Courses / Department of Informatics Engineering

Master in Artificial Intelligence and Data Science

General Objectives of the Course

MIACD aims to develop advanced disciplinary skills in the fields of artificial intelligence and data science, its advanced technologies and its transversal applications and through a vast set of curricular units that provide it with a strong interdisciplinary nature. The MIACD aims to offer highly complex contexts that allow students to be exposed from a very early age to the typical restrictions of real contexts, whether in scale or complexity, and the most relevant technological components in the industry for the development of effective advanced solutions. , preparing the student both to pursue advanced studies and to practice the profession. In this way, the master's degree allows you to meet needs in the area of engineering and data science in different areas of activity, whether in the national and international market, or in different research subdomains.

Admission Requirements

1. Holders of a Bachelor’s degree or legal equivalent in: Data Science and Engineering, Computer Engineering, Informatics and
Systems Engineering, Communications and Telematics, Communication Engineering, Electrical Engineering, Electrical and
Computer Engineering, Electrical and Telecommunication Engineering, Mathematics and Physics;
2. Holders of the Bachelor’s degree or legal equivalent in other areas of Engineering and Exact and Natural Sciences;
3. Holders of a foreign academic degree that is recognized by the Research Department of Computer Science to meet the objectives
of a degree in the areas mentioned in the previous paragraphs;
4. In justified cases, holders of an academic, scientific or professional curriculum that is recognized to attest the capacity to complete
this cycle of studies by the Scientific Committee of the Department of Computer Science.

Candidates should check the admission requirements available on this site, in addition to the information provided here.

Professional Goals

MECD's professional opportunities are transversal to all companies active in the data economy, encompassing spin-off companies, medium and large companies and multinationals, from the ICT, e-commerce, health, telecommunications, consultancy, banking, industry and services, in the global space, where the needs for skills in the area of Engineering and Data Science are increasingly pressing, and there is a great lack of professionals with specific skills in this area.
In fact, the demand for professionals with skills in these areas has been growing exponentially. These outputs include:
- Data Science Engineer
- Artificial Intelligence Engineer
- Data Engineer
- Computational Learning Engineer
- Data Architect
- Data Analyst
- Marketing analyst

Mode of Study

Face-to-face

Teaching / Evaluation language(s)

Portuguese/English

Examination Regulations, Assessment and Grading

Specific evaluation rules are established for each curricular unit according to the rules of UC, the final grade being an integer in the range 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

• Acquire and demonstrate in-depth knowledge and understanding of the theories, methods and advanced techniques of Artificial Intelligence and Data Science and their deployment in contexts of high scale and complexity;
• Acquire and demonstrate deep knowledge about the innovation and value creation potential of artificial intelligence and data science;
• Acquire familiarity and ability to critically reflect on relevant social and ethical-legal aspects related to artificial intelligence and data sciences;
• Identify and develop solutions using a wide range of advanced methodological, computational, programming and software techniques for preparation, cleaning, integration, exploration, reduction, prospecting, modeling and visualization of data;
• Acquire fundamental knowledge and its limits that enable the continuation of advanced studies;
• Openness and ability to learn new developments and ideas in the area.

Recognition of Prior Learning

The candidate may ask for the evaluation, and possible crediting, of previous relevant formation and experience. At University of Coimbra the “Regulamento de Creditação da Formação Anterior e de Experiência Profissional” is applied. This accreditation cannot exempt the successful public defence of the Dissertation, Work Project or Internship Report.

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 in the curricular plan, including three optional course, corresponding to 120 ECTS, as defined in FORM_C.

Access to Further Studies

By attributing the masters degree, this study cycle allows access to third cycle studies, limited to the specific requirements established by each of these courses, namely to the Doctoral Program on Informatics Engineering.

Study Programme

Artificial Intelligence and Data Science

Academic year
2025-2026

Course Type
2nd Cycle Studies - Continuity Master Programme

DGES Code: ME93

Qualification Awarded: Mestre

Duration: 2 Year(s)

ECTS Credits: 120.0

Category: Continuity second cycle

Applications

Call for Applications

Accreditations

Agência de Avaliação e Acreditação do Ensino Superior: 2025-07-31 a 2031-07-30
Direcção Geral de Ensino Superior: Nº Registo: R/A-Cr 8/2020/AL01; 2025-05-28