LG1. Review the concept of function and its properties. Types of functions and operations with functions.
LG2. Graphics of elementar functions and function transformations.
LG3. Limits, indeterminations and graphic interpretation. Continuity.
LG4. Derivatives and its applications. Graphic interpretation.
LG5. Linear approximations and higher order approximations.
LG6. Derivative of composed functions and inverse functions.
LG7. Calculations with matrices and vectors.
LG8. Calculating detrminants and applicating its proprieties.
LG9. Knowing the concept of linear transformation and representation with matrices.
LG10. Calculating eigenvalues and eigenvectors.

PC1. Function. Elementar functions, Different type of functions. Operations with functions. Logaritmic and trigonometric functions.
PC2. Limits of a function at a point, Continuity at a point. Assimptotic lines.
PC3. Derivative of a function at a point. Derivative rules. Optimization problems.
PC4. Derivative of composed functions – chain rule. Derivative of the inverse function.
PC5. Linear approximation and Taylor approximation.
PC6. Solving linear equation systems. Matrices and operations. Inverting matrices. Determinants and properties. Linear transformations.
PC7. Real vector space. Inner product. Parallelism and perpendicularity.
PC8. Eigenvalues, eigenvectores and matrix diagonalization.

Passing with a grade not lower than 10 points in one of the following modalities:
- Assessment throughout the Semester:
* 7 assignments/mini-tests conducted during classes. The best 5 are counted, each with a weight of 5% (total of 25%).
* autonomous work, with a weight of 5%.
* applied mathematics project, with a weight of 10%.
* Final test to be conducted on the date of the first exam period, with a weight of 60% and a minimum grade of 8 points
or
- Examination Assessment (100%).

There is the possibility of conducting oral examinations.
Grades above 17 points must be defended orally.

At the end of this course, the student should be able to:
LO1. Understand cybersecurity in its different perspectives
LO2. Understand the main security challenges and threats that organisations and users have to face;
LO3. Introduce the legal, ethical and strategic context of information security
LO4. Identify and manage information security risk;
LO5. Know and apply appropriate security technologies for risk mitigation;
LO6. Know mechanisms for the management and maintenance of information security environments.

SC1. Introduction to Cybersecurity: main components; cybersecurity pillars; cybersecurity frameworks.
SC2. Information Security Planning and Legal and Ethical Framework
SC3. Principles of Information Security Governance and Risk Management
SC4. Introduction to Information Security Technology: access controls, firewalls, vpns, idps, cryptography and other techniques.
SC5. Physical Security: physical access control mechanisms, physical security planning, among others.
SC6. Information Security Implementation: information security project management; technical and non-technical aspects of information security implementation.
SC7. Personnel Security: personnel security considerations; personnel security practices.
SC8. Maintenance of Information Security.

Assessment throughout the semester:
- Carrying out a set of group projects and activities (60%) throughout the semester.
- Two individual tests (40%) [minimum mark of 6 for each test].
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 periodic assessment process, with 3 seasons under the terms of the RGACC.

By the end of this course unit, the student should be able to:
LO1: Apply fundamental programming concepts.
LO2: Create procedures and functions with parameters.
LO3: Understanding the syntax of the Python programming language.
LO4: Develop programming solutions for problems of intermediate complexity.
LO5: Explain, execute and debug code fragments developed in Python.
LO6: Interpret the results obtained from executing code developed in Python.
LO7: Develop programming projects.

PC1. Integrated development environments. Introduction to programming: Logical sequence and instructions, Data input and output.
PC2. Constants, variables and data types. Logical, arithmetic and relational operations.
PC3. Control structures.
PC4. Lists and Lists of Lists
PC5. Procedures and functions. References and parameters.
PC6. Objects and object classes.
PC7. File Manipulation.

This course follows a semester-long project-based assessment model due to its predominantly practical nature, and does not include a final exam.

Students are assessed based on the following components (A1 + A2):
A1: Learning Tasks with teacher validation (30%)
Five learning tasks will be completed throughout the semester.
The A1 grade corresponds to the average of the grades for the five tasks. To pass A1, the student must meet one of the following requirements:
- obtain at least 7 points in each of the five tasks
or
- obtain a minimum average of 8 points across the five tasks.

A2: Mandatory Group Project (3) with theoretical-practical discussion (70%)
Minimum grade of 9.5 points.
Late submissions will result in penalties.

Remediation:
Students who do not achieve the minimum overall grade may complete an individual Practical Project (100%) with oral discussion.
If a student misses an exam due to absence, or does not achieve the minimum grade of 7 points, they may take a make-up exam at the end of the semester.

Attendance:
A minimum attendance of 2/3 of classes is required.

The objective of the UC is to develop a technological project in line with the scope of the Course. Contact will be established with project planning considering the main phases: Requirements analysis, development, partial tests and final tests and changes. Contact with laboratory equipment and tools is one of the goals for designing a software, hardware or both project.

I. Introduction to technological innovation along the lines of Europe
II. Planning a technological project and its phases
III. Essential aspects for the development of a project
IV. Definition of material resources
V. Budget of a project
VI. Partial and joint Test Plan
VII. Presentation of a technological project
VIII. Technological project demonstration
IX. Preparation of Technical Report

Periodic grading system:
- Group project: first presentation: 30%; second presentation and exibithion: 40%; final report: 30%. The presentations, demonstrations and defence are in group.

LO1: Know the basic operating principles of a computer system
LO2: Make a clear distinction between hardware and software and explain how they interact
LO3: Identify the main physical components of a computer and describe their functions
LO4: Understand and describe different computer architectures
LO5: Understand how a computer runs programs and how it communicates with other computers and users
LO6: Know the components of operating systems (OS), describe their functions and how they are implemented in different OSs
LO7: Distinguish between different types of OS and their practical applications
LO8: Use the command line, scripts and the OS graphical environment to carry out administration tasks
LO9: Understand hardware and OS virtualization and their relevance to saving resources
LO10: Know how to implement hardware virtualization in type II hypervisors and in the cloud, and OS components in the Docker environment

PC1: Introduction to number bases 2, 8, and 16; binary addition and subtraction; coding and representation of information (ASCII and others).
PC2: Computer structure: system board; CPU (processor architecture); memories; BUS; storage system; graphics cards; communication ports; peripherals.
PC3: Components of Operating Systems (OS): Process management; Memory hierarchy; Input and output management; File system; Administration and security.
PC4: Study of Linux and Windows OS commands.
PC5: Hypervisors type II (VMware, VirtualBox) - Create, OS configuration, export and import of virtual machines (VMs) Windows (client and server), Linux (client, firewall and email servers, VoIP, storage); Networking VMs.
PC6: Clouds (Azure and others)—Create Windows and Linux VMs; access and use VMs in clouds. Containers (Docker) - virtualization of OS components.

The CU follows the project-based assessment model due to its eminently practical nature, and does not include a final exam.
A minimum attendance of 80% of classes, presentations, and other events that may be considered necessary for learning is required. Attendance and participation in theoretical-practical-laboratory courses are essential.
It is mandatory to complete 80% of the practical work.
The laboratory project, in groups, is mandatory. Groups of 5 or 6 students.
Summative assessment weights:
SA1: 2 practical assignments (12.25% each): 25% -> 2 group practical assignments (Hardware + OS, OS + Virtualization).
SA2: 2 mini-tests: 25% -> multiple-choice tests, carried out individually, on Moodle in the classroom, without consultation. Each mini-test covers half the subjects.
SA3: Laboratory project, with group presentation and demonstration and individual oral discussion: 50% -> the project work is eliminatory. Anyone who does not achieve a minimum mark of 9.5 out of 20 for the project fails the course.
Those who pass the project but fail the other components (< 9.5 out of 20) can make up the grade in the 2nd season by taking a test that includes the whole subject and is worth 50% of the grade, replacing the individual assignments and mini-tests (which also cover the whole subject). In order to take the 2nd season test, it is compulsory to pass the laboratory project, which contributes 50% to the final grade. For those who have already passed the 1st season assessment, they can take the 2nd season test to improve 50% of their final grade.
Formative assessment:
- Exercises and standard tests are made available on Moodle so that students can self-assess their knowledge.
- For those who require it, question timeframes are available for discussion and guidance on how to carry out the project.

At the end of the course, students should be able to:
LO1: Create and Manipulate Data Structures
LO2: Apply the most appropriate sorting and search algorithms for a specific problem
LO3: Analyze the complexity and performance of an algorithm
LO4. Identify, implement, and analyze the most appropriate data structures and algorithms for a certain problem

S1. The Union-Find data structure
S2. Algorithm analysis
S3: Data structures: stacks, queues, lists, bags
S4: Elementary sorting: selectionsort, insertionsort, shellsort
S5: Advanced sorting: mergesort, quicksort, heapsort
S6. Complexity of sorting problems
S7: Priority Queues
S8. Elementary symbol tables
S9. Binary search trees
S10. Balanced search trees
S11. Hash tables

Period 1: Assessment throughout the semester or Final Exam
Assessment throughout the semester, requiring attendance at least 3/4 of the classes:
- 2 practical tests (60%), with a minimum grade of 7.5 in each.
- 2 theoretical tests (40%), with a minimum grade of 7.5 in each.
The final weighted average between the theoretical and practical tests must be equal to or higher than 9.5.
Assessment by Exam:
- (100%) Final Exam with theoretical and practical components
Students have access to the assessment by Exam in Period 1 if they choose it at the beginning of the semester or if they fail the assessment throughout the semester.
Period 2: Final Exam
- (100%) Final Exam with theoretical and practical components
Special Period: Final Exam
- (100%) Final Exam with theoretical and practical components

LG1 Dominate the concepts of sequence and numerical series
LG2 Calculate limits of sequences and, relative to a series, find out the existence of sum
LG3 Understand the generalization of the concept of series to functional series and obtain the convergence domain
LG4 Understand the definition of integral as the limit of Riemann sums
LG5 Calculate primitives and apply them to determine the value of integrals
LG6 Apply integrals to calculate areas, lengths and mean values
LG7 Solve 1st order linear ordinary differential equations (ODEs)
LG8 Calculate partial derivatives and directional derivative
LG9 Interpret the gradient vector as the direction of maximal increase of a function
LG10 Decide about the existence of a tangent plane
LG11 Obtain the 1st order Taylor development and, explore numerically in higher order
LG12 Obtain unconstrained extrema(otimization)

PC1 Sequences. Monotony. Bounded sequences. Geometric progression
PC2 Convergence of sequences
PC3 Numerical series, partial sums and sum
PC4 Convergence criteria of series of non-negative terms
PC5 Simple and absolute convergence of alternating series. Leibniz's criterion
PC6 Power series and domain of convergence
PC7 Antiderivatives. Riemann definite integral. Fundamental theorem of calculus
PC8 Integration by parts and change of variables. Decomposition into simple fractions
PC9 Applications of integral (area, length, mean value)
PC10 Improper integral and convergence
PC11 First order linear ODE
PC12 Multivariable real functions. Level curves. Limits and continuity
PC13 Partial derivatives at a point and gradient vector. Linear approximation, tangent plane and differentiability
PC14 Directional derivative. Chain rule. Taylor's polynomials and series
PC15 Quadratic forms and otimization problems

Approval with a grade >= 10 points (out of 0 to 20) in one of the following modalities:
- Assessment throughout the semester:
* 4 mini-tests conducted during classes, each with a weight of 5% (total of 20%).
* Mid-semester test (15%).
* Autonomous work (5%).
* Final test (60%) on the date of the first exam period, with a minimum grade of 8 points.

Or

- Assessment by exam (100%).

There is the possibility of conducting oral exams.
Grades above 17 points must be defended orally.

LO1: Understand the main theories, concepts, and issues related to Work, Organizations, and Technology;
LO2: Understand the main processes of the digital transition directly related to the world of work and its organizations;
LO3: Analyze the multiple social, economic, and political implications brought by the digital transition;
LO4: Explore cases, strategies, and application methods to understand the real impacts of the digital transition on professions, companies, and organizations.

PC1. Is work different today than it was in the past?
PC2. What rights and duties in the world of work?
PC3. How has theory looked at technology?
PC4. What digital technologies are changing work?
PC5. What future for work?
PC6. Is artificial intelligence really that intelligent?
PC7. Where does precariousness begin and end?
PC8. Who is to blame when the machine makes a mistake?
PC9. Do digital technologies change the relationship between unions and companies?
PC10. What digital transformation in Portugal?

Continuous assessment throughout the semester:
Each student will conduct a Flipped Classroom session, which represents 20% of the final grade.

Individual work accounting for 35% of the final grade.

Group work accounting for a total of 35% of the final grade (10% for the group presentation and 25% for the written work).

Attendance and participation in classes represent 10% of the final grade. A minimum attendance of no less than 2/3 of the classes is required.

Each assessment element must have a minimum grade of 8. The final average of the various elements must be equal to or greater than 9.5.

Examination evaluation (1st Period if chosen by the student, 2nd Period, and Special Period): in-person exam representing 100% of the final grade with a minimum grade of 9.5.

Upon completing this course unit, students should be able to:

LO1. Understand the model proposed by the von Neumann architecture.

LO2. Recognise the relationship between software and hardware.

LO3. Understand how the basic components of a CPU interact and grasp the fundamental concepts of GPU architecture.

LO4. Comprehend the interaction between the CPU, GPU, and the memory and peripheral subsystems.

LO5. Understand the memory hierarchy and its impact on performance.

LO6. Comprehend key performance metrics and basic performance analysis techniques.

S1 Historical evolution of computers, human-computer interaction, impact on modern computing; von Neumann architecture: model, characteristics, limitations; alternatives.
S2 Binary representation, data types, instruction and program storage; code translation: programming languages, compilers, assembly.
S3 Instruction types and formats, addressing modes, memory access, execution cycle; control flow, data transfer.
S4 CPU, GPU, and Peripherals: CPU structure and components (ALU, CU, registers), internal organisation, data and control flow, pipeline concepts; introduction to GPU; motherboard, communication ports, peripherals.
S5 CPU-memory interaction, storage hierarchy, cache (mapping, replacement), main memory, persistent storage (HDDs, SSDs), virtual memory.
S6 Performance metrics (CPI, MIPS, FLOPS), factors influencing performance, analysis and optimisation of memory and processor usage, role of the operating system.

The assessment can be carried out in one of the following modes:

Assessment throughout the semester:

Two written tests during the semester, with a minimum grade of 8 out of 20 for each test (30% + 30%).

Group practical project and its oral presentation (40%).

Once the practical group work has been completed, if the student does not obtain the minimum grade in the written assessment tests, they may take the theoretical component assessment in an exam worth 60%.

Final Exam Assessment:

Written exam (100%).

To pass the course unit, students must achieve a final grade of 9.5 or higher out of 20.

LO1. Acquiring knowledge about the fundamentals and stages of the Design Thinking process
LO2. Develop skills such as critical thinking, collaboration, empathy and creativity.
LO3. To apply Design Thinking in problem solving in several areas, promoting innovation and continuous improvement.

S1. Introduction to Design Thinking and Stage 1: Empathy (3h)
S2. Steps 2 and 3: Problem Definition and Ideation (3h)
S3. Step 4: Prototyping (3h)
S4. Step 5: Testing and application of Design Thinking in different areas (3h)

Semester-long Assessment Mode:

• Class participation (20%): Evaluates students' presence, involvement, and contribution in class discussions and activities.

• Individual work (40%): Students will develop an individual project applying Design Thinking to solve a specific problem. They will be evaluated on the application of the stages of Design Thinking, the quality of the proposed solutions, and creativity.

• Group work (40%): Students will form groups to develop a joint project, applying Design Thinking to solve a real challenge. Evaluation will be based on the application of the steps of Design Thinking, the quality of the solutions, and collaboration among group members.

To complete the course in the Semester-long Assessment mode, the student must attend at least 75% of the classes and must not score less than 7 marks in any of the assessment components. The strong focus on learning through practical and project activities means that this course does not include a final assessment mode.

OA1 - To be trained in the ethical and responsible use of Generative Artificial Intelligence (AI) tools
OA2 - To acquire critical analysis skills on the results produced by Generative AI tools
OA3 - To be able to identify and develop creative solutions in solving ethically and socially complex problems with Generative AI
OA4 - To be able to apply Generative AI tools in the preparation of academic work, in particular in the application of academic writing and in the use of normative citation and referencing procedures.

CP1 - Introduction to AI and Generative AI:
* Theoretical exposition on the historical context, evolution and important concepts about Artificial Intelligence (AI) and Generative AI
CP2 - Prompt Engineering:
* Explanation of good practices for interacting with generative language models
CP3 - Generative AI Tools:
* Exploration of multiple Generative AI tools, based on text, images and videos
CP4 - Formation of argumentative content:
* Development of creative solutions using argumentation practices and Generative AI tools
CP5 - Rules for scientific writing:
* Application of citation and referencing standards (APA standards) in academic writing

The Semester-Long Assessment includes the following activities:
1. Individual Activities (50%)
1.1 Prompt Simulations with AI Tools in an Academic Context (20%):
* Description: The student must create a clear/justified, well-structured prompt, according to the script proposed by the instructor in class.
* Assessment: (submit in Moodle), communication and teamwork skills based on the quality of the prompt simulations performed.
1.2 Oral Defense - Group Presentation - 5 min. Discussion - 5 min. (30%):
* Description: Each student must present their contributions to the work completed to the class.
* Assessment: After the student's presentation, there will be a question-and-answer session.
2. Group Activities (50%) [students are organized into groups of up to 5 students, randomly selected], which include:
* Group presentations, reviews, edits, and validations of AI-generated content. The assessment (to be submitted in Moodle) includes gathering relevant information, assessing the clarity and innovative nature of the use of structured prompts.
* Development of strategies for reviewing, editing, and validating AI-generated content. Students will be asked to critically evaluate and reflect on the ethical challenges of integrating AI into an academic environment. The assessment (to be submitted in Moodle) will consist of correcting the work based on the accuracy and quality of the reviews and edits, as well as student participation in providing feedback to their peers.
* Final Project Presentation Simulations, where groups choose a topic and create a fictitious project following the structure of a technical report or scientific text. They present their project in class (5 min.) and discuss the topic (5 min.). The assessment (to be submitted in Moodle) will consider the organization, content, correct use of the structure, and procedures of the academic work.

General Considerations:
Feedback on student performance in each activity will be provided during the Semester Assessment.
To be assessed throughout the semester, students must attend 80% of classes and achieve a score of at least 7 points in each assessment.
If there are questions about participation in the activities, the instructor may request an oral discussion.
The group must ensure that at least one computer is available for each group to allow for classroom activities.
There will be no final exam assessment; passing will be determined by the weighted average of the assessments throughout the semester. Assessments in the second and special assessment periods will have an alternative assessment method, so any students wishing to take the assessment in these assessment periods should contact their instructor in advance to learn about the assessment procedure.

LO1. Develop specific oral communication skills for public presentations.
LO2. Know and identify strategies for effective use of the vocal apparatus.
LO3. Identify and improve body expression. LO4. Learn performance techniques.
The learning objectives will be achieved through practical and reflective activities, supported by an active and participatory teaching method that emphasizes experiential learning. The knowledge acquired involves both theatrical theory and specific oral communication techniques. Students will learn about the fundamentals of vocal expression, character interpretation and improvisation, adapting this knowledge to the context of public performances.

PC1. Preparing for a presentation.
PC2. Non-verbal communication techniques.
PC3. Voice and body communication, audience involvement. PC4. Presentation practice and feedback. The learning objectives will be achieved through practical and reflective activities, supported by the active and participatory teaching method which emphasizes experiential learning. Classes will consist of activities such as: Theatrical experiences and group discussions; Practical activities; Presentations and exhibitions of autonomous work; Individual reflection.

The assessment of the Public Presentations with Theatrical Techniques course aims to gauge the development of students' skills in essential aspects of public presentations. The assessment structure includes activities covering different aspects of the experiential learning process involving both theatrical techniques and specific communication techniques.
Assessment throughout the semester includes activities covering different aspects of the process of preparing a public presentation, including group and individual work activities:
Group activities (50%) [students are challenged to perform in groups of up to 5 elements, made up randomly according to each activity proposal].
1-Practical Presentations: Students will be assessed on the basis of their public presentations throughout the semester:
Description: each group receives a presentation proposal and must identify the elements of the activity and act in accordance with the objective.
The results of their work are presented in class to their colleagues (Time/group: presentation - 5 to 10 min.; reflection - 5 min.). Assessment (oral): based on active participation, organization of ideas and objectivity in communication, vocal and body expression, the use of theatrical techniques and performance. Presentations may be individual or group, depending on the proposed activities.
Individual activities (50%)
1-Exercises and Written Assignments (Autonomous Work):
Description: In addition to the practical presentations, students will be asked to carry out exercises and written tasks related to the content covered in each class. These activities include reflecting on techniques learned, creating a vision board, analyzing academic objectives, student self-assessment throughout the semester, answering theoretical questions and writing presentation scripts.
Assessment: (Oral component and written content), organization, content, correct use of the structure and procedures of the autonomous work proposed in each class, ability to answer questions posed by colleagues and the teacher. Communication skills and the quality of written work will be assessed, with a focus on clarity of presentation. These activities will help to gauge conceptual understanding of the content taught.
There will be no assessment by final exam, and approval will be determined by the weighted average of the assessments throughout the semester.
General considerations: in the assessment, students will be given feedback on their performance in each activity.
To complete the course in this mode, the student must attend 80% of the classes. The student must have more than 7 (seven) points in each of the assessments to be able to remain in evaluation in the course of the semester.

Upon completing this course, students should:
OA1: Recognise AI fundamentals, linking predicate logic and knowledge-based systems.
OA2: Build and interpret simple machine learning models, distinguishing classification from regression, and defining suitable evaluation metrics.
OA3: Apply deductive and inductive reasoning, understanding how knowledge representation and heuristics guide decision-making.
OA4: Critically analyse the suitability of AI approaches in specific contexts, considering data, performance, and ethical implications.
OA5: Implement basic Generative AI strategies, focusing on prompt engineering and innovative content generation.
OA6: Demonstrate autonomous research and experimentation skills, integrating AI concepts into collaborative projects.
OA7: Reflect on AI constraints and socio-economic impacts, adopting a responsible stance in methodology selection and application.

S1: Essential AI concepts: definition, historical evolution, and multidisciplinary relevance.
S2: Predicate logic and knowledge-based systems: representation, deduction, and applications.
S3: Reasoning methods and heuristics: informed and uninformed search, selecting suitable strategies.
S4: Introduction to machine learning: basic notions, classification and regression algorithms, evaluation metrics.
S5: Simple predictive models: design, implementation, and results analysis in real-world scenarios.
S6: Generative AI: foundations, prompt engineering, and creative applications.
S7: Critical approach to AI limitations, ethical challenges, and socio-economic implications.

The assessment of this curricular unit follows the model of Assessment Throughout the Semester (ALS), provided for in the RGACC, and includes several moments, organized into three assessment blocks (AB), aimed at measuring progress and consolidating knowledge. It is made up as follows:
AB1: Written Exam (40%)
Assesses the fundamental concepts of artificial intelligence, machine learning, and generative AI. The exam evaluates both theoretical understanding and the ability to apply the concepts in practice.

AB2: Final Project in AI (60%)
Conducted individually or in groups, this project involves the design, implementation, and evaluation of a prototype or case study based on the course content. It encourages integration of knowledge and critical reflection on the topics covered. Evaluation is divided into a written report (60%) and an oral presentation (40%), delivered during the final session.

Additional rules:
Each assessment block requires a minimum score of 8.5 points.
If necessary, an individual oral discussion may be conducted to confirm knowledge.
The final course grade is the weighted sum of both blocks, with a minimum of 10 points required to pass.

Upon completion of this course, students will be able to:
LO1. Understand the basic principles of how a computer network operates
LO2. Understand and comprehend the OSI and TCP/IP reference models
LO3. Understand how the main protocols used in everyday life work
LO4. Understand and comprehend the operation of transport-level protocols
LO5. Understand how devices are interconnected in a wired network
LO6. Be able to design, configure, and manage a computer network

PC1. Introduction to the physical layer. Presentation of the OSI and TCP/IP reference models
PC2. Introduction to the data link layer. Installation and configuration of a switch
PC3. Introduction to the network layer: IPv4 and IPv6 addressing; IPv4 protocol and subnet creation. Operation and configuration of a router
PC4. Exploration of TCP/UDP transport protocols. Congestion control
PC5. Exploration of the application layer: DNS, Email, and File Transfer
PC6. Traffic control between networks

It can be accomplished in one of the following ways:

1. Assessment throughout the semester:

Theoretical component
-1st test to be taken in the middle of the semester (30%);
-2nd test to be taken at the end of the semester (30%).
(there is also the possibility of doing a final exam (60%) for those who have failed the 1st and/or 2nd tests)

Practical component
-1 practical group assignment and its presentation (40%).

Note: Both tests have a minimum mark of 8 values, and it should be noted that the practical component is mandatory for the purposes of approval. The minimum grade for passing the course is 10 values.

2. Exam evaluation:
- It is available in the first or second seasons
- Written exam (100%)
The minimum mark for passing the course is 10 values.

Upon completion of this course students will be able to:
LO1. Understand the most common threats, attacks and vulnerabilities in computer networks
LO2. To know and understand the various security mechanisms for each network layer in the reference models
LO3. Know and explore security problems in several network protocols
LO4. To identify, analyse and correct security problems in computer networks.

SC1. Risks, Threats and Attacks to Communication Networks
SC2. Security at the Physical and Connection Level: Ethernet Networks; Attacks and Defenses; Security in Wi-Fi 802.11 Networks
SC3. Network Level Security: IPv4 and IPv6 Security; IPSEC Protocol; Attacks on protocols (ICMP, ARP and DHCP)
SC4. Transport level security: SSL/TLS protocol; SSH protocol; Virtual Private Networks: IPSEC and OpenVPN
SC5. Application-level security: DNS security; Secure e-mail; Secure file transfer
SC6. Firewalls: Typologies and security polivies configuration.
SC7. Intrusion Detection and Prevention: Types of systems (IDS, IPS, Network or Host-based). Honeynets and Honeypots. Usage and security configuration.

There are two possible modes as follows:
1. Assessment throughout the semester:
- Two written tests carried out during the semester with a minimum grade of 8 (in 20) in each test (30% + 30%)
- Two lab experiments in group (15%), with a minimum grade of 8 in each lab
- One practical work in group, including its oral presentation, with a minimum grade of 8 (25%)
2. Exam evaluation:
- Written exam (100%)

In order to pass the course, the student must obtain a grade of 10 or more.

At the end of this course, students should be able to:
OA1. Understand the ethical stance to adopt as a cybersecurity professional;
LO2. Realise the ethical and privacy implications of cybersecurity;
LO3. Understand the main national and international legislative references in the area of cybersecurity;
LO4. Identify the legal and privacy requirements for cybersecurity projects.

CP1. Ethics and technological development:
- Basic concepts and theoretical framework;
- Specificity of ethical issues in ICT;
- Responsibility in engineering;
- Applied ethics and normative ethics;
- Regulatory gaps;
- Ethics and cybersecurity.

CP2. Cybersecurity Legal Frameworks:
- EU Cybersecurity Strategy;
- National cyberspace security strategy (CM Res. no. 92/2019);
- Cybercrime Law (Law no. 109/2009);
- Legal framework for security in cyberspace (Dir. 2016/1148, and 2022/2555, Law no. 46/2018, and DL no. 65/2021);
- Artificial Intelligence Regulation (Regulation (EU) 2024/1689);
- Privacy and protection of personal data: GDPR, Law 58/2019 and Law 59/2019;
- Protection of privacy in the electronic communications sector: The e-privacy directive 2002/58/EC and Law 41/2004;
- International standards and technical specifications: ISO 27001, and other relevant ones. Implementing Regulation (EU) 2018/151. CM Resolution no. 41/2018.

Assessment throughout the semester:
- Group resolution of case studies (40%), with two deliveries during the semester [minimum mark of 7].
- Individual test in the 1st term (60%)
Attendance at a minimum number of classes is not compulsory for assessment throughout the semester.
Assessment by exam:
- For students who opt for this process or for those who fail the assessment process throughout the semester, with 3 seasons under the terms of the RGACC. The marks for case studies are not taken into account for students who choose to take an exam. Those who choose to take the assessment throughout the semester must take both components of the assessment.

LO1 Frame and understand the main components of the World Wide Web;
LO2 Know and correctly apply the client programming model and the MVC paradigm;
LO3 Use and extend server technologies to develop web applications and services;
LO4 Integrate web applications and services with Database Management Systems;
LO5 Understand the life cycle pipeline of a web project;
LO6 Develop creativity, technological innovation, critical thinking;
LO7 Develop self-learning, peer review, teamwork, oral expression.

S1 Introduction. The history of the Web. Programming languages for the Web; W3C standards.
S2 World Wide Web Architecture. Screen marking with HyperText Markup Language (HTML).
S3 Client-side programming. Structure description (HTML), style sheets (CSS) and dynamic updating of the graphical interface. Input validation; Introduction to client-side security.
S4 Server-side programming. Distribution of static content, dynamic generation of content and MVC design pattern. Services and communication between services. Introduction to server-side security.
S5 Data persistence. Integration with Database Management Systems
S6 Service-oriented web architectures. Web Services and Microservices. Middleware models for the Web. Containerization.

Course with Periodic Assessment, not by Final Exam.
Assessment weights:
- Lab project (in group between 2 and 4), with technical report, individual oral discussion (60%)
- 4 multiple response individual Mini-tests (40%)

A mark below 8 assigns (in average of mini-tests) the student to an exam in normal and/or the appeal period (40% of the mark) in a written test, with the completion and approval of the group project, or an individual project (with technical report and individual oral discussion) is mandatory (60%).

At the end of this UC, the student should be able to:
LG.1. Present the image of the product/service in a website
OA.2. Present the image of the product/service in social networks
OA.3. Describe functionalities of the product/service
OA.4. Describe phases of the development plan
OA.5. Develop a prototype
OA.6. Test the prototype in laboratory
OA.7. Correct the product/service according to tests
OA.8. Optimize the product/service considering economic, social, and environmental aspects
OA.9. Adjust the business plan after development and tests, including commercialization and image
OA.10. Define product/service management and maintenance plan

I. Development of the product/service image
II. Functionalities of the product/service
III. Development plan
IV. Development of the product/service (web/mobile or other)
V. Revision of the business plan
VI. Management and maintenance of the product/service
VII. Certification plan
VIII. Intellectual property, patents, and support documentation
IX. Main aspects for the creation of a startup - juridical, account, registry, contracts, social capital, obligations, taxes

Periodic grading system:
- Group project: first presentation: 30%; second presentation: 30%; final report: 40%. The presentations, demonstrations and Defence are in group.

LG1 - Know and use the main concepts of descriptive statistics, choose appropriate measures and graphical representations to describe data
LG2 - Apply basic concepts of probability theory, namely compute conditional probabilities, and check for independence of events
LG3 - Work with discrete and continuous random variables.
LG4 - Work and understand the uniform, Bernoulli, binomial, Poisson, Gaussian distribution, as well as Chi-Square and t distribution
LG5 - Perform point parameter estimation and distinguish parameters from estimators
LG6 - Build and interpret confidence intervals for parameter estimates
LG7 - Understand the fundamentals of hypothesis testing
LG8 - Get familiar with some software (such Python or R)

Syllabus contents (SC):
SC1 - Descriptive statistics: Types of variables. Frequency tables and graphical representations. Central tendency measures. Measures of spread and shape.
SC2 - Concepts of probability theory: definitions, axioms, conditional probability, total probability theorem and Bayes's formula
SC3 - Univariate and bivariate random variables: probability and density functions, distribution function, mean, variance, standard deviation, covariance and correlation.
SC4 - Discrete and Continuous distributions: Uniform discrete and continuous, Bernoulli, binomial, binomial negative, Poisson, Gaussian, Exponential Chi-Square and t distribution.
SC 5 - Sampling: basic concepts. Most used sample distributions
SC6 - Point estimation and confidence intervals
SC7 - Hypothesis testing: types of errors, significance level and p-value

Approval with a mark of not less than 10 in one of the following methods:
- Assessment throughout the semester: 1 mini-test taken during the lessons (15%) + Final written test taken on the date of the 1st period (60%) + autonomous work (5%) + group project (20%),
All assessment components, except for the autonomous work, are mandatory and require a minimum grade of 8 out of 20.
or
- Assessment by Exam (100%).

Notes:
1) A complementary oral assessment may be conducted after any evaluation moment to validate the final grade.
2) For this Course Unit, students must consult the Iscte Academic Code of Conduct, available on the institutional platforms, to ensure compliance with the established ethical and behavioral standards.

At the end of the course, each student should be able to:

LO1. Explain what databases and information systems are, characterising them both in terms of technology and their importance for organisations.

LO2. formally represent information requirements by drawing up conceptual data models.

LO3. design databases using the relational model and the UML language.

LO4. build and manipulate relational databases using SQL.

LO5. know and use database administration tools.

LO6. know the main security threats and vulnerabilities in databases.

LO7. know how to mitigate security problems in databases

LO8. know what NoSQL databases are, their main technologies and fields of application.

PC 1. Introduction to databases (DB) and information systems (IS)

1. Characteristics of a DB system;
2. Database management systems (DBMS).
3. IS, technological and organisational perspective;
4. Types of DBs and ISs.

PC 2. requirements analysis and data modelling with UML.

PC 3. Relational modelling:

1. Basic concepts: tables, keys, normal forms, relational algebra.
2. Logical design: UML-relational conversion.
3. Physical design: data types.

PC 4. SQL language

1. Data definition.
2. Data manipulation.
3. Routines and triggers.

PC 5. Database administration

1. DBMSs and administration tools.
2. Optimising DBs with indexes.

PC 6. DB security

1. Confidentiality: users and permissions; DB encryption; data masking; inference.
2. Integrity: restrictions; transactions and concurrency; routines and triggers (revisited).
3. Availability: backup and recovery; replication and balancing.
4. SQL injection.
5. Auditing.

PC 7. NoSQL.

Assessment throughout the semester consisting of 4 individual tests:
- UML and relational model: 25%.
- SQL: 25%
- Security: 25%
- DB and NoSQL administration: 25%.
The duration of each test is 1h15m and the final average of the 4 tests must be equal to or greater than 10 values.

Assessment by exam:
The student can opt for this assessment method in any of the exam seasons. The exam lasts 3 hours and the student must obtain a grade of 10 values or more to pass.

At the end of this CU the student should be able to:
LO1: Understand the main basic principles of modern cryptography
LO2: Understand how the main cryptographic cipher mechanisms work
LO3: Understand how some of the main cryptographic protocols work
LO4: Understand the future development of cryptography
LO5: Use cryptographic mechanisms to protect computers, networks and data.

CP1. Introduction to cryptosystems and cryptanalysis
CP2. Continuous ciphers
CP3. Block ciphers
CP4. Message summarisation and integrity functions
CP5. Public key cryptography
CP6. Digital signatures
CP7. Identification protocols, authenticated key exchange and null knowledge protocols
CP8. Lattice-based cryptography and completely homomorphic cryptography
CP9. Cryptographic tools and libraries

Assessment throughout the semester:
- Carrying out a set of group projects and activities (50%) throughout the semester.
- Completion of two individual tests (50%) [minimum mark of 6 for each test].
Attendance at a minimum number of classes is not compulsory in 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.

At the end of the learning unit, the student must be able to: LG.1. Understand entrepreneurship; LG.2. Create new innovative ideas, using ideation techniques and design thinking; LG.3. Create value propositions, business models, and business plans; LG.5. Develop, test and demonstrate technology-based products, processes and services; LG.6. Analyse business scalability; LG.7. Prepare internationalization and commercialization plans; LG.8. Search and analyse funding sources

I. Introduction to Entrepreneurship;
II. Generation and discussion of business ideas;
III. Value Proposition Design;
IV. Business Ideas Communication;
V. Business Models Creation;
VI. Business Plans Generation;
VII. Minimum viable product (products, processes and services) test and evaluation;
VIII. Scalability analysis;
IX. Internationalization and commercialization;
X. Funding sources

Periodic grading system: - Group project: first presentation: 30%; second presentation: 30%; final report: 40%.

At the end of the course, students should be able to:
LO1: Apply co-creation methodologies to develop innovative projects
LO2: Create empathy with the user and the organisation (define needs, obstacles, objectives, opportunities, current and desired tasks), define the problem and the issues addressed by the project
LO3: Carry out a systematic literature review and an analysis of the competitive landscape, related to the problem identified and the issues raised
LO4: Identify the digital (including data collection), computational and other resources needed to address the problem
LO5: Apply consolidated knowledge of project planning, agile management and project development to solve the problem
LO6: Participate in collaborative and co-creation dynamics and make written and oral presentations in the context of individual or group work

C1. Information security project planning and management methodologies
C2. Presentation of case studies and project themes for digital technologies in information security (product, service or process)
C3. Selection of the project theme and how it fits into the organization
C4. Problem space: creating empathy with the user and their organization, defining the problem and its related issues, considering business requirements, customer and user needs and technological challenges
C5. Application of a systematic literature review methodology and its critical analysis.
C6. Identification of the digital (including data collection), computational and other resources needed to develop the project.
C7. Carrying out what is proposed in the case studies / projects presented, appropriate to the work to be developed by the artificial intelligence students. Preparation of reports and final documentation. Communicating the results.

UC with assessment throughout the semester, not including assessment by final exam, given the adoption of the project-based teaching method applied to real situations. Presentations, demonstrations and discussions can be carried out in groups or individually, depending on the type of project chosen.
Components and weights of the course assessment:
D1. Project Definition and Planning [compulsory component, weight 20%]
D2. Intermediate Project Deliverables [compulsory component, weight 30%]
D3. Final Project Report [compulsory component, weight 30%]
D4. Final Presentation and Discussion [compulsory component, weight 20%]
Failure to fulfil any of these components will result in the UC not being completed.
The final mark (NF) is indicated by the following formula: NF = 0.2*D1+0.3*D2+0.3*D3+0.2*D4
A minimum attendance of no less than 5/6 of the lessons (10 lessons) is required.

LO1 Integrate and apply knowledge, skills and competences acquired during the degree programme to real technology-based projects
LO2 Apply user-centred co-creation methodologies in the development and prototyping of innovative products or services
OA3 Apply agile project management techniques to manage iterative prototyping cycles, ensuring the timely delivery of technological solutions
LO4 Know how to iteratively develop a functional prototype that responds to a problem specified in the Applied Project I course unit
LO5 Critically evaluate the effectiveness and usability of the prototypes developed through user testing
LO6 Produce design documentation for the innovative solution, including architecture, hardware and software configuration, installation, operation and use manuals
LO7 Make written and oral presentations and prepare a submission to a peer-reviewed conference, demonstrating creativity, innovation and self-learning

C1 Solution space: Problem-centred co-creation methodologies applied to the ideation of the best technological solution for the project
C2 Agile management of the solution phase and project delivery
C3 Tools and techniques for iterative prototyping of the solution
C4 User studies and metrics for evaluating usability and task satisfaction
C5 Data analysis of evaluation results and solution iteration
C6 Solution documentation: requirements backlog and user stories, architecture design and specifications, hardware and software configuration, installation, operation and use manuals
C7 Oral, written and audiovisual communication of the results and submission to a conference with peer review. Elevator pitch to relevant stakeholders
C8. Workshop demonstration with relevant players in the field of software and applications

UC with assessment throughout the semester, not including assessment by final exam, given the adoption of the project-based teaching method applied to real situations. Presentations, demonstrations and discussions can be carried out in groups or individually, depending on the type of project chosen.
Components and weights of the course assessment:
D1. Intermediate Project Deliverables [compulsory component, 50% weight] (the number of deliverables is variable, depending on the type of project and the planning carried out in conjunction with the organisation promoting it)
D2. Final Project Report [compulsory component, 30% weight]
D3. Presentation, Demonstration and Final Discussion [compulsory component, weight 20%]
Failure to fulfil any of these components will result in the UC not being completed.
The final mark (NF) is indicated by the following formula: NF = 0.5*D1+0.3*D2+0.2*D3
A minimum attendance of no less than 5/6 of the lessons (10 lessons) is required.

On completion of this course, students will be able to:
LO1. Know and understand software and application security problems
LO2. Know and understand the main security risks and challenges for web and mobile applications
LO3. Know and apply methodologies to the principles of secure software design and development
LO4. Know techniques for exploiting software and applications
LO5. Design mitigation measures for software and applications to avoid security vulnerabilities

CP1. Security problems in applications and software: memory exploitation, concurrency conditions, output generation, side channels, among others.
CP2. Detecting software vulnerabilities and mitigating their exploitation
CP3. Secure software development to mitigate vulnerabilities
CP4. Software Development, Security and Operation (DevSecOps)
CP5. Main vulnerabilities exploited in web and mobile applications, web services and APIs
CP6. Cybersecurity and data protection controls that should be implemented in web, mobile, web services and API applications
CP7. Exploitation of vulnerabilities in web, mobile and web services applications

Assessment throughout the semester:
- Carrying out a group project (60%) throughout the semester
- Individual test (40%) [minimum mark of 9.5]
Attendance at a minimum number of classes is not compulsory for assessment throughout the semester.
Assessment by exam:
For students who opt for this process or for those who fail the assessment process throughout the semester, with 3 seasons under the terms of the RGACC.

On completion of this course, students should:
LO1. Identify the main sources, systems and mechanisms for acquiring security data and events
LO2. Identify and apply the main techniques, methods and tools required for incident response
LO3. Identify suspicious behaviour and events and discern malicious activity
LO4. Apply methods to contain, eradicate and respond to cybersecurity threats
LO5. Define and implement disaster recovery plans
LO6. Apply business continuity management methods

CP1. Requirements analysis and support for security investigations
CP2. CERT, CSIRT and SOC: objectives, functioning and operation
CP3. Logging and security monitoring activities: sources, systems, data acquisition and analysis
CP4. Resource protection techniques
CP5. Incident management and prevention
CP6. Vulnerability and security patch management
CP7. Incident response strategies
CP8. Disaster recovery plans and processes
CP9. Business continuity planning

Assessment throughout the semester:
- Completion of a group project (70%) throughout the semester
- Attendance and participation in seminar sessions (30%);
Attendance at seminar sessions is compulsory and students must attend all the sessions that have been organized.
This course does not include the possibility of assessment by examination. However, students who have not passed the assessment during the semester will have the opportunity to submit their project on a date during the 2nd term.

On completion of this course, students will be able to:
LO1. Understand the subject of digital forensic analysis, its historical context and legal framework
LO2. Discuss the effects of using IT systems, including the traces left behind as a side-effect of normal everyday activities
LO3. Understand the methodologies, processes and fundamentals of digital forensic analysis: obtaining evidence, investigating and reporting, in the verbal and written domain.
LO4. Know the main tools (hardware and software) and techniques for carrying out digital forensic investigations

CP1. The effects of using digital systems and the traces of activities using them
CP2. Overview of the digital investigation process, obtaining digital evidence and the legal framework
CP3. The process of obtaining and safeguarding digital evidence in windows systems
CP4. Digital investigation process
- data acquisition from physical storage devices
- good practices and limitations in the acquisition of digital evidence
- analysing forensic images and recovering files
- good practices in analysing documents
- safeguarding information in memory
- good practices for safeguarding information in open sources
CP5. Present and explore software tools for carrying out forensic investigations
CP6. Drawing up forensic analysis reports and presenting conclusions.

Assessment throughout the semester:
- Carrying out a group project (40%) throughout the semester
- Individual test (40%) [minimum mark of 9.5]
- Completion of a set of practical laboratories (20%)
Attendance at a minimum number of classes is not compulsory for assessment throughout the semester.
Assessment by exam:
For students who opt for this process or for those who fail the assessment process throughout the semester, with 3 periods under the terms of the RGACC.

On completion of this course, students will be able to:
LO1. Understand and identify the main security risks and threats to which systems and networks are exposed.
LO2. Know the main security audit methodologies and procedures
LO3. Identify and get to know some of the main security auditing tools
LO4. Know and correctly apply the life cycle for carrying out security audits
LO5. Apply ethical principles when carrying out security audits

CP1. Introduction to computer security audits and assessments
CP2. Main standards and procedures for security certification and auditing
CP3. Computer security audit and assessment methodologies
CP4. Tools for auditing the security of systems, communication and information networks
CP5. Definition, implementation and management of system, communication network and information security audit projects
CP6. Carrying out security audits of systems, communication and information networks: gathering information, conducting the audit, validating and confirming the results, identifying and confirming vulnerabilities or non-conformities.
CP7. Drawing up reports with the results of computer security audits and assessments: audit and assessment process, activities, evidence and reports (remediation/mitigation) of vulnerabilities
CP8. Principles of ethics and deontology in carrying out computer security audits.

Assessment throughout the semester:
- Carrying out a group project (60%) throughout the semester
- Individual test (40%) [minimum mark of 9.5]
Attendance at a minimum number of classes is not compulsory for assessment throughout the semester.
Assessment by exam:
For students who opt for this process or for those who fail the assessment process throughout the semester, with 3 periods under the terms of the RGACC.

After completing this UC, the student will be able to:

LO1. Identify the main themes and debates relating to the impact of digital technologies on contemporary societies;
LO2. Describe, explain and analyze these themes and debates in a reasoned manner;
LO3. Identify the implications of digital technological change in economic, social, cultural, environmental and scientific terms;
LO4. Predict some of the consequences and impacts on the social fabric resulting from the implementation of a digital technological solution;
LO5. Explore the boundaries between technological knowledge and knowledge of the social sciences;
LO6. Develop forms of interdisciplinary learning and critical thinking, debating with interlocutors from different scientific and social areas.

S1. The digital transformation as a new civilizational paradigm.
S2. The impact of digital technologies on the economy.
S3. The impacts of digital technologies on work.
S4. The impact of digital technologies on inequalities.
S5. The impacts of digital technologies on democracy.
S6. The impacts of digital technologies on art.
S7. The impacts of digital technologies on individual rights.
S8. The impacts of digital technologies on human relations.
S9. The impacts of digital technologies on the future of humanity.
S10. Responsible Artificial Intelligence.
S11. The impact of quantum computing on future technologies.
S12. The impact of digital technologies on geopolitics.

The assessment process includes the following elements:

A) Ongoing assessment throughout the semester
A1. Group debates on issues and problems related to each of the program contents. Each group will participate in three debates throughout the semester. The performance evaluation of each group per debate will account for 15% of each student's final grade within the group, resulting in a total of 3 x 15% = 45% of each student's final grade.
A2. Participation assessment accounting for 5% of each student's final grade.
A3. Final test covering part of the content from the group debates and part from the lectures given by the instructor, representing 50% of each student's final grade.
A minimum score of 9.5 out of 20 is required in each assessment and attendance at a minimum of 3/4 of the classes is mandatory.

B) Final exam assessment Individual written exam, representing 100% of the final grade.