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Master in Data Science

InformationCourse/CS accredited by the Agency for Assessment and Accreditation of Higher Education (A3ES).

Admissions Requirements

  • Holders of a bachelor's degree or holders of an equivalent foreign higher academic degree, under the conditions described in the law, in the areas of Computer Science, Computer Engineering, Mathematics, Economics, Physics, Biology, Electrical Engineering, or similar areas.
  • Undergraduate students who are able to complete a degree in terms of the previous point before the end of the enrollment term for the cycle of studies; applications that do not demonstrate the completion of 85% of the credits of the cycle of studies in question at the date of application will be excluded.

Note: in the registration phase, applications that do not prove having completed the degree (or equivalent) by the end of the enrollment deadline will be excluded.

Criteria for Selection and Ranking

The ranking will be done according to the following criteria and sub-criteria:
  • Criterion 1: academic curriculum (area of training and average obtained) (85%)
    • Subcriterion 1.1: bachelor’s degree adequacy (10%)

      The degree adequacy will be scored on a scale of 0 to 20 according to the following principles:

      • degrees in the area of computer science or computer engineering, mathematics, statistics, data analysis, artificial intelligence, physics, physical engineering, electrical engineering and industrial management engineering or similar will be rated 20;
      • degrees with a solid background in statistics/mathematics or computing such as mechanical engineering, economics, management, management informatics will be rated 18;
      • degrees with some background in statistics or computing such as biology, (engineering) chemistry or another engineering will be rated 16;
      • applications that do not fit in the previous cases will be analysed on a case-by-case basis; the score in this subcriterion will be determined according to the Curricular Units carried out in the relevant areas for the cycle of studies.
    • Subcriterion 1.2: adjusted bachelor’s degree grade (75%)

    The adjusted grade is obtained by normalising the bachelor’s degree grade to the 0-20 scale (rounded to the nearest integer), adding the value of ln(R/r), and rounding to the first decimal digit, with ln expressing the natural logarithm and R and r being, respectively for the University of Porto and the university issuing the degree, the positions in the world ranking published in http://www.webometrics.info

    For admitted applications where the degree has not yet been concluded, the previous formula applies, replacing the bachelor’s degree final grade with the weighted average of the curricular units completed on the application date rounded to the nearest integer.

  • Criterion 2: scientific curriculum and professional experience (15%)

    The scientific curriculum and professional experience are classified from 0 to 20 according to the following two sub-criteria, considering the relevance of the indicators for the area of the cycle of studies.

    • Subcriterion 2.1: technical and/or scientific publications and communications (5%)
    • Subcriterion 2.2: professional experience in the industry, participation in research projects or internships (5%)
    • Subcriterion 2.3: complementary training in the area, including degree and non-degreeawarding courses, such as other masters, postgraduate short or long degrees, and duly certified short courses (5%)

In the event of a tie, the ranking of the higher education institution considered in subcriterion 1.2 will be used as the first tie break criterion and the result of an interview as the second tie break criterion.

The grades of the curricular units carried out must be certified by an official document to be presented by the candidate, including, whenever possible, their weighted average. In case the candidate does not yet have a bachelor's degree, and the presentation of the average is not possible via an official document, it must be indicated, explicitly, in the comments field of the application form.



Course Director: m.cd.diretor@fc.up.pt
Postgraduate Section: pos.graduacao@fc.up.pt
Students: m.cd@fc.up.pt

General information

Official Code: MA09
Director: Álvaro Figueira
Acronym: M:DS
Academic Degree: Master
Type of course/cycle of study: Masters Degree
Start: 2018/2019
Duration: 4 Semesters

Study Plan


  • Master's degree in Data Science (120 ECTS credits)
  • Specialization in Data Science (60 ECTS credits)

Predominant Scientific Areas

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