Artificial Intelligence Engineering

Porto Higher Institute of Engineering (ISEP)

General Data

Type of Credits: ECTS
ECTS Credits: 120
Level: EQF-7 (Master)
Languages: English, Portuguese
Fields of study: 0613 Software and applications development and analysis
Mode of Learning: Presential
Study Modality: Full time
Professional Practices: No
Available for Mobility Students: Yes
Restricted to alliance students: No
Code: -

Coordination

Carlos Ramos

https://www.isep.ipp.pt/Course/Course/462

Presentation

Artificial Intelligence (AI) is transforming entire sectors of the economy and creating new opportunities in areas such as mobility, banking, insurance, and retail. With global growth exceeding 37% per year, AI is one of the most dynamic and valued technological fields, having a strong impact on the creation of start-ups, spin-offs, and new business models. 

If you want to be at the forefront of this technological revolution, develop intelligent solutions, and join highly innovative teams, Artificial Intelligence is the master’s degree for you. 

Competencies

What areas can you work in? 

  • Data Science and Big Data; 
  • Intelligent and Decision Support Systems; 
  • Business Intelligence; 
  • Human–AI System Interaction; 
  • Machine Learning; 
  • Computer Vision and Robotics; 
  • Business Intelligence and Knowledge Management; 
  • Research and Teaching. 

Learning Outcomes

What does this master’s degree give you? 

  • You attend the first master’s program in Portugal titled Artificial Intelligence, covering the main domains of the field. 
  • You join an area of excellence at ISEP/P.PORTO, connected to GECAD, an R&D group rated “Excellent” by FCT, and to the first PhD in AI and Intelligent Systems in Portugal (DIAESI). 
  • You learn through an updated curriculum covering current and emerging topics such as Generative AI, LLMs, Agents, Robotics, Deep Learning, Natural Language Processing, Computer Vision, IoT, and AI Ethics. 
  • You develop skills through an innovative methodology – Challenge-Based Learning (CBL) – solving real-world challenges in teams. 
  • You have the opportunity to carry out a project, thesis, or internship in national and international companies or research groups. 
  • You gain access to a highly valued job market, with some of the best-paid positions nationally and internationally. 

Courses

Term 1

Code Name Year Term ECTS Type Mobility
Sin codigo Knowledge Engineering Year 1 1 7.50 Mandatory No
Sin codigo Machine Learning Year 1 1 7.50 Mandatory No
Sin codigo Planning and Decision Support Year 1 1 7.50 Mandatory No
Sin codigo Programming Paradigms in Artificial Intelligence Year 1 1 7.50 Mandatory No
Sin codigo Ethics and Social Aspects of Artificial Intelligence Year 2 1 7.50 Mandatory No
Sin codigo Preparatory Work of Dissertation Year 2 1 11.00 Mandatory No
Sin codigo Privacy and Security in Intelligent Systems Year 2 1 4.00 Mandatory No
Sin codigo Research and Innovation in Artificial Intelligence Year 2 1 7.50 Mandatory No

Term 2

Code Name Year Term ECTS Type Mobility
Sin codigo Artificial Neural Networks and Deep Learning Year 1 2 7.50 Mandatory No
Sin codigo Multi-Agent Systems Year 1 2 7.50 Mandatory No
Sin codigo Natural Language and Generative Artificial Intelligence Year 1 2 7.50 Mandatory No
Sin codigo Robotics and Intelligent Environments Year 1 2 7.50 Mandatory No
Sin codigo Dissertation Year 2 2 30.00 Mandatory No

Term 1

Code Name Year Term ECTS Type Mobility
Sin codigo Knowledge Engineering Year 1 1 7.50 Mandatory No
Sin codigo Machine Learning Year 1 1 7.50 Mandatory No
Sin codigo Planning and Decision Support Year 1 1 7.50 Mandatory No
Sin codigo Programming Paradigms in Artificial Intelligence Year 1 1 7.50 Mandatory No
Sin codigo Ethics and Social Aspects of Artificial Intelligence Year 2 1 7.50 Mandatory No
Sin codigo Preparatory Work of Dissertation Year 2 1 11.00 Mandatory No
Sin codigo Privacy and Security in Intelligent Systems Year 2 1 4.00 Mandatory No
Sin codigo Research and Innovation in Artificial Intelligence Year 2 1 7.50 Mandatory No

Term 2

Code Name Year Term ECTS Type Mobility
Sin codigo Artificial Neural Networks and Deep Learning Year 1 2 7.50 Mandatory No
Sin codigo Multi-Agent Systems Year 1 2 7.50 Mandatory No
Sin codigo Natural Language and Generative Artificial Intelligence Year 1 2 7.50 Mandatory No
Sin codigo Robotics and Intelligent Environments Year 1 2 7.50 Mandatory No
Sin codigo Dissertation Year 2 2 30.00 Mandatory No

Year 1

Code Name Term ECTS Type Mobility
Sin codigo Knowledge Engineering 1 7.50 Mandatory No
Sin codigo Machine Learning 1 7.50 Mandatory No
Sin codigo Planning and Decision Support 1 7.50 Mandatory No
Sin codigo Programming Paradigms in Artificial Intelligence 1 7.50 Mandatory No
Sin codigo Artificial Neural Networks and Deep Learning 2 7.50 Mandatory No
Sin codigo Multi-Agent Systems 2 7.50 Mandatory No
Sin codigo Natural Language and Generative Artificial Intelligence 2 7.50 Mandatory No
Sin codigo Robotics and Intelligent Environments 2 7.50 Mandatory No

Year 2

Code Name Term ECTS Type Mobility
Sin codigo Ethics and Social Aspects of Artificial Intelligence 1 7.50 Mandatory No
Sin codigo Preparatory Work of Dissertation 1 11.00 Mandatory No
Sin codigo Privacy and Security in Intelligent Systems 1 4.00 Mandatory No
Sin codigo Research and Innovation in Artificial Intelligence 1 7.50 Mandatory No
Sin codigo Dissertation 2 30.00 Mandatory No

Year 1

Code Name Term ECTS Type Mobility
Sin codigo Knowledge Engineering 1 7.50 Mandatory No
Sin codigo Machine Learning 1 7.50 Mandatory No
Sin codigo Planning and Decision Support 1 7.50 Mandatory No
Sin codigo Programming Paradigms in Artificial Intelligence 1 7.50 Mandatory No
Sin codigo Artificial Neural Networks and Deep Learning 2 7.50 Mandatory No
Sin codigo Multi-Agent Systems 2 7.50 Mandatory No
Sin codigo Natural Language and Generative Artificial Intelligence 2 7.50 Mandatory No
Sin codigo Robotics and Intelligent Environments 2 7.50 Mandatory No

Year 2

Code Name Term ECTS Type Mobility
Sin codigo Ethics and Social Aspects of Artificial Intelligence 1 7.50 Mandatory No
Sin codigo Preparatory Work of Dissertation 1 11.00 Mandatory No
Sin codigo Privacy and Security in Intelligent Systems 1 4.00 Mandatory No
Sin codigo Research and Innovation in Artificial Intelligence 1 7.50 Mandatory No
Sin codigo Dissertation 2 30.00 Mandatory No

Admission Requirements

Can I apply? 

You can apply for the master’s programme if you: 

  • Hold a bachelor’s degree or legal equivalent. 
  • Are in the final year of a bachelor’s degree, applying on a conditional basis, and provide proof of completion by the last day of enrolment for the phase in which they applied, under penalty of exclusion. 
  • Hold a foreign higher education degree awarded after a first cycle of studies organised according to the Bologna Process by a signatory country. 
  • Hold a foreign higher education degree recognised by the Scientific and Technical Council (CTC) of ISEP as equivalent to a bachelor’s degree. 
  • Hold an academic, scientific, or professional record recognised by the Scientific and Technical Council (CTC) of ISEP as sufficient to access the master’s degree programme.

 

If you need the recognition by ISEP’s Scientific and Technical Council (CTC), you must request it in advance. Please contact the Academic Division or the programme director (contact available on the course webpage, right sidebar) for guidance. 

It is also possible to request degree recognition through DGES: https://www.dges.gov.pt/en/pagina/degree-and-diploma-recognition. 

Access to Further Studies

What if you want to continue studying? 

Doctoral Program in Artificial Intelligence and Intelligent Systems Engineering