The Master in Artificial Intelligence Engineering (MEIA) is a bet on Excellence, Innovation and the Future, accredited for the maximum period (6 years) by the Accreditation Agency (A3ES).
This Programme aims to offer a Programme preparing students for the new trends in Computer Engineering, in particular for Artificial Intelligence, which at the moment appear to be very strong in large companies and with a high factor in creating new startups, and spinoffs.
The programme will make a strong alignment between the training offer of the Department of Computer Engineering and the resident competencies in terms of R&D, namely by the existence of an ISEP R&D Unit with the ranking of Excellent (GECAD - Engineering Research Group and Intelligent Computing for Innovation and Development) by FCT.
The Programme covers the main methodologies and technologies of Artificial Intelligence (AI) in a comprehensive way, namely: AI Programming Paradigms; Knowledge Engineering; Planning and Decision Support; Machine Learning; Natural Language; Intelligent Environments; Internet of Things; Computer Vision; Robotics; Intelligent Agents; AI Social Aspects; AI Research and Innovation; AI Applications; Preparation and Development of Internship / Project / Dissertation.
It is also the objective of the Master to encourage pedagogical innovation practices, especially those that inculcate complex problem-solving skills, critical thinking and creativity, the 3 main cross-cutting skills planned for 2020 by employers (Top 10 Soft Skills 2020).
The Master allows to follow careers like Big Data Engineer; Business Intelligence Engineer; Computer Vision and Intelligent Robotics Engineer; Data Scientist; Decision Support Engineer; Entrepreneur; Higher Education Professor; Human-AI System Interaction Engineer; Innovation Expert; Intelligent Systems Consulting; Knowledge Engineer and Manager; Machine Learning Engineer; and Researcher.
1º Year | ||
---|---|---|
Curricular unit | Period | ECTS |
Machine Learning 1 | 1st Semester | 7.5 |
Knowledge Engineering | 1st Semester | 7.5 |
Programming Paradigms in Artificial Intelligence | 1st Semester | 7.5 |
Planning and Decision Support | 1st Semester | 7.5 |
Intelligent Environments | 2st Semester | 7.5 |
Machine Learning 2 | 2st Semester | 7.5 |
Natural Language and Conversational Systems | 2st Semester | 7.5 |
Multi-Agent Systems | 2st Semester | 7.5 |
2º Year | ||
Curricular unit | Period | ECTS |
Social Aspects of Artificial Intelligence | 1st Semester | 7.5 |
Applied Artificial Intelligence | 1st Semester | 7.5 |
Research and Innovation in Artificial Intelligence | 1st Semester | 7.5 |
Preparatory Work of Project/Dissertation/Internship | 1st Semester | 7.5 |
Project/Dissertation/Internship | 2st Semester | 30.0 |