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.

Mandatory

• Ramos, P. Desenhar Bases de Dados com UML, Conceitos e Exercícios Resolvidos, Editora Sílabo, 2ª Edição, 2007.
• Damas, L.: SQL - Structured Query Language, FCA Editora de Informática, 14ª Edição, 2017.
• Danturthi, R. S.: Database and Application Security: A Practitioner's Guide, Addison-Wesley Professional, ISBN 978-0138

Optional

• Kaufman, M. & Meier, A.: SQL and NoSQL Databases – Modeling, Languages, Security and Architectures for Big Data Management, 2ª ed., Springer, 2023.
• Basta A., Zgola M.: Database Security, Cengage Learning. ISBN 978-1435453906, 2011.
• Sullivan D.: NoSQL for mere mortals, Addison-Wesley Professional, ISBN 978-0134023212, 2015.

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%.

Mandatory

A. Osterwalder, Y. Pigneur / John Wiley & Sons, Value Proposition Design: How to Create Products and Services Customers Want, 2014, ·, ·
A. Osterwalder, Y. Pigneur / John Wiley & Sons, Business Model Generation: A Handbook for Visionaries, Game Changers, and Challengers., 2010, ·, ·
P. Burns / Palgrave Macmillan, Entrepreneurship and Small Business, 2016, ·, ·
S. Mariotti, C. Glackin / Global Edition. Pearson; Dorf. R., Byers, T. Nelson, A. (2014). Technology Ventures: From Idea to Enterprise. McGraw-Hill Education, Entrepreneurship: Starting and Operating A Small Business, 2015, ·, ·

Optional

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.

Mandatory

Russell, S., & Norvig, P. (2021). Artificial Intelligence: A Modern Approach (4th ed.). Pearson.
→ Considerado a "bíblia" da IA, cobre desde fundamentos históricos até algoritmos modernos.

Goodfellow, I., Bengio, Y., & Courville, A. (2016). Deep Learning. MIT Press.
→ Introdução acessível e aprofundada ao deep learning.

Mitchell, T. M. (1997). Machine Learning. McGraw-Hill.
→ Livro clássico sobre fundamentos de aprendizagem de máquina.

Domingos, P. (2015). The Master Algorithm: How the Quest for the Ultimate Learning Machine Will Remake Our World. Basic Books.
→ Introdução mais popular, sem fórmulas, ideal para contexto geral.

Chollet, F. (2021). Deep Learning with Python (2nd ed.). Manning.
→ Didático, foca em exemplos práticos com Keras/TensorFlow.

Optional

Haenlein, M., Kaplan, A., Tan, C. T., Tan, B. C., & Zhang, P. (2019). Artificial Intelligence (AI) and Management Analytics. Journal of the Academy of Marketing Science, 48(3), 411–431.

Jordan, M. I., & Mitchell, T. M. (2015). Machine Learning: Trends, Perspectives, and Prospects. Science, 349(6245), 255–260.

Topol, E. (2019). High-performance Medicine: The Convergence of Human and Artificial Intelligence. Nature Medicine, 25, 44–56.

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 and security settings on network infrastructure devices

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. 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.

Mandatory

-Kurose J., Keith Ross K. (2017). Computer networking: a top-down approach. Pearson. ISBN: 978-0-13-359414-0;
-Tanenbaum A., Wetherall D. (2021). Redes de Computadores. Bookman. ISBN: 9788582605608.

Optional

-Boavida F., Monteiro E. (2021). Engenharia de Redes Informáticas. FCA Editora. ISBN: 9789727226948.

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.

Mandatory

E. Reis, P. Melo, R. Andrade & T. Calapez (2015). Estatística Aplicada (Vol. 1) - 6ª ed, Lisboa: Sílabo. ISBN: 978-989-561-186-7.
Reis, E., P. Melo, R. Andrade & T. Calapez (2016). Estatística Aplicada (Vol. 2), 5ª ed., Lisboa: Sílabo. ISBN: 978-972-618-986-2.
Afonso, A. & Nunes, C. (2019). Probabilidades e Estatística. Aplicações e Soluções em SPSS. Versão revista e aumentada. Universidade de Évora. ISBN: 978-972-778-123-2.
Ferreira, P.M. (2012). Estatística e Probabilidade (Licenciatura em Matemática), Instituto Federal de Educação, Ciência e Tecnologia do Ceará – IFCE III, Universidade Aberta do Brasil – UAB.IV. ISBN: 978-85-63953-99-5.
Farias, A. (2010). Probabilidade e Estatística. (V. único). Fundação CECIERJ. ISBN: 978-85-7648-500-1.

Optional

Haslwanter, T. (2016). An Introduction to Statistics with Python: With Applications in the Life Sciences. Springer. ISBN: 978-3-319-28316-6.

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 8 for each test].
In order to be assessed throughout the semester, students must attend 70% of classes.
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.
Note: Notwithstanding the provisions of the assessment, the teacher reserves the right to request an oral assessment from the student or group to validate the knowledge demonstrated in the assignment or tests.

Mandatory

Stinson D. R., Paterson M. (2018). Cryptography: Theory and Practice. Chapman and Hall/CRC. ISBN: 978-1138197015.
Aumasson J. (2017). Serious Cryptography: A Practical Introduction to Modern Encryption. No Starch Press. ISBN: 978-1593278267.
Tilborg H., Jajodia S. (2011). Encyclopedia of Cryptography and Security. Springer. ISBN: 978-1441959058.
Paar C., Pelzl J., Preneel B. (2014). Understanding Cryptography: A Textbook for Students and Practitioners. Springer. ISBN: 978-3642446498.
Bray S. (2020). Implementing Cryptography Using Python. Wiley. ISBN: 978-1119612209.
Nielson S. J., Monson C. (2019). Practical Cryptography in Python: Learning Correct Cryptography by Example. ISBN: 978-1484248997.

Optional

Material complementar a fornecer pela equipa docente durante as aulas.
Ristic I. (2013). OpenSSL Cookbook: A Guide to the Most Frequently Used OpenSSL Features and Commands. Feisty Duck. ISBN: 9781907117053.
Schneier B. (2017). Applied Cryptography: Protocols, Algorithms and Source Code in C. Wiley. ISBN: 978-1119096726.
Bowne S. (2018). Hands-On Cryptography with Python: Leverage the power of Python to encrypt and decrypt data. Packt Publishing. ISBN: 978-1789534443.
Zúquete A. (2018). Segurança em Redes Informáticas. FCA. ISBN: 978-972-722-857-7.

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. Intrusion Detection and Prevention: Types of systems (IDS, IPS, Network or Host-based). Honeynets and Honeypots.
SC7.Zero Trust Architectures

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 (25% + 25%)
- Two lab experiments in group (20%), with a minimum grade of 8 in each lab
- One practical work in group, including its oral presentation, with a minimum grade of 8 (30%)
2. Exam evaluation:
- Written exam (100%)

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

Mandatory

Stallings, W. (2016). Network Security Essentials: Applications and Standards. Pearson.
Kurose, J., Ross, K. (2021). Computer Networking: A Top-Down Approach. 2021.

Optional

Peterson, L., Davie, B. (2021). Computer Networks: A Systems Approach (The Morgan Kaufmann Series in Networking). Morgan Kaufmann.
Stewart, M., Kinsey, D. (2020). Network Security, Firewalls, and VPNs (ISSA). Jones & Bartlett Learning.
Zuquete, A. (2018). Segurança em Redes Informáticas. FCA.
Ciampa, M. (2017). CompTIA Security+ Guide to Network Security Fundamentals. Cengage Learning.

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.

Mandatory

European Union Agency for Fundamental Rights, The Handbook on European data protection law, 2019, -, http://fra.europa.eu/en/publication/2018/handbook-european-data-protection-law-2018-edition
Poel I., Royakkers L. (2011). Ethics, Technology, and Engineering: An Introduction., Wiley-Blackwell.
Nunes D. (2020). Os Crimes Previstos na Lei do Cibercrime. Gestlegal. ISBN: 9789898951502.

Optional

Sara Baase, A gift of fire : social, legal, and ethical issues for computing technology, 2013, 4th edition
Pedro Dias Venâncio, Lei do Cibercrime : Anotada e Comentada, 2023, Editora D’ideias ISBN: 9789895398614
Adela Cortina, Ética Mínima, 2020, Editora Tecnos
Bynum, Ward T., Rogerson S., Computer Ethics and Professional Responsibility: Introductory Text and Readings. Oxford: Blackwell., 2004
Cordeiro, A.B.N., Direito da Proteção de Dados à luz do RGPD e da Lei n.º 58/2019, Edições Almedina., 2020
Gomes M, Gomes M. (2006). O Código da Privacidade e da Protecção de Dados Pessoais na Lei e na Jurisprudência (nacional e internacional). Edições Centro Atlântico. ISBN: 9789896150228., 2006

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.

Mandatory

·
A. Osterwalder, Y. Pigneur / John Wiley & Sons, Value Proposition Design: How to Create Products and Services Customers Want, 2014, ·, ·
A. Osterwalder, Y. Pigneur / John Wiley & Sons, Business Model Generation: A Handbook for Visionaries, Game Changers, and Challengers, 2010, ·, ·
P. Burns / Palgrave Macmillan, Entrepreneurship and Small Business, 2016, ·, ·
R. Dorf, T. Byers, A. Nelson / McGraw-Hill Education, Technology Ventures: From Idea to Enterprise., 2014, ·, ·
S. Mariotti, C. Glackin / Global Edition. Pearson, Entrepreneurship: Starting and Operating A Small Business, 2015, ·, ·

Optional

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%).

Mandatory

Livros de texto:
Dean J. (2018). Web Programming with HTML5, CSS, and JavaScript. Ed: Jones & Bartlett Learning. ISBN-13: 978-1284091793. ISBN-10: 1284091791
Menezes N. (2019). Introdução à programação com Python: Novatec. ISBN-13: 978-8575227183.
Grinberg M. (2018). Flask Web Development: Developing Web Applications with Python. O'Reilly. ISBN: 978-1491991732
George N. (2019). Build a Website With Django 3: A complete introduction to Django 3. GNW Independent Publishing. ISBN: 978-0994616890.
Ahmad H. (2017). Building RESTful Web Services with PHP 7. Ed: Packt Publishing. ISBN-13: 9781787127746.
Hillar G. (2016). Building RESTful Python Web Services. Packt Publishing. ISBN: 978-1786462251
Haverbeke M. (2018). Eloquent JavaScript: A Modern Introduction to Programming (3rd. ed.). No Starch Press, USA.
Architecture of the World Wide Web, Volume One, W3C Recommendation 15 December 2004, https://www.w3.org/TR/webarch/

Optional

Haverbeke M. (2018). Eloquent JavaScript: A Modern Introduction to Programming (3rd. ed.). No Starch Press, USA.
Architecture of the World Wide Web, Volume One, W3C Recommendation 15 December 2004, https://www.w3.org/TR/webarch/
Artigos:
Fielding, R. T. (2000) REST: Architectural Styles and the Design of Network-based Software Architectures, PhD thesis, University of California, Irvine.

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.

Mandatory

Lewrick, M, Link, P., Leifer, L. (2020). The Design Thinking Toolbox, Wiley, ISBN 9781119629191
Knapp, J., Zeratsky, J., & Kowitz, B. (2016). Sprint: How to Solve Big Problems and Test New Ideas in Just Five Days. Bantam Press.
Osterwalder, A., Pigneur, Y., Papadakos, P., Bernarda, G., Papadakos, T., & Smith, A. (2014). Value proposition design. John Wiley & Sons.
Brown, T (2009), Change by Design: How Design Thinking Transforms Organizations and Inspires Innovation, HarperCollins, 2009, ISBN-13: 978-0062856623
Outra bibliografia dependente dos temas específicos do projeto e das organizações onde os alunos o irão desenvolver.

Optional

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.

Mandatory

ISO/IEC 27037:2012. Information technology - Security techniques - Guidelines for identification, collection, acquisition and preservation of digital evidence
Carrier B. (2005). File system forensic analysis. Addison-Wesley Professional. ISBN 0321268172.
Johansen G. (2020). Digital Forensics and Incident Response: Incident response techniques and procedures to respond to modern cyber threats. Packt Publishing Ltd. ISBN: 978-1838649005.
Oettinger W. (2020). Learn Computer Forensics: A beginner's guide to searching, analyzing, and securing digital evidence. Packt Publishing Ltd. ISBN: 978-1838648176.
Casey E. (2009). Handbook of digital forensics and investigation. Academic Press. ISBN: 0123742676.
Sammons J. (2012). The basics of digital forensics: the primer for getting started in digital forensics. Syngress. ISBN: 978-0128016350

Optional

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.

Mandatory

Baloch R. (2014). Ethical Hacking and Penetration Testing Guide. Auerbach Publications. ISBN: 978-1482231618
Hutchens J. (2014). Kali Linux Network Scanning Cookbook. Packt Publishing Ltd.
Kegerreis, M., Schiller, M., & Davis, C. (2020). It Auditing Using Controls to Protect Information Assets 3rd Edition. MC Graw Hill.
Velu V. K. (2017). Mastering Kali Linux for Advanced Penetration Testing.Packt Publishing Ltd. ISBN: 9781787120235
Vladimirov A. (2016). Assessing Information Security - Strategies, Tactics, Logic and Framework. IT Governance Publishing.
Ullman, C. J. (2023). The Active Defender - Immersion in the Offensive Security Mindset . John Wiley & Sons, Inc.

Optional

Conjunto de artigos, páginas web e textos que complementam a informação bibliográfica da unidade curricular, e que serão fornecidos pela equipa docente.
Parasram S. , Samm A., Boodoo D. (2018). Kali Linux 2018: Assuring Security by Penetration Testing. Packt Publishing Ltd. ISBN: 9781789341768
Patel R. S. (2013). Kali Linux social engineering. Packt Publishing Ltd. ISBN: 9781783283279
Sak B, Ram J. R. (2016). Mastering Kali Linux Wireless Pentesting. Packt Publishing Ltd. ISBN: 9781785285561
Shoemaker, D., Kohnke, A., & Sigler, K. (2017). Implementing Cybersecurity A Guide to the National Institute of Standards and Technology Risk Management Framework.

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.

Mandatory

Zalewski M. (2012). The tangled web: A guide to securing modern web applications. No Starch Press. ISBN: 1-59327-388-6.
Stuttard D., Pinto M. (2012). The Web Application Hacker's Handbook: Finding and Exploiting Security Flaws. Wiley. ISBN: 978-1118026472.
Hsu, T. H. C. (2018). Hands-On Security in DevOps: Ensure continuous security, deployment, and delivery with DevSecOps. Packt Publishing Ltd. ISBN : 1788995503.
Richardson T. (2012). Secure Software Design. Jones & Bartlett Learning. ISBN: 978-1449626327
Deogun D., Johnsson B., Sawano D. (2019). Secure By Design. Manning Publications. ISBN: 978-1617294358
Grembi J. (2008). Secure Software Development: A Security Programmer's Guide. Cengage Learning. ISBN: 978-1418065478
Adkins H., Beyer B., Blankinship P., Lewandowski P., Oprea A., & Stubblefield A. (2020). Building Secure and Reliable Systems: Best Practices for Designing, Implementing, and Maintaining Systems. O'Reilly Media. ISBN: 978-1492083122.

Optional

CP1: Review and deepening of project planning and management methodologies, with an emphasis on co-creation and agile management.
CP2: Presentation of case studies and project topics in digital inf. security technologies, focusing on the continuity of PATDSI-I projects.
CP3: Selection and refinement of the project theme, considering the organizational framework and the challenges identified previously.
CP4: Analysis of the problem space: creating empathy with the user and the organization, defining and deepening the problem, taking into account business requirements and technological challenges.
CP5: Continuation of the literature review and critical analysis of the competitive landscape to support the proposed solution.
CP6: Identification and integration of the digital, computational, and other resources necessary for project development.
CP7: Development of the applied project, including implementation and refinement of the solution based on feedback, and communication of 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. 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.

Mandatory

M. Lewrick, P. Link, L. Leifer / Wiley, ISBN 9781119629191, The Design Thinking Toolbox, 2020
Darrell Rigby, Sarah Elk, Steve Berez / Scrum Institute, The Scrum Framework 3rd Edition
https://www.scrum-institute.org/contents/The_Scrum_Framework_by_International_Scrum_Institute.pdf
Ries, E. / Capítulos 3 e 4, Penguin Group, The Lean Startup: How Today's Entrepreneurs Use Continuous Innovation to Create Radically Successful Businesses, 2017
J. Knapp, J. Zeratsky, B. Kowitz / Bantam Press., Sprint: How to Solve Big Problems and Test New Ideas in Just Five Days., 2016
A. Osterwalder, Y. Pigneur, P. Papadakos, G. Bernarda, T. Papadakos, A. Smith / John Wiley & Sons., Value proposition design., 2014
T. Brown , H., Collins, 2009, ISBN-13: 978-0062856623, Change by Design: How Design Thinking Transforms Organizations and Inspires Innovation, 2009
The Basics of User Experience Design by Interaction Design Foundation, https://www.interaction-design.org/

Optional

Doing Agile Right: Transformation Without Chaos Hardcover, 2020
Gwaldis M., How to conduct a successful pilot: Fail fast, safe, and smart, 2019, ·, https://blog.shi.com/melissa-gwaldis/
Jeff Sutherland, J.J. Sutherland, Scrum: The Art of Doing Twice the Work in Half the Time, 2014
Snyder, C. (2003). Paper Prototyping: the fast and easy way to design and refine user interfaces. Morgan Kaufmann Publishers.
Nielsen, J. (1994) Enhancing the explanatory power of usability heuristics. Proc. ACM CHI'94 Conf. (Boston, MA, April 24-28), pp. 152-158.
Rettig M. (1994), Prototyping for Tiny Fingers, Communications of The ACM, 1994
Conjunto de artigos, páginas web e textos que complementam a informação bibliográfica da unidade curricular, e que serão fornecidos pela equipa docente.

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
The syllabus contents of this curricular unit will be transferred to students through the organization of thematic seminairs.

Assessment throughout the semester:
- Completion of one or more group assignments/projects (60%) during the semester;
- Completion of an assessment component (40%) designed to evaluate students’ knowledge.

This course unit does not provide for assessment exclusively through a final exam. However, students who do not complete the assignment(s) and/or the assessment component during the semester may be assessed through an individual assignment/project, weighted at 100%, to be submitted on a date to be defined during the period scheduled for the second assessment period of the course unit.
Note: Whenever there are indications of the use of Generative Artificial Intelligence tools, the instructor may require an oral assessment from the student or group in order to validate the knowledge demonstrated in the submitted work.

Mandatory

Snedaker S. (2013). Business Continuity and Disaster Recovery Planning for IT Professionals. Syngress. ISBN: 978-0124105263
Whitman M., Mattord H. (2013). Principles of Incident Response & Disaster Recovery. Cengage Learning. ISBN: 978-1111138059
Anson S. (2020). Applied Incident Response. Wiley. ISBN: 978-1119560265
Chuvakin A., Schmidt K., Phillips C. (2012). Logging and Log Management: The Authoritative Guide to Understanding the Concepts Surrounding Logging and Log Management. Syngress. ISBN: 978-1597496353

Optional

Cichonski P., Millar T., Grance T., Scarfone K. (2012). Computer Security Incident Handling Guide (SP 800-61 Rev. 2). National Institute of Standards and Technology.
Phillips B., Landahl M. (2020). Business Continuity Planning: Increasing Workplace Resilience to Disasters. Butterworth-Heinemann. ISBN: 978-0128138441
Murdoch D. (2019). Blue Team Handbook: SOC, SIEM, and Threat Hunting (V1.02): A Condensed Guide for the Security Operations Team and Threat Hunter. Independently published. ISBN: 978-1091493896

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.

Mandatory

Chalmers, D. (2022). Adventures in technophilosophy In Reality+ - Virtual Worlds and the problems of Philosophy (pp. xi-xviii). W. W. Norton & Company.
Chin, J., Lin, L. (2022). Dystopia on the Doorstep In Deep Utopia – Surveillence State – Inside China’s quest to launch a new era of social control (pp. 5–11). St. Martin’s Press.
Dignum, V. (2019). The ART of AI: Accountability, Responsibility, Transparency In Responsible Artificial Intelligence - How to Develop and Use AI in a Responsible Way (pp. 52–62). Springer.
Howard, P. N. (2020). The Science and Technology of Lie Machines In Lie Machines - How to Save Democracy from Troll Armies, Deceitful Robots, Junk News Operations, and Political Operatives (pp. 1-4; 6-7; 10-18). Yale University Press.
Kearns, M., Roth, A. (2020). Introduction to the Science of Ethical Algorithm Design In The Ethical Algorithm - The Science of Socially Aware Algorithm Design (pp. 1-4; 6-8; 18-21). Oxford University Press.

Optional

(Principal - continuação)
Kissinger, H. A., Schmidt, E., Huttenlocher, D (2021). Security and World Order In The Age of AI - And Our Human Future (pp. 157–167, 173-177). John Murray Publishers.
Parijs, P. V., Vanderborght, Y. (2017). Ethically Justifiable? Free Riding Versus Fair Shares In Basic Income - A Radical Proposal for a Free Society and a Sane Economy (pp. 99–103). Harvard University Press.
Pentland, A. (2014). From Ideas to Actions In Social Physics – How good ideas spread – The lessons from a new science (pp. 4–10). The Penguin Press.
Zuboff, S. (2021). O que é capitalismo de vigilância? In A Era do Capitalismo de Vigilância - A luta por um futuro humano na nova fronteira de poder (pp. 21–25). Intrínseca.

***
(Complementar)
Acemoglu, D.; Johnson, S. (2023). What Is Progress? In Power and progress: our thousand-year struggle over technology and prosperity (pp. 1 - 7). PublicAffairs.
Bostrom, N. (2024). The purpose problem revisited In Deep Utopia – Life and meaning in a solved world (pp. 121–124). Ideapress Publishing.
Castro, P. (2023). O Humanismo Digital do século XXI e a nova Filosofia da Inteligência Artificial In 88 Vozes sobre Inteligência Artificial - O que fica para o homem e o que fica para a máquina? (pp. 563 – 572). Oficina do Livro/ISCTE Executive Education.
Gunkel, D. J. (2012). Introduction to the Machine Question In The Machine Question - Critical Perspectives on AI, Robots, and Ethics (pp. 1-5). The MIT Press.
Innerarity, D. (2023). O sonho da máquina criativa. In Inteligência Artificial e Cultura – Do medo à descoberta (pp. 15 – 26). Colecção Ciência Aberta, Gradiva.
Jonas, H. (1985). Preface to the English version of the Imperative of Responsibility In The Imperative of Responsibility: In Search of an Ethics for the Technological Age. (pp. ix - xii). University of Chicago Press.
Nakazawa, H. (2019). Manifesto of Artificial Intelligence Art and Aesthetics In Artificial Intelligence Art and Aesthetics Exhibition - Archive Collection (p. 25). Artificial Intelligence Art and Aesthetics Research Group (AIAARG).
Patel, N. J. (2022, february 4). Reality or Fiction - Sexual Harassment in VR, The Proteus Effect and the phenomenology of Darth Vader — and other stories. Kabuni. https://medium.com/kabuni/fiction-vs-non-fiction-98aa0098f3b0
Pause Giant AI Experiments: An Open Letter. (22 March, 2023). Future of Life Institute. Obtido 26 de agosto de 2024, de https://futureoflife.org/open-letter/pause-giant-ai-experiments/

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.

Mandatory

Ribeiro, A. & Rosa, A. (2024). Descobrindo o potencial do CHATGPT em sala de aula: guia para professores e alunos. Atlantic Books.
Cotton, D. R., Cotton, P. A., & Shipway, J. R. (2024). Chatting and cheating: Ensuring academic integrity in the era of ChatGPT. Innovations in education and teaching international, 61(2), 228-239.
d’Alte, P., & d’Alte, L. (2023). Para uma avaliação do ChatGPT como ferramenta auxiliar de escrita de textos acadêmicos. Revista Bibliomar, São Luís, 22(1), 122-138. DOI: 10.18764/2526-6160v22n1.2023.6.
Kasneci, E., Seßler, K., Küchemann, S., Bannert, M., Dementieva, D., Fischer, F., ... & Kasneci, G. (2023). ChatGPT for good? On opportunities and challenges of large language models for education. Learning and individual differences, 103, 102274.

Optional

Cowen, T., & Tabarrok, A. T. (2023). How to learn and teach economics with large language models, including GPT. GMU Working Paper in Economics No. 23-18. DOI: 10.2139/ssrn.4391863
Lund, B. D., Wang, T., Mannuru, N. R., Nie, B., Shimray, S., & Wang, Z. (2023). ChatGPT and a new academic reality: Artificial Intelligence‐written research papers and the ethics of the large language models in scholarly publishing.

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.

Mandatory

Stewart, J. (2022). Cálculo, Vol I, Cengage Learning, (9a Ed.)
Cabral I., Perdigão, C. e Saiago, C. (2018). Álgebra Linear: Teoria, Exercícios Resolvidos e Exercícios Propostos com Soluções, Escolar Editora
Magalhães, L.T. (2004). Álgebra Linear como Introdução a Matemática Aplicada, 8ª edição, Texto Editora

Optional

Campos Ferreira, J. (2018). Introdução à Análise Matemática, Fundação Calouste Gulbenkian
Goldstein, L. (2011). Matemática Aplicada a Economia. Administração e Contabilidade, (12a edição) Editora Bookman
Strang, G., (2007) Computational Science and Engineering, Wellesley-Cambridge Press.

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.

Mandatory

Morris Mano, M., & Ciletti, M. D., ""Computer System Architecture"", Pearson, 6ª edição (2017). Stallings, W., ""Computer Organization and Architecture: Designing for Performance"", Pearson, 10ª edição (2015). Guilherme Arroz, José Monteiro, Arlindo Oliveira, Arquitectura de Computadores: dos Sistemas Digitais aos Microprocessadores – 6.ª Edição, IST Press, 2024, ISBN: 978-972-8469-54-2."

Optional

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:
- Completion of a set of group projects and activities (50%) throughout the semester
- Completion of a set of individual mini-tests throughout the semester (50%) [minimum grade of 8 for each test]
For assessment throughout the semester, minimum attendance of 70% of classes is required.
Exam assessment:
For students who choose this process or who fail the assessment process throughout the semester, with 3 periods in accordance with the RGACC.

Mandatory

Whitman, M., Mattord, H. (2021). Principles of Information Security. Course Technology.
Whitman, M., & Mattord, H. (2016). Management of information security. Nelson Education.
Andress, J. (2014). The Basics of Information Security: Understanding the Fundamentals of InfoSec in Theory and Practice. Syngress.
Kim, D., Solomon, M. (2016). Fundamentals of Information Systems Security. Jones & Bartlett Learning.

Optional

Conjunto de artigos, páginas web e textos que complementam a informação bibliográfica da unidade curricular, e que serão fornecidos pela equipa docente.

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.

Mandatory

Brown, T. (2008). Design Thinking. Harvard Business Review, 86(6), 84–92.
Lewrick, M., Link, P., & Leifer, L. (2018). The design thinking playbook: Mindful digital transformation of teams, products, services, businesses and ecosystems. John Wiley & Sons.
Lockwood, T. (2010). Design Thinking: Integrating Innovation, Customer Experience and Brand Value. Allworth Press.
Stewart S.C (2011) “Interpreting Design Thinking”. In: https://www.sciencedirect.com/journal/design-studies/vol/32/issue/6

Optional

Brown, T., & Katz, B. (2011). Change by design. Journal of product innovation management, 28(3), 381-383.
Brown, T., Katz, B. M. Change by Design: How Design Thinking Transforms Organizations and Inspires Innovation. HarperBusiness, 2009.
Liedtka, J. (2018). Why Design Thinking Works. Harvard Business Review, 96(5), 72–79.
Gharajedaghi, J. (2011). Systems thinking: Managing chaos and complexity. A platform for designing business architecture. Google Book in: https://books.google.com/books?hl=en&lr=&id=b0g9AUVo2uUC&oi=fnd&pg=PP1&dq=design+thinking&ots=CEZe0uczco&sig=RrEdhJZuk3Tw8nyULGdi3I4MHlQ

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:
If a student misses an exam due to absence they may take a make-up exam at the end of the semester.

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

Mandatory

Portela, Filipe, Tiago Pereira, Introdução à Algoritmia e Programção com Python, FCA, 2023, ISBN: 9789727229314

Sónia Rolland Sobral, Introdução à Programação Usando Python, 2a ed., Edições Sílabo, 2024, ISBN: 9789895613878

Nilo Ney Coutinho Menezes, Introdução à Programação com Python: Algoritmos e Lógica de Programação Para Iniciantes. Novatec Editora, 2019. ISBN: 978-8575227183

John Zelle, Python Programming: An Introduction to Computer Science, Franklin, Beedle & Associates Inc, 2016, ISBN-13 : ‎978-1590282755

Ernesto Costa, Programação em Python: Fundamentos e Resolução de Problemas, 2015, ISBN 978-972-722-816-4,

Optional

João P. Martins, Programação em Python: Introdução à programação com múltiplos paradigmas, IST Press, 2015, ISBN: 9789898481474

David Beazley, Brian Jones, Python Cookbook: Recipes for Mastering Python 3, O'Reilly Media, 2013, ISBN-13 ? : ? 978-1449340377

Kenneth Reitz, Tanya Schlusser, The Hitchhiker's Guide to Python: Best Practices for Development, 1st Edition, 2016, ISBN-13: 978-1491933176, https://docs.python-guide.org/

Eric Matthes, Python Crash Course, 2Nd Edition: A Hands-On, Project-Based Introduction To Programming, No Starch Press,US, 2019, ISBN-13 ‏: ‎978-1593279288

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.

Mandatory

Prieto, G. (2014). Falar em Público - Arte e Técnica da Oratória. Escolar Editora.

Optional

Anderson, C. (2016). TED Talks: o guia oficial do TED para falar em público. Editora Intrinseca.
Luiz, P. (2019). Manual de Exercícios Criativos e Teatrais. Showtime. Rodrigues, A. (2022). A Natureza da Atividade Comunicativa. LisbonPress.

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

Mandatory

Cormen, T. H., Leiserson, C. E., Rivest, R. L., Stein, C. (2022). Introduction to Algorithms, Fourth Edition. Estados Unidos: MIT Press.
Rocha, A. (2011). Estruturas de Dados e Algoritmos em Java. Portugal: FCA.
Sedgewick, R., Wayne, K. (2014). Algorithms, Part II. Reino Unido: Pearson Education.

Optional

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 requires a final grade of no less than 10 points (out of 20) in one of the following modalities:
- Continuous Assessment:
* 3 tests (T1, T2, T3), with a minimum score of 7.0 points (out of 20)
* final grade: (T1 + T2 + T3) / 3
* T1 and T2 are taken during the semester
* T3 is taken on the date of the 1st exam period
* T1 or T2 may be retaken on the date of the 1st exam period
or
- Final Exam Assessment (100%).

Oral examinations may be conducted if the instructor deems it appropriate.
Grades above 17 points must be defended in an oral exam.

Mandatory

[1] Stewart, J. (2022). Cálculo, Vol I, Cengage Learning, (9ª Ed.)
[2] Campos Ferreira, J. (2024). Introdução à Análise Matemática, Fundação Calouste Gulbenkian (12ª Ed.)
[3] Lipsman, R.L., Rosenberg, J.M. (2018) Multivariable Calculus with MATLAB, Springer
[4] Hanselman, D., Littlefield, B. and MathWorks Inc. (1997) The Student Edition of MATLAB, 5th Version, Prentice-Hall

Optional

PC1: Introduction to Operating Systems.
PC2: Concurrency and process management.
PC3: Process scheduling and synchronization.
PC4: Interprocess communication.
PC5: Memory management: Models and algorithms.
PC6: Input and output.
PC7: File systems.
PC8: Shell commands and shell programming.
PC9: Virtualization and containerization.

It consists of:

- Two written tests to be taken during the semester with a minimum grade of 8 per test (30% + 30%).

- Practical group work and its oral presentation (40%), with a minimum grade of 8. Group work is mandatory.

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%. If the student obtains exactly 8 in the written component and in order to pass the CU, they must obtain 12 in the practical work, since for the purposes of passing the CU, the student must obtain a grade equal to or higher than 9.5.

Mandatory

- Textos, exercícios e guias de laboratório disponibilizados pela equipa docente.
- Morris Mano, Charles Kime, "Logic and Computer Design Fundamentals", 5th Ed, Prentice Hall, 2015,
ISBN: 978-1292096070
- Guilherme Arroz, José Monteiro, Arlindo Oliveira, "Arquitectura de Computadores: dos Sistemas Digitais
aos Microprocessadores - 2ª Edição", IST Press, 2009
- Andrew Tanenbaum, Todd Austin, "Structured Computer Organization", 6th Ed, Pearson, 2012, ISBN:
978-0132916523
- A. S. Tanenbaum and H. Bos, "Modern Operating Systems (4th Ed)", Pearson Prentice-Hall, 2014, ISBN:
978-0133591620
- W. Stallings, "Operating Systems Internals and Principles", 9th Ed, Pearson, 2017, ISBN: 978-0134670959
- M. Portnoy, "Virtualization Essentials", 2nd Ed, 2016, Sybex, ISBN: 978-1119267720
- S. Mohan Jain, "Linux Containers and Virtualization: A Kernel Perspective", Apress, 2020, ISBN: 978-1484262825

Optional

- José Alves Marques, Paulo Ferreira, Carlos Ribeiro, Luís Veiga, Rodrigo Rodrigues, "Sistemas Operativos", FCA, 2012, ISBN 978-972-722-575-0
- Paulo Trezentos e António Cardoso, "Fundamental do Linux", 3ª Edição, FCA, 2009, ISBN: 978-972-722-514-9
- A. Silberschatz, P. Galvin, G. Gagne, "Operating Systems Concepts Essentials", 2nd Ed, Wiley, 2013,
ISBN: 978-1118804926
- Abraham Silberschatz, "Operating System Concepts", 10th Edition, Wiley, 2018, ISBN: 978-1119456339
- Recursos diversos referidos nas Observações: https://www.acsov.pt/p/recursos.html

C1. Fundamentals of Project Management: concepts, characteristics, operations vs. projects
C2. Project Life Cycles and Methodologies (Waterfall, Agile, Hybrid)
C3. Planning and Control Dimensions: scope, time, cost, resources, risk, quality, communication
C4. PM² Methodology: structure, artefacts, stakeholders
C5. Applied Project: planning, execution, monitoring, closure, and benefits evaluation

Assessment is continuous and based on a combination of group and individual evaluation components.
A minimum attendance of two-thirds of the classes is required.
Assessment Components:
1. Project Management Dossier (50%) – Group Assessment
A structured document covering all phases of the project life cycle, based on the PM² methodology, including:
o Project Initiation
o Planning
o Execution and Control
o Closure
2. Final Project Presentation (20%) – Group Assessment
3. Individual Oral Discussion (20%) – Individual Assessment
4. Individual Written Reflection (10%) – Individual Assessment

Mandatory Requirements:
• Minimum grade of 9.5/20 in all assessment components
• Submission of all group project deliverables
This course unit does not include a final exam.

Mandatory

Lester A. / 7th edition, Elsevier Science & Technology., Project Management Planning and Control, 2017, ·, ·
Tugrul U. Daim, Melinda Pizarro, e outros / Spinger, Planning and Roadmapping Technological Innovations: Cases and Tools (Innovation, Technology, and Knowledge Management), 2014, ·, ·

Optional

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 accounts for 35% of the final grade.

Completion of a group assignment, worth a total of 35% of the final mark (15% for the written work and 20% for the group discussion).

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.

Mandatory

Autor, David H., "Why Are There Still So Many Jobs? The History and Future of Workplace Automation.", 2015, Journal of Economic Perspectives, 29 (3): 3-30.
Benanav, A, Automation and the Future of Work, 2020, London: Verso
Boreham, P; Thompson, P; Parker, R; Hall, R, New Technology at Work, 2008, Londres: Routledge.
Crawford, C, The Atlas of AI. Power, Politics, and the Planetary Costs of Artificial Intelligence, 2021, Yale University Press.
Edgell, S., Gottfried, H., & Granter, E. (Eds.). (2015). The Sage Handbook of the sociology of work and employment.
Grunwald, A. (2018). Technology Assessment in Practice and Theory. London: Routledge.
Huws, U. (2019) Labour in Contemporary Capitalism, London, Palgrave.
OIT (2020), As plataformas digitais e o futuro do trabalho
Agrawal A, Gans J, Goldfarb A (2018), Prediction Machines, Boston, Massachusetts, Harvard Business Review Press.
Autor D (2022), The labour market impacts of technological change, Working Paper 30074, NBER Working Paper Series.

Optional

✔ Autor D (2022), The labour market impacts of technological change, Working Paper 30074, NBER Working Paper Series.
✔ Braun J, Archer M, Reichberg G, Sorondo M (2021), Robotics, AI and Humanity, Springer.
✔ Cedefop (2022). Setting Europe on course for a human digital transition: new evidence from Cedefop’s second European skills and jobs survey, Publications Office of the European Union.
✔ Eurofound (2020), New forms of employment: 2020 update, Publications Office of the European Union.
✔ ILO (2018), The economics of artificial intelligence: Implications for the future of work, International Labour Office.
✔ ILO (2019), Work for a Brighter Future – Global Commission on the Future of Work. International Labour Office.
✔ Nowotny H (2021), “In AI we trust: how the Covid-19 Pandemic Pushes us Deeper into Digitalization”, Delanty G (ed.) (2021), Pandemics, Politics and Society, De Gruyter, 107-121.
✔ OECD (2019b), How’s Life in the Digital Age?, OECD Publishing.
✔ Wilkinson A, and Barry M (eds) (2021), The Future of Work and Employment, Edward Elgar.
✔ Zuboff S (2019), The Age of Surveillance Capitalism, PublicAffairs.