<\/div><\/div>\n\n\n\n
\n
<\/div>\n\n\n\n\n
\n

School<\/h2>\n \n
Technology and Management<\/a><\/div>\n
<\/div>\n <\/div>
\n

City<\/h2>\n \n
Leiria<\/a><\/div>\n
<\/div>\n <\/div>
\n

Language<\/h2>\n
Portuguese<\/div>\n
<\/div>\n <\/div>
\n

Type<\/h2>\n
Evening<\/div>\n
<\/div>\n <\/div>\n\n
\n

Length<\/h2>\n
4 Semesters<\/div>\n
<\/div>\n<\/div>\n\n
\n

Vacancies\n<\/h2>\n
\n

General and International student contingent:\u00a0 50<\/p>\n<\/div>\n

<\/div>\n<\/div>\n\n
\n

Notice<\/h2>\n
\n

Edital 2026<\/a> (PT Doc retf)<\/p>\n<\/div>\n

<\/div>\n<\/div>\n\n
\n

DGES certification<\/h2>\n
\n

Link to Registration<\/a><\/p>\n<\/div>\n

<\/div>\n<\/div><\/div>\n<\/div>\n\n\n\n
<\/div>\n\n\n\n
<\/div>
\n
\n
\n
\"\"<\/figure><\/div><\/div>\n\n\n\n
\n
<\/div>
\n

Objectives<\/h2>\n
Programme<\/div>\n<\/div>\n
\n

The degree aims to endow students with solid skills, having the following learning goals:
1) To apply the knowledge and understanding and problem resolution skills in new situations and in broad andmultidisciplinary contexts;
2) To deeply understand Data Science concepts, methods and techniques and their usage in real problems;
3) To dominate Data Science applications and technologies;
4) To develop data retrieval, preparation, integration, exploration, reduction, prospection, modelling and analysis solutions;
5) To integrate knowledge, deal with complex questions, develop solutions in situations of limited or incomplete information;
6) To communicate conclusions and the underlying knowledge and reasoning to experts and non-experts in the area;
7) To be able to learn in a self-oriented and autonomous way through life;
8) To acquire professional and scientific research skills.<\/p>\n<\/div><\/div><\/div><\/div>\n<\/div>\n<\/div>\n<\/div><\/div><\/div>\n\n\n\n

<\/div>
\n
\n
\n
<\/div>
\n
<\/div>\n\n\n<\/div><\/div><\/div>\n<\/div>\n\n\n\n
\n
\"\"<\/figure>\n<\/div>\n<\/div>\n<\/div><\/div><\/div>\n\n\n\n
<\/div>\n\n\n \n
\n \t
\n \t\t \t\t
\n \t\t
\n \t\t\t
\n \t\t\t\t
\n \t\t\t\t\t
\n \t\t\t\t\t\t