Master in Artificial Intelligence

General Objectives of the Course

The MIA provides advanced training to first-cycle students in Science and Engineering, equipping them with essential competencies in designing, analyzing, implementing, and refining AI solutions for scientific research and industry needs. The proposal stems from a thorough market analysis, input from industrial and academic partners, insights from national and international AI, Machine Learning (ML) and Data-Science programs, and our extensive experience in fundamental AI research across various multidisciplinary contexts, such as health services, smart cities, transportation, industrial management, computational creativity, and multimedia.
The MIA ensures students possess enduring knowledge and understanding of the concepts, advanced principles, theories, methods and practices of AI, and also an integrated set of instrumental, systemic and interpersonal skills, preparing them to keep pace with the advancements in the field of AI and for a long and successful career.

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;
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

The MIA aims to complement and deepen the training for students of 1st cycle in the areas of Science and Engineering, in the area of Artificial Intelligence. The study cycle aims at the acquisition of essential competencies in the design and implementation of advanced solutions in high complexity and scale interdisciplinary contexts in the multiple fields of intervention of engineering and Artificial Intelligence, both at the level of scientific research and at the industry level. Potential jobs include, but are not limited to, AI Engineer, ML Engineer, Data Scientist, AI Research Scientist, AI Product Manager, AI Ethics Specialist, Deep Learning Engineer, AI Product Designer, AI Consultant.

Mode of Study

Full- or part-time attendance, presence required in daytime schedule

Teaching / Evaluation language(s)

Portuguese and English

Examination Regulations, Assessment and Grading

Assessments and Grading Regulation: 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

Knowledge and Understanding:
- Demonstrate extensive knowledge and deep understanding of advanced AI theories, methods, and techniques to tackle complex problems across various domains.
- Recognize the potential for AI-driven innovation and value creation.
- Understand AI challenges in various domains.
- Be familiar with the human and ethical aspects of AI.

Application of Knowledge, Understanding, Judgment, and Communication:
- Develop AI solutions using diverse techniques.
- Take into account human factors in AI.
- Communicate effectively with specialists and non-specialists.
- Apply a multidisciplinary perspective to AI.

Learning:
- Acquire foundational knowledge for advanced studies.
- Embrace new AI developments and ideas.
- Think critically about AI's technical and ethical aspects.

Course Coordinator(s)

Fernando Jorge Penousal Martins Machado
machado@dei.uc.pt

Recognition of Prior Learning

The recognition of prior learning is carried out according to the Academic Regulation of the University of Coimbra, RAUC, Regulation No. 805-A/2020, DR, 2nd series, of September 24 (http://www.uc.pt/academicos/regulamentos/regulamentos), under the terms set in Decree-Law No. 74/2006, of March 24, in its current wording

Qualification Requirements and Regulations

The qualification is framed in Decree-Law no. 74/2006, of March 24, in the current version; Ordinance no. 782/2009, of July 23.

Graduation Requirements

Get approval in all courses in the curricular plan, three optional course, 120 ECTS

Access to Further Studies

y attributing the master's degree, this study cycle allows access to third cycle studies, limited to the specific requirements established by each of these courses, namely to the PhD in Informatics Engineering.

Study Programme

Artificial Intelligence

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Course Type
2nd Cycle Studies - Continuity Master Programme

DGES Code: ME55

Qualification Awarded: Mestre

Duration: 4 Semester(s)

ECTS Credits: 120.0

Category: Continuity second cycle

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Applications

Call for Applications

• 2nd Cycle Course

• Application submission
• Web page with information for candidates

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Accreditations

Agência de Avaliação e Acreditação do Ensino Superior

2024-07-31 a 2030-07-30

Direcção Geral de Ensino Superior

Nº Registo: R/A-Cr 107/2024

2024-07-25

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Documents