Computer Engineering

O1. To understand basic ideas of management;

O2.To understand the historical approach of management;

O3.To understand the complexity of globalization;

O4.To understand the basic ideas of knowledge management.

O5.To understand the learning organization as knowledge discipline;

O6. To understand how important is the organizational culture to improve the organizational performance.

1. Basic foundations of management
2. Pioneering ideas of management
3. Globalization phenomenon
4. Knowledge management
5. Organizational learning
6. Organizational culture
7. Knowledge management and innovation.

OPTION 1:
Assessment throughout the term:
1.Involvement in class activities - 20%.
-Levels of attendance and punctuality.
-Participation in class.
-Answer of questions in class.
2. Test - 80%.
Passing grade is 10 points, with at least 7,50 points (out of 20) in the test.

OPTION 2:
End-of-term exam - 100%.
A positive evaluation means a grade of 10 or above (over 20).

OA1. Develop skills of inquiry and reflection on the social and ethical impact of computing, and evaluate possible ethical and technical responses to those questions.
OA2. To think critically on the impact of introducing a given technology or product in a given environment. Will this product or technology enhance or degrade quality of life? What will the impact be upon individuals, groups and organizations?
OA3. Identify values that guide the day-to-day activities of professional practices of computing and communication technologies, debating and becoming familiar with standards of good practice, codes of conduct and codes of ethics established by professional associations.
OA4. To learn or discuss approaches to ethical aligned design methods, which seek to align technologies with defined values and ethical principles that prioritize human well-being.

1·Ethics, computing, and society: The specificity of ethical issues in ICTs; Human rights in the digital age.
2·The responsibility of engineers. Active and passive responsibility. The context of technological development.
3·Normative ethics: Values, norms and virtues; Utilitarianism, Kant, Virtue ethics; normative argumentation.
4·Applied computer ethics and policy gaps: Ethical decision making and case studies.
5·Privacy and data protection: The GDPR.
6·Intellectual and industrial property: Copyright, the legal protection of computer programs; patents.
7·Artificial Intelligence: ethical principles and the AI act.

The evaluation in the 1st term is carried out throughout the semester or by exam.
The evaluation in the 2nd term is by exam only.

If the student opts for evaluation throughout the semester, it includes:

Group assignment: 60%
Individual written test: 38%
Attendance/participation: 2%

Both the group assignement and the written test have a minimum grade of 7 out of 20.

To obtain 100% in the attendance component, the student must attend at least 70% of the classes.

At the end of the course, the student should be able to:
1. Be able to understand and determine the security environment in information systems;
2. Understand and define access control policies;
3. Understand and apply some security controls and standards;
4. Offer advice on information and network security;
5. Develop and apply security plans and policies;
6. Reviewing and advising on certain security operations;
7. Designing plans to guarantee business continuity and resilience;
8. Understand and explain the role of encryption and data privacy in information security;
9. Establish policies and procedures for managing security incidents;
10. Understand software development problems and their security aspects.

1. Introduction to Information Security
2. Legal, Regulatory, Ethical, and Professional Aspects of Information Security
3. Information Security Planning
4. Asset and Risk Management in Information Security
5. Digital Network Security
6. Data Privacy
7. Cryptography
8. Information Security Architecture and Engineering
9. Identity Management and Access Controls
10. Security Assessment and Testing in Applications and Software Development

Assessment throughout the semester:
- Completion of a set of exercises and practical projects with group activities (50%) throughout the semester
- Completion of two individual midterm assessments (50%), [minimum score of 6 points for each test]. The first assessment takes place midway through the semester and the second on the first exam date.
Attendance at a minimum number of classes is not compulsory for the assessment throughout the semester.
Assessment by exam:
For students who opt for this process or for those who fail the assessment throughout the semester process, with 3 seasons under the terms of the RGACC.

LO1: Research user needs and the implications of modality and social conduct for interaction and experience.
LO2: Analyse multimodal interaction, groups of users, their communications, activities and contexts of use with respect to rich media.
LO3: Design input modalities, output media and interactive content to appeal to an audience.
LO4: Create and reflect upon critical design practice.
LO5: Understand the fundamental principles of data visualization for an effective communication.
LO6: Design analytic interfaces for business intelligence systems.
LO7: Compare and criticise different analytic interfaces.
LO8: Implement novel human-computer interactions adapted to different contexts.
LO9: To know how to analyse and quantify interface usability and user experience.

PC1: Understanding Contexts of interaction in human-computer interfaces
User Experience, Engagement and Communication
Analysis of users? needs
PC2: Designing User Experience (In Context)
Participatory Design
Designing Mobile Experiences and intelligent Environments
Designing for Multiple Channels
Designing for Participation (online communities and social computing)
Creative use of storyboarding
PC3: Challenges of visualization or information in human-computer interfaces.
Applied to a wide variety of contexts for communication.
Applied to Business Intelligence and decision support systems
PC4: Fundamental principles of data visualization
PC5: Design of analytic interfaces for decision support:
Reporting
Dashboards
PC6: Crucial concepts of storytelling
PC7: Prototyping of human-computer interfaces
PC8: Evaluating Usability and User Experience:
formative evaluation;
evaluating mobile interaction;
usability heuristics.

The student has two assessment methods: assessment throughout the semester and assessment by exam (for 100% of the grade). Given the practical nature of this course, we recommend the semester-long assessment method, which includes the development of a practical assignment.

Assessment throughout the semester consists of the following components:
- Project (in groups) (45%): includes the delivery of a report, final prototype and video.
- Presentation and discussion of the project (45%), with an individual grade.
- Data visualization exercise (in groups): 10%

Eligibility criteria for evaluation throughout the semester: minimum class attendance of 60% (30% user experience and 30% data visualisation classes) .
Minimum mark of 10 in all components. The working groups have 3 to 4 members. Given the large number of students, it is not possible to carry out individual projects.

The project has two binding partial deliveries to continue to be assessed throughout the semester. The first delivery (typically in week 7) includes the initial version of the user research, with the definition of the questionnaires to be carried out with users. The second delivery (typically in week 11) includes the complete version of the user research, with the analysis of the data from the user questionnaires. Each group will receive informal and formative feedback to improve the quality of the final project. Those who fail to complete the two partial deliveries will be assessed by exam.

The orals for the presentation and discussion of the project and the data visualization exercise will be held via Zoom, on a date to be agreed with each group. The marks for the orals are individual and all members of the group must be present at the oral.

Alternatively, the student can be assessed by a final exam worth 100% of the grade, in the 1st period, 2nd period and special assessment period.

After completing this course unit the student should be able to:
LO1. To know the technical, social and business forces that drive architectural choices.
LO2. To identify the main characteristics of a quality model for software architectures.
LO3. To describe an architecture using an adequate description language.
LO4. To recognize the major architectural styles of existing software systems.
LO5. To propose architectural alternatives for a problem and discuss their adequacy.

PC1. What Is Software Architecture and why it is Important
PC2 Understanding Quality Attributes (e.g. Availability, Interoperability, Modifiability, Performance, Testability)
PC3. Architectural Tactics and Patterns
PC4. Quality Attribute Modeling and Analysis
PC5. Architecture in Agile Projects
PC6. Architecture and Requirements
PC7. Designing an Architecture
PC8. Documenting Software Architectures
PC9. Architecture, Implementation, and Testing
PC10. Architecture Reconstruction and Conformance
PC11. Architecture Evaluation
PC12. Architecture and Software Product Lines

The practical nature of this curricular unit and the need for knowledge assessment to be carried out essentially through the ability of students to apply knowledge in the conception, design, implementation, validation, verification, deployment, maintenance and evolution of a software project, leads to the choice of a project-based evaluation method.

In the 1st season or normal season, evaluation throughout the semester, with no obligation of minimum attendance, with 3 evaluation moments of the group project:
- Presentation of progress mid-semester weighting 20% of the final grade;
- Final project report weighting 15% and software delivered weighting 35% of the final grade;
- Final presentation weighting 10% and discussion weighting 10% of the final grade.

The evaluation is based on the performance and individual contribution of each member of the group.

Or evaluation at the end of the semester (1st season), by individual project with 2 evaluation moments:
- Project report weighting 20% and software delivered weighting 45% of the final grade;
- Presentation of the work weighting 10% and discussion weighting 15% of the final grade.

In the 2nd season, grade improvement or special season (under the terms of the RGACC), assessment by individual project, available to students who request it:
- Project report weighting 20% of the final grade;
- Software delivered weighting 45% of the final grade;
- Presentation of the work weighting 10% of the final grade;
- Discussion of the work weighting 15% of the final grade.

All assessment periods include an assessment component carried out on the eLearning platform, with a weight of 10% (2 out of 20) in the final grade.

All assessment components, in all assessment periods, have a minimum score of 9.5 (out of 20).

At the end of the course the student should be able to:
OA1. Identify the main historical milestones of ML.
OA2. Know its relations with other scientific areas.
OA3. Enumerate and recognize some of its applications.
OA4. Know the characteristics of the main algorithms in the field of Machine Learning.
OA5. Know, and be able to explain, the main concepts of an algorithm that exemplifies: Supervised Learning (symbolic and sub-symbolic), Unsupervised Learning, Reinforcement Learning and Search Algorithms.
OA6. Explain in full detail one of the learning algorithms studied.
OA7. Implement a learning algorithm or use one in a non-trivial problem.

CP1. Historical notes on Machine Learning. Relationship with other displines. Applications.
CP2. Machine Learning problems and approaches;
CP3. Unsupervised Learning;
CP4. Supervised Learning (symbolic and sub-symbolic);
CP5. Reinforcement Learning;
CP6. Search methods and Genetic/Evolutionary Algorithms;
CP7. Data pre-processing, results validation;
CP8. Speedup of ML algorithms;
CP9. ML algorithm implementation.

It is only possible to pass this course by assessment throughout the semester, this course has no exam.

Assessment elements:
- 4 practical exercises, code and report, in groups of 2 (10% each) during the academic term with face-to-face discussion;
- 1 test (20%), during the academic term;
- group project (40%) which includes a report, code and oral presentation

The assessment in the special season will consist of the project carried out individually and, as in the other terms, to be handed in one week before the special term and a written test which replaces the component of the practical exercises and mini-tests. The weights of these assessment elements are the same as those indicated above.

Attendance is not used as an evaluation or failure criterion.

The Information Systems Management (GSI) Curricular Unit (UC) aims to promote knowledge, planning, development and exploration of Information Systems, from different perspectives, allowing each student to have “their own path” in the program content . In this way, each student will have obtained a differentiated set of knowledge, supported by the Program and capable of supporting the learning objectives identified below.

I. Management and Management of ISs in the Company
The. Manage the organization and manage Information Systems and Technologies (ITS)
B. Concerns of STI Managers
w. Impact of STIs on Organizations
II. Information Systems and Technologies Planning
The. STI Strategy in Organizations
B. Business Vision by STIs
w. Align STI strategy with Business strategy
III. Develop Information Systems and Technologies
The. Architecture Concept in ITS
B. Frameworks and Reference Models for STI
w. Information Management and Knowledge Management
IV. Explore Information Systems and Technologies
The. Project management
B. Telecommunications, the Internet and wireless technologies
w. IS security

Continuous evaluation:
1. Group Work – 70% of the final grade
Classroom presentation 20% (min grade 9.5 val.)
Final Report – submission in Moodle 50% (min grade 9.5 val.)
2. Individual Work – 30% of the final grade
Chapter summary in research format 20% (min grade 9.5 val.)
Note: one submission per student (of one of the four chapters) – Moodle submission of support pdf
Intervention in the room per pitch of 5 minutes 10% (min. score 9.5 val.)
Note: one pitch per student – ​​Moodle submission of support pdf
Rating by Exam:
Exam 1st Season, 2nd Season, and Special Season (alternative to the previous ones)
Written Test (50%) + Case Report (50%) – statement to be provided by the teacher and submitted in Moodle

After completing this course unit the student should be able to:
LO1. Know the fundamentals of functional programming
LO2. Apply meta-programming mechanisms
LO3. Design APIs (application programming interfaces)
LO4. Develop reusable software

PC1. Introduction to Kotlin programming language
PC2. Meta-programming and annotations
PC3. Design patterns for extensibility
PC4. Plugin-based systems

Periodic assessment:
- In-class quizzes (20%)
- Mid-term project evaluation (20%), to present during the semester
- Project (60%), to deliver and defend during the exam season

It is compulsory to attend at least 50% of the scheduled lectures and lab classes.

Project is the only form of evaluation, it is not possible to be evaluated through an exam. Evaluation in Época Especial requires delivering and defending the Project, with the requirement that its development should have been supervised during the semester classes.