Computer Engineering
Computer Engineering
Programme Introduction
The Master in Computer Engineering – Mobile Computing aims to confer a professional specialization with great emphasis on mobile computing and related technologies, allowing a series of studies to the holders of a degree in Computer Engineering, and related courses, including the possibility of expertise to professionals in the labour market.
Programme Coordinator
Luís Alexandre Lopes Frazão
coord.mei-cm.estg@ipleiria.pt
Reference
School
City
Language
Type
Length
Vacancies
General and International Contingent: 40
Notice
Edital 2026 (PT doc retf)
Edital 2026 (retf)
DGES certification
Objectives
The graduate students of the study cycle should be able to:
- Apply the knowledge and the ability to understand and solve problems in new and unfamiliar situations, and in broad and multidisciplinary contexts;
- Integrate knowledge, handle complex issues, develop solutions and make judgments in situations of limited or incomplete information;
- Communicate the conclusions achieved and the knowledge acquired, both to specialists and non-specialist in the field of Mobile Computing;
- Develop skills that allow a life-long learning fundamentally in a self-oriented or independent way.
Study Plan
- 1st Year
- 2nd Year
| ID | Name | Semester | ECTS | Length |
|---|---|---|---|---|
| Emerging and Intelligent Technologies | 1st Semester | 6 | 52,5 h | |
|
1. Concepts on Emerging and Intelligent Technologies; 2. Emerging Technologies; 3. Intelligent Ecosystems; 4. Industry 4.0 and 5.0; 5. Internet of Unmanned Vehicles; 6. Smart Solutions: applications, architectures and technologies; 7. Development of intelligent solutions supported by emerging technologies. | ||||
| Machine and Deep Learning | 1st Semester | 6 | 45 h | |
|
1. Introduction to machine learning 2. Neural networks 2.1 Structure of an artificial neuron 2.2. The Perceptron 2.3 Multi-layer perceptron 2.4 Activation functions 2.5 Stochastic gradient 2.6 Backpropagation algorithm 2.7 Loss functions 2.8 Validation and evaluation of models 2.9 Regularisation and optimisation 3. Convolutional neural networks 3.1 Convolutional layers 3.2 Pooling layers 3.3 Dense layers 3.4 Training a convolutional neural network 3.5. Transfer learning 3.6. Applications in image processing 4. Recurrent neural networks 5. Attention mechanism 6. Graph neural networks 7. Reinforcement learning | ||||
| Virtual and Augmented Reality | 1st Semester | 6 | 52,5 h | |
|
1. introduction to Virtual Reality (VR), Augmented Reality (AR) and Mixed Reality 2. User interaction based on VR and AR 3. Using VR and AR in digital twins 4. Development of VR and AR solutions 5. Evaluating VR and AR solutions | ||||
| Development for Mobile Devices | 1st Semester | 6 | 52,5 h | |
| ||||
| Option I | 1st Semester | 6 | 45 h | |
|
Students must choose one of the following curricular units: Design and Development of Digital Games 1. Game Design 2. Games User Experience 3. Introduction to a contemporary game engine 4. 2D and 3D development 4.1. Simulação de Física 4.2. Animação 4.3. UI e Menus 4.4. Áudio 5. Game Programming Patterns Management of Informatic Projects
| ||||
| Cloud Computing | 2nd Semester | 6 | 52,5 h | |
|
1. Introduction to cloud computing 1.1 Paradigm and conceptual model 1.2 Basic concepts and terminology 1.3 Goals and benefits, risk and challenges 1.4 Usage scenarios 2. Concepts and models 2.1 Cloud computing characteristics 2.2 Delivery models 2.3 Deployment models 2.4 Service-Level Agreement 3. Performance, scaling and load balancing 3.1 Performance and scale 3.2 Vertical scaling 3.3 Horizontal scaling 3.4 Load balancing 3.5 Performance tests and analysis 4. Security and disaster recovery 4.1 Security models applied to cloud computing 4.2 Techniques and procedures for disaster recovery applied to cloud computing 5. Tools, procedures and economic models 5.1 Developer point-of-view 5.2 Enterprise point-of-view 5.3 Startup point-of-view 6. Orchestration of cloud services 6.1 Planning and defining a cloud orchestration architecture 6.2 Implementing and monitoring a cloud orchestration | ||||
| Advanced Topics in Artificial Intelligence | 2nd Semester | 6 | 45 h | |
|
1. Types of Artificial Intelligence 2. Deep Learning in Natural Language Processing 2.1 Text data preparation 2.2 Representation of groups of words 2.3 Transformer architecture 2.4 Sequence-to-sequence learning 3. Generative deep learning 3.1 Text generation 3.2 DeepDream image modification 3.3 Neuronal style transfer 3.4 Image generation with variational autoencoders 3.5 Generative adversarial networks (GAN) 4. Explainability models 5. Good practices 5.1 State of the art of deep learning models 5.2 Model training optimization | ||||
| Cybersecurity | 2nd Semester | 6 | 45 h | |
| ||||
| Option II | 2nd Semester | 6 | 45 h | |
|
Students must choose one of the following curricular units: Enterprise Architectures 1. Enterprise Architectures 1.1 Introduction to EA 1.2 Frameworks and Tools 1.3 ArchiMate 1.4 TOGAF 2. Service-Oriented Architectures (SOA) 2.1 SOA Principles and strategy 2.2 SOA patterns 3.Enterprise IS foundations 3.1 ESB 3.2 API management & (micro) Service Layers 3.3 Identity Services 3.4 RPA 4. Technologically Innovative Business Models 4.1 Busines Analysis Overview 4.2 Digital Business Case studies 4.2.1 Artificial Intelligence 4.2.2 Augmented Reality 4.2.3 Natural User Interfaces 4.2.4 Analytics & Visualization 4.2.5 Blockchain 4.2.6 E-commerce & SAAS 4.2.7 Crowdfunding 4.2.8 Robotics Software Quality 1. Software Testing 1.1. Fundamentals of Testing 1.2. Testing Throughout the Software Lifecycle 1.3. Static Techniques 1.4. Test Design Techniques 1.5. Test Management & Tool Support for Testing 2. The Deployment Pipeline that supports Continuous Integration 2.1. Foundations of Software Delivery 2.2. Defining a Deployment Pipeline 2.3. The Commit Stage 2.4. Automated Acceptance Testing 2.5. Deploying and Releasing Applications 3. Quality Attributes in Software Architecture 3.1. Understanding Quality Attributes 3.2. Architecture and Quality 3.3. Containerisation Free Option | ||||
| Ambient Intelligence and Internet of Things | 2nd Semester | 6 | 52,5 h | |
|
Internet of Things: concept, communication, architectures and interoperability. Smart Objects and Ambient Intelligence: context, interface and user activities. Learning models for adaptive and evolving environments. Ambient Intelligence Project. | ||||
| ID | Name | Semester | ECTS | Length |
|---|---|---|---|---|
| Project / Internship / Dissertation | Anual | 54 | 40 h | |
|
Project Students will develop an original work in the Computer Engineering – Mobile Computing scientific areas. The work plan shall be approved by the school scientific body and shall be mostly done in academic and research environment. Internship Students will develop an original work in the Course’s scientific areas. The work plan shall be approved by the school scientific board and shall be mostly done in a professional environment. Dissertation Students will develop an original work in the Computer Engineering – Mobile Computing scientific areas. The work plan shall be approved by the school scientific body and shall be mostly done in academic and research environment. | ||||
Entry Requirements
People who can apply to the Master’s Degree:
- Holders of an undergraduate degree or a legal equivalent in Computer Engineering, and related fields;
- Holders of a foreign higher education diploma, granted after a first cycle of studies, under the principles of the Bologna Process, by a State, which has subscribed this Process, in Computer Engineering, and related fields;
- Holders of a foreign higher education diploma that is recognized as meeting the objectives of an undergraduate degree by the Technical and Scientific Council of the School of Technology and Management, in Computer Engineering, and related fields;
- Holders of an academic, scientific or professional curriculum that is recognized as certifying the skills to attend this cycle of studies by the Technical and Scientific Council of the School of Technology and Management.
.
People who can apply to the Master’s Degree:
- Holders of an undergraduate degree or a legal equivalent in Computer Engineering, and related fields;
- Holders of a foreign higher education diploma, granted after a first cycle of studies, under the principles of the Bologna Process, by a State, which has subscribed this Process, in Computer Engineering, and related fields;
- Holders of a foreign higher education diploma that is recognized as meeting the objectives of an undergraduate degree by the Technical and Scientific Council of the School of Technology and Management, in Computer Engineering, and related fields;
- Holders of an academic, scientific or professional curriculum that is recognized as certifying the skills to attend this cycle of studies by the Technical and Scientific Council of the School of Technology and Management.
.
Accreditation
State: Accredited
Number of years of accreditation: 6
Publication date: 23/01/2020
A3ES Accreditation
State: Accredited
Number of years of accreditation: 6
Publication date: 23/01/2020
A3ES Accreditation
More Information
International Student
All information related to the international student application should be consulted on our International Students webpage.
Contacts
E-mail: studywithus@ipleiria.pt
International Student
All information related to the international student application should be consulted on our International Students webpage.
Contacts
E-mail: studywithus@ipleiria.pt
Application Fee
60€
Enrolment Fee
General contingent: 50€
International student contingent: 100€
General contingent: 50€
International student contingent: 100€
Tuition Fee
General contingent: 697 €
International student contingent: 3000€
General contingent: 697 €
International student contingent: 3000€