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Accredited
6 Years
27 Mar 2025
Accreditation DGES
Initial registry R/A-Cr 76/2019 de 25-10-2019
Update registry R/A-Cr 76/2019/AL01 de 19-03-2025

Tuition fee EU nationals (2025/2026)

1.stYear 4000.00 €
2.rdYear 1800.00 €
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Lectured in Portuguese
Teaching Type In person

Check here the detailed study plan


The identification of optional courses is subject to an analysis of the prior competences of the admitted candidates, in the process of analysing the applications, with reference to the following training plans:

Personalized plan A - for students with prior skills in Data Science:

  > Knowledge and Reasoning in Artificial Intelligence

  > Mathematical Methods in Machine Learning

  > Computational Optimization

  > 2 Free optional courses


Personalized plan B - for students with no previous skills in Data Science:

  > Unsupervised Statistical Learning

  > Prediction Models

  > Big Data Management

  > Big Data Processing and Modelling

  > 1 Free optional course


Personalized plan C - for students without previous skills in Data Science and Programming:

  > Unsupervised Statistical Learning

  > Prediction Models

  > Big Data Management

  > Programming Fundamentals

  > Big Data Processing and Modelling


Other alternative training programmes may be identified depending on the candidate's prior competences.


 Note: There are curricular units that can accommodate international students and can therefore be taught in English, namely Big Data Management, Forecasting Models and Unsupervised Statistical Analysis.

Programme Structure for 2025/2026

1st Year
Bayesian Modelling
6.0 ECTS
Text Mining for Data Science
6.0 ECTS
Interdisciplinary Seminar in Data Science
6.0 ECTS
Business Analytics Fundamentals
6.0 ECTS
Time Series Analysis and Forecasting
6.0 ECTS
2nd Year
Project Design for Data Science
6.0 ECTS
Deep Learning for Computer Vision
6.0 ECTS
Master Project in Data Science
48.0 ECTS
Master Dissertation in Data Science
48.0 ECTS

Objectives


 To provide comprehensive training in Data Science, in line with current trends and market needs and the emerging lines of research

 To provide knowledge and skills in advanced data analysis, especially for dealing with big data and for extracting knowledge from unstructured data (text and image);

 To provide applied training aimed at developing skills and competencies in handling the latest technological tools for data science;

 Train skilled professionals in the current state of the art in data governance, attribute selection and engineering, and the construction and use of learning models suitable for different data regimes and formats.


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