Bachelor's Degree in Data Science and Engineering

General Objectives of the Course

The main goal of the degree is to empower students with the theoretical knowledge and skills that allow them to design and develop computer applications for
data analysis and the required computational infrastructure. Graduates will be able to proceed to advanced degrees, or to pursue a career in Industry at a global
The B.Sc. in Data Science Engineering will provide the students with real scenarios, so that they can get in touch with the challenges that occur in real scenarios.
This will endow the students to pursue advance studies and to excel in the industry. This was based on recommendations from future employers and on similar
degrees, particularly European and North American spaces.
The degree ensures that the graduates have the knowledge of the basic principles, concepts, theories, methodologies and practices in data science engineering,
and they will be able to express such capacities through a series of instrumental, systemic and interpersonal skills.

Admission Requirements

National Call for Access and Entry to Higher Education (DGES):

One of the following sets:
19 Mathematics A
07 Physics and Chemistry
19 Mathematics A

Application score: 100 points (0-200 scale)
Entry exams: 95 points (0-200 scale)

Calculation Formula:
Secondary school average: 50%
Entry exams: 50%

Other forms of access (UC-applicants):
- Change of Institution / Course Pair Schemes;
- Special Access Call for over 23-years-olds;
- Special Access Call for Holders of Other Higher Education Courses;
- Special Call for International Students.

This information does not exempt the consultation of the webpage of the Directorate General of Higher Education (DGES) and/or of the Applicants website. Please, visit the DGES and the Applicants websites

Professional Goals

The demand for professionals with skills in data science has been growing
exponentially. According to the study "Final results of the European Data Market study measuring the size and trends of the EU data economy" published by the European Commission in May 2017
( in the European market, the number of companies active in data science will increase to 359 thousand in 2020, generating a turnover of more than 739 billion euros, which corresponds to an increase of more than 150% compared to the turnover registered in 2016. The realization
of this potential implies the creation of 769 thousand jobs in professions related to the science of data. These indicators are in line with projections made by other organizations: according to IBM, the annual demand for professionals with skills in data analysis will be 700,000 professionals in 2020
( / 02/21 / data-analyst-data-scientist-big-data-work / 235 /) and according to the World Economic Forum the data science profession will be among the top 10 professions
most needed in 2020 (https: //
To cope with this exponential increase in demand for professionals, several companies announce their own recruitment and team development programs, such as EDP ( big-data-manager) in banking, MilleniumBCP (
in-oeiras), to give examples in the Portuguese market. In the international market, JP Morgan
(, or telecommunications, Vodafone
(https: / / / The employment market in advanced data analysis is still in an embryonic state. The trend will be an exponential increase in the demand for these professionals, which has been accompanied by the average remuneration of
these professionals who are among the highest paid professionals in the market
( -and-jobs-in-europe /).
The LECD aims to provide solid training in the principles and methodologies of data engineering and data science, enabling its trainees mainly to pursue advanced studies (particularly at the master's level).However, it also aims to enable the practice of the profession in contexts that involve the design of solutions
for problems of small and medium complexity / scale and support to the implementation of complex solutions, be it in the component related to data engineering, or in the science of data. LECD curricula is organized
vertically with a high level of specialization, in contrast to a broadband formation that can usually found in the typical informatics engineering curricula, such as the Licenciatura in Informatics Engineering at the University
of Coimbra.

Mode of Study


Teaching / Evaluation language(s)


Examination Regulations, Assessment and Grading

Specific assessment rules are established for each curricular unit according to the Pedagogical Regulation of UC, the final grade being an integer in the range of 0 to 20. For approval in a given curricular unit a final grade equal to or higher than 10 is required.

Learning Objectives and Intended Skills

Knowledge and Comprehension: - Profound knowledge and understanding of i) theories, principles, methods and techniques for data storage, integration,
manipulation and processing; ii) the potential for innovation and value creation in engineering and data science;
Application of knowledge, understanding, judgment and communication: - Identification of problems, design and development of solutions using a wide range of methodological, computational, programming and software techniques for the management, preparation, cleaning, integration, exploration, reduction,
prospecting, modeling and visualization of data; - Communication with specialists and non-specialists
Learning: - Preparation for admission in advanced degrees; - Openness and ability to learn new developments and ideas in the area; - Critical and reflective
thinking towards the technical, social, ethical and legal aspects of the possibilities and limitations of engineering and data science.

Course Coordinator(s)

Jorge Manuel Oliveira Henriques

ECTS Departmental Coordinator(s)

Paula Alexandra Gomes da Silva

Recognition of Prior Learning

Recognition of prior learning is carried out in accordance with the Academic Regulation of the University of Coimbra.

Qualification Requirements and Regulations

Article 3, DL no. 74/2006, March 24th, as written in the DL no. 65/2018, of August 16th

Graduation Requirements

Obtain approval in all courses of the curricular plan, including an optional
course, corresponding to 180 ECTS, as defined in A12.4.

Access to Further Studies

By attributing the bachelor degree, this study cycle allows access to second cycle studies, limited to the specific requirements established by each of these courses, namely to the Master in Data Science and Engineering.

Study Programme

Data Science and Engineering

Academic year

Course Type
1st Cycle Studies

DGES Code: L192

Qualification Awarded: Bachelor's Degree

Duration: 3 Year(s)

ECTS Credits: 180.0


Call for Applications


Agência de Avaliação e Acreditação do Ensino Superior
2020-07-31 a 2026-07-30
Direcção Geral de Ensino Superior

Nº Registo: R/A-Cr 12/2020/AL01