Informatics Engineering

Objetives

The main objective of the Master in Informatics Engineering is to complement the broadband training acquired during a first degree in Computer Science, or equivalent, with advanced training in relevant areas of Computer Sciences and in other transversal areas. In particular, the Master shall:  

• Meet Bologna's assumptions in its various aspects, including teaching methodologies, length of study cycles, employability and student mobility 

• Offer training directly related to the real needs of the employing market 

• Capture the interest of the largest possible number of students of the first degree, either from the University of Algarve, or from other national and foreign universities 

• Foster the interest in research activities and offer the necessary training to attend a third training cycle leading to a PhD degree

Operating Mode

Classes take place every weekday from 2:00 p.m. to 8:00 p.m.

The Master's Degree consists of an organized set of course units corresponding to 90 ECTS credits, and a dissertation of a scientific nature, a project work or an internship of a professional nature, which corresponds to the remaining 30 ECTS credits.

The training model of the master's course is composed of the following groups of optional course units:

• Priority Axis Course Units – A set of course units of three priority axes: Intelligent Systems, Networks and Systems, and Software Science and Engineering, which allow the student to specialize in these topics. The student must take 60 ECTS in this set. 
• Nuclear Sciences Course Units – Set of course units considered core in the advanced training of a Computer Engineer. The student must take 12 ECTS from this set.
• Complementary Skills Course Units – Set of transversal and complementary competence course units (soft-skills). The student must take 3 ECTS from this set. 
• Dissertation/Project/Internship Project – Initial preparation work for a Dissertation or Project or Internship, corresponding to 15 ECTS, and carried out under the supervision of a PhD.
• Dissertation/Project/Internship  – Thesis of a scientific nature or a project work, original and specially carried out for this purpose, or an internship of a professional nature, subject to a final report, which corresponds to the remaining 30 ECTS credits. In any case, the Dissertation/Project/Internship will be carried out individually by the student under the guidance of a PhD.

Skills

• The Profile of General Skills of the Master in Informatics Engineering is developed along four fundamental components: (i) To Know (theoretical knowledge), (ii)To  Know How to Do (technical-professional knowledge), (iii) Social Know How (Social and relational skills) and (iv) Learning how to Learn (Cognitive skills).
• The Master promotes the development of the general skills of its students in each one of the aspects listed above. In particular:
• Consolidating knowledge in Engineering Sciences and in Computer Sciences
• Providing the ability to synthesize and analyze data, develop scientific and technological experiences and solve problems using carefully the available resources, namely those associated with computer resources
• Providing the ability to communicate, oral and written, data, ideas, problems and solutions to different audiences and in particular to audiences specialized in the field of Computer Science
• Fostering the sense of responsibility and professional ethics
• Providing the ability to work as a team and adapt to technological changes through continuous and autonomous curriculum development

The Master in Computer Engineering is able to demonstrate specific skills in:

• Analysis, design and development of information systems
• Analysis and development of distributed systems and parallel systems
• Relevant Programming Languages and Paradigms
• Information Systems Management
• IT systems project and management
• Advanced topics in network security and cybersecurity.
• Advanced Topics in Information Systems
• Computer network design and management, focusing on the Internet of Things
• Extraction of relevant information from large volumes of data
• Design of intelligent systems for solving complex problems
• Development and training of models using Generative Artificial Intelligence