João Pedro Duarte Monge

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.
PC8: Graphical Interface.

The course follows a project-based continuous assessment model throughout the semester due to its highly practical nature, and does not include a final exam.

The student is evaluated according to the following parameters:
A1 (30% of the final grade): Learning Tasks validated by teachers, with a minimum grade of 8 points on the average of the tasks. There are 10 learning tasks and the 8 best grades count.

A2 (70% of the final grade): Mandatory Group Project (maximum 3 members) with theoretical-practical discussion (Delivery: 30%, Practical-oral: 40% with a minimum grade of 8). Component A2 has a minimum score of 9.5 points.

Students who do not achieve the minimum grade will have the opportunity to complete a 100% Practical Project with an oral discussion.

Minimum attendance of no less than 2/3 of classes is required.

João Pedro Pavia

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.

José Barros

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:
* 8 assignments/mini-tests conducted during classes. The best 6 are counted, each with a weight of 5% (total of 30%).
* autonomous work, with a weight of 5%.
* applied mathematics project, with a weight of 5%.
* 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.

Minimum attendance of no less than 2/3 of classes is required.

Maria da Conceição Mendes Canilho Teixeira Pereira

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.

João Pedro Duarte Monge

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

José Barros

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) by separating variables
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 and constrained extrema(otimization)
LG13 Articulate the various approaches to content, graphical, numerical and algebraic

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 Riemann definite integral. Fundamental theorem of calculus and antiderivatives
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 classification >=10 points (1-20 scale) in one of the following modalities:
-Continuous assessment: Test 1 (10%) + Test 2 (20%) + practical work in Python (10%) + autonomous work (10%) + Final Test (40%). The average of the 2 tests and the classification on the final test must be >=7 points (1-20 scale). In case of big differences in the classifications on tests and final test, an oral assessment might be necessary.
-Assessment by Exam (100%), in any of the exam periods

João Pedro Pavia

Diogo Roque Mendes

On completion of this course, students will be able to:
LO1. Know the basic operating principles of a computer network
LO2. Know and understand the OSI and TCP/IP reference models
LO3. Know how the main protocols used in everyday life work, particularly HTTP
LO4. Know and understand how protocols work at transport level.
LO5. Know how to interconnect devices in a wired network.
LO6. Be able to design, configure and manage a computer network

CP1. Introduction to computer networks and presentation of the OSI and TCP/IP reference models
CP2. Introduction to the physical and data link layer. Installation and configuration of a switch
CP3. Introduction to the network layer: IPv4 and IPv6 addressing; IPv4 protocol and creating subnets.
CP4. Packet forwarding; Operation and configuration of a router.
CP5. Exploring TCP/UDP transport protocols. Congestion control.
CP6. Exploring the application layer: DNS, E-mail and File Transfer.
CP7. Configuring firewalls
CP8. Computer network management

It can be accomplished in one of the following ways:

1. Periodic assessment:

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
-3 laboratories to be carried out in groups (15%);
-1 practical group assignment and its presentation (25%).

Note: Both tests and laboratories have a minimum mark of 8 values, and it should be noted that the practical component is mandatory for the purposes of approval in the periodic assessment. The minimum mark 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.

José Miguel Dias

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.

Margarida Santos

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.

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.

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.

LO1. Know the structure, language and ethical and normative (APA) procedures for writing academic texts.
LO2. Learn how to use generative models to write academic texts.
LO3. Discuss procedures for the analysis, relevance and reliability of data generated by AI.
LO4. Recognize the ethical implications of using generative AI in an academic context. The learning objectives will be achieved through practical and reflective activities such as:
- Group discussions;
- Analysis of texts;
- Oral defense;
- Practical exercises.

CP1. Introduction: academic writing and generative models:
- Understanding how Generative Artificial Intelligence works: the path towards using generative AI in the academic environment.
CP2. Procedures for planning and constructing argumentative texts with the help of AI:
- Identifying the possibilities and hallucinations in the answers produced by Generative AI.
CP3. Critical analysis of texts produced: identifying and referencing data sources and analyzing their relevance to the objectives of academic work:
- Exploring the possibilities of data validation and the potential use of Generative AI tools in the production of academic papers.
CP4. Opportunities and risks of using AI: good practice guide for accessing, sharing and using Generative AI in an academic context:
- Understand the dynamics in responsible and ethically committed use when carrying out academic work with Generative AI tools.

The assessment of the course aims to gauge the development of students' skills in the informed use of generative models as an aid to the production of academic work. Assessment throughout the semester includes the following activities:
1.Individual activities (50%)
1.1 Participation in activities throughout the semester (10%).
Description: this component aims to assess each student's specific contribution to the activities carried out.
Assessment: Interventions in the classroom; relevance of the student's specific contributions to the debates.
1.2 Simulations of prompts 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 teacher in class.
Assessment: (submit on moodle), communication skills and teamwork based on the quality of the prompt simulations carried out.
1.3 Oral Defense - group presentation - 5 minutes; debate - 5 minutes (20%).
Description: Each student must present their contributions to the work carried out to the class.
Evaluation: after the student's presentation, there will be a question and answer session.2. group activities (50%)
[students are organized in groups of up to 5 elements, constituted randomly]
2.1 Group presentations, revisions, editing and validation of content produced by AI (20%):
Description: Formation of working groups to review and edit the texts, using the generative models.
Evaluation: (submit to moodle), collection of relevant information, clarity and the innovative nature of the use of properly structured promts.
2.2 Development of strategies for reviewing, editing and validating content produced by AI (10%).
Description: At the end of each stage of the activity, students will have to promote critical evaluations by reflecting on the ethical challenges of integrating AI into an academic environment.
Evaluation: (submit on moodle), work will be corrected and evaluated based on accuracy and compliance with the quality of revisions, edits and the participation of students in the feedback provided to colleagues.
2.3 Final Project Presentation Simulations (20%):
Description: the groups choose a topic and create a fictitious project following the structure of a technical report or scientific text, making a presentation of their project in class (5 minutes) and debating the topic (5 minutes).
Evaluation: (submit on moodle): organization, content, correct use of the structure and procedures of academic work.
General considerations: feedback will be given during the semester. 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.

José Farinha

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.

João Filipe Gaspar

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%.

Paulo Henrique Contente Rocha

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 elements are compulsory and have a minimum mark of 8.
A minimum attendance of no less than 2/3 of classes is required
or
- Assessment by Exam (100%).

João Pedro Pavia

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.

Carlos Serrão

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.

Manuel João da Silva Oliveira

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.

Thiago Bessa Pontes

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%).

João Pedro Pavia

At the end of this course, the student should be able to
LO1. To introduce and to give to the students the main systems distributed through the Internet
LO2. Provide students with knowledge about a set of distributed architectures and services as well as their implementation: web applications and services, messaging services, mobile applications, IoT, Cloud and Distributed Ledger Technologies
LO3. Understand the main security threats and challenges of the same and possible mitigations.

SC1. Introduction to Distributed Systems: fundamentals and main paradigms
SC2. Distributed Computing Models and Platforms
SC3. Fundamentals of Fault-tolerant Systems: Main Paradigms, Models and Platforms of Trusted Systems
SC4. Real-Time Distributed Systems: Main Models and Platforms
SC5. Main Threats, Vulnerabilities and Security Attacks on Distributed Systems
SC6. Security Models and Measures in Distributed Systems

Periodic Assessment:
- 2 tests (50%)
- 3 laboratory activities (15%)
- 1 practical group project (35%)

The minimum mark for each test is 8 values. Such fact, implies that students must have a positive mark in the group work as well as in the laboratory activities (i.e. higher than 11 values).

Assessment by Exam:

-Students who fail the periodic assessment may try to take the subject through an exam.

Regardless of the form of assessment the student takes, the minimum mark for approval is 10 values.

Inês Raquel Vaz de Oliveira

João Paulo Martins Ribeiro

At the end of this course, the student should be able to
LO1. Understand which ethical posture to adopt as a cybersecurity professional;
LO2. Understand the ethnical and privacy implications of cybersecurity;
LO3. Understand the main national and international legislative references in the area of cyber-security;
LO4. Identify the legal and privacy requirements in cybersecurity projects.

SC1. Ethics and technological development:
- Specificity of ethical issues in Information and Communication Technology.
- Responsibility in engineering.
- Applied ethics and regulatory gaps.
- Ethics and Cyber-security.
SC2. Main Cybersecurity Legal Frameworks:
- The national and international cybersecurity strategy.
- Privacy and personal data protection: The RGPD, Law 58/2019 and Law 59/2019.
- The protection of privacy in the electronic communications sector: The e-privacy directive 2002/58/EC (amended by 2009/136/EC) and Law No. 41/2004 (amended by Law No. 46/2012).
- Law on Cybercrime (109/2009).Legal regime for security in cyberspace: The NIS Directive 2016/1148 and Law no. 46/2018. International standards and technical specifications: ISO 27001. The Implementing Regulation (EU) 2018/151. Resolution of the Council of Ministers no. 41/2018, of 28 March.

Periodic Assessment:
- Group resolution of case studies (40%), with two submissions during the semester.
- Individual Test (60%)

The group work for the case study has a minimum evaluation of 7/20 points.

Final Exam:
- Written Test (100%)

The students that fail the periodic assessment have two periods of examination (1st and appeal). The mark of the case studies is not considered for students who choose to take the exam. Students who choose to take the periodic assessment must do both components of it.

Rogério Matos Bravo

Upon completion of this course students will be able to:
LO1. Understand the theme of digital forensic analysis, its historical context and legal framework
LO2. Discuss the effects of the use of IT systems, including the traces left as a side effect of normal day-to-day activities
LO3. Understand the methodologies, processes and fundamentals of digital forensic analysis: evidence gathering, investigation and reporting
LO4. Know the main software tools and techniques for conducting digital forensic investigations

SC1. Effects of the use of digital systems and the traces of the activities of their use
SC2. Overview of the digital investigation process, obtaining digital evidence and legal framework
SC3. Process of obtaining digital evidence in multiple systems
SC4. Digital investigation process
- Acquisition of data from physical storage devices
- Limitations in acquiring digital evidence
- Study of file systems with main focus on Microsoft Windows & Linux systems
- File system analysis and file recovery
- File structure analysis and document analysis
- In-memory information analysis
- E-mail analysis
- Internet artefacts analysis
SC5. Present and explore software tools for conducting forensic investigations
SC6. Writing forensic analysis reports and presenting evidence.

Periodic Assessment:
- Individual test (40%)
- Laboratories cases (20%)
- Development of a Group Project (40%)

Students who fail the periodic assessment may try to take the subject in an exam in the 2nd season.

Arlindo Jorge Ribeiro

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.

Nuno Alexandre Ferreira

Upon completion of this course students will be able to:
LO1. Know and to understand the problems of software and application security
LO2. To know and to understand the main risks and challenges of Web and Mobile application security
LO3. Know and apply methodologies and principles for secure software design and development
LO4. Know techniques to perform software and application exploitation
LO5. Design mitigation measures in software and applications to avoid security vulnerabilities

SC1. Security problems in applications and software: memory exploitation, concurrence conditions, output generation, side channels, among others.
SC2. Detection of software vulnerabilities and mitigation of their exploitation
SC3. Secure software development for the mitigation of vulnerabilities
SC4. Software Development, Security and Operation (DevSecOps)
SC5. Main vulnerabilities exploited in web applications, mobile, web services and APIs
SC6. Cybersecurity and data protection controls that should be implemented in web applications, mobile, web services and APIs
SC7. Exploitation of vulnerabilities in web applications, mobile and web services

Periodic Assessment:
- Components:
* 40% - Project;
* 60% - Individual written test (without consultation).
- Minimum score for both components: 40%.

Review for final exam:
* 100% - Written test
- Final approval: note >= 10

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

SC1. Requirements Analysis and Support for Security Investigations
SC2. CERT, CSIRT and SOC: objectives, functioning and operation
SC3. Logging and security monitoring activities: sources, systems, data acquisition and analysis
SC4. Resource protection techniques
SC5. Incident management and prevention
SC6. Management of vulnerabilities and security patches
SC7. Incident Recovery Strategies
SC8. Disaster Recovery Plans and Processes
SC9. Business Continuity Planning

Periodic Assessment:
- Individual test (60%)
- Resolution of a group project (40%)

Students who fail the periodic assessment may try to take the subject in an exam in the 2nd season.

José Paulo Garcia de Castro

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.