S1 Co-creation methodologies based on Design Thinking and Design Sprint
C2 Sustainable Development Goals (SDGs) of the United Nations. Creation of value propositions
S3 Presentation of case studies and digital technologies project topics (product, service or process)
S4 Selecting the project topic and framing it in the organization
S5 Problem space: creating empathy with the user and his organization, defining the problem and its related issues, considering business requirements, customer and user needs, and technology challenges
S6 Application of a systematic literature review methodology and its critical analysis. Competition analysis (if applicable)
S7 Identification of digital resources (including data collection), computational, and other resources required for project development
S8 Application of agile project management methodologies, appropriate to the group work to be developed by the students. Communication of results

Course in periodic assessment, not contemplating final exam, given the adoption of the project-based teaching-learning method applied to real situations. Presentations, demonstrations and discussion will be carried out in groups.
Assessment weights:
R1 Report: Project Topic Definition: 5%
R2 Report: Empathy with the User and the Organization and Definition of the Problem. Its presentation and group discussion: 40%
R3 Report: Systematic Literature Review and Project Development Planning. Its presentation and group discussion: 55%

Mandatory

·
Brown, T. / HarperCollins, 2009, ISBN-13: 978-0062856623, Change by Design: How Design Thinking Transforms Organizations and Inspires Innovation, 2009, ·, ·
Osterwalder, A., Pigneur, Y., Papadakos, P., Bernarda, G., Papadakos, T., & Smith, A., Value proposition design / John Wiley & Sons., 2014, ·, ·
Knapp, J., Zeratsky, J., & Kowitz, B. / Bantam Press, Sprint: How to Solve Big Problems and Test New Ideas in Just Five Days, 2016, ·, ·
Lewrick, M, Link, P., Leifer, L. / Wiley, ISBN 9781119629191, The Design Thinking Toolbox, 2020, ·, ·

Optional

·
Ries, E. / capítulos 3 e 4, Penguin Group, Ries, E. (2017), The Lean Startup: How Today's Entrepreneurs Use Continuous Innovation to Create Radically Successful Businesses, 2017, ·, ·
·, Scrum Institute (2020), The Kanban Framework 3rd Edition, 2020, ·, www.scrum-institute.org/contents/The_Kanban_Framework_by_International_Scrum_Institute.pdf acedido em 02/2023
Darrell Rigby, Sarah Elk, Steve Berez / The Scrum Framework 3rd Edition, Doing Agile Right: Transformation Without Chaos HardcoverScrum Institute, 2020, ·, www.scrum-institute.org/contents/The_Scrum_Framework_by_International_Scrum_Institute.pdf acedido em 02/2023
Jeff Sutherland, J.J. Sutherland, Scrum: The Art of Doing Twice the Work in Half the Time, 2014, ·, ·
Project Management Institute / 6th ed. Newton Square, PA: Project Management Institute, A guide to the project management body of knowledge (PMBOK guide), 2017, ·, ·
Gwaldis M., How to conduct a successful pilot: Fail fast, safe, and smart, 2019, ·, https://blog.shi.com/melissa-gwaldis/ acedido em 02/2023

P1. Quality Control (QC), quality metrics and non-destructive inspection.
P2. Integration of QC in automation systems and interconnection to the process.
P3. Fundamentals of artificial vision and artificial intelligence essential to QC.
P4. Selection and calibration of sensors, lenses, filters, and lighting for QC based on artificial vision.
P5. Passive and active collection of sensory data, its filtering, processing, and analysis for QC.
P6. Automatic learning of models and their use in detecting and predicting failures/deviations.
P7. Human-machine interfaces in the context of QC.

Periodic Assessment: Group project (60%) + Individual written test (40%).
Assessment by Exam: Individual written exam (100%).

Mandatory

Szeliski, R. (2021). Computer Vision: Algorithms and Applications (2nd ed). Springer.
Dawson-Howe, K. (2014). A Practical Introduction to Computer Vision with OpenCV (1st. ed.). Wiley.
Anand, S., & Priya, L. (2019). A Guide for Machine Vision in Quality Control (1st ed.). CRC Press.

Optional

CP1: Robotics Fundamentals
CP2: Robot Technology
CP3: Robot Applications in Industry
CP4: Kinematics
CP5: Robot Languages and Programming
CP6: Robot Control Systems
CP7: Block Programming
CP8: Redundancy

The evaluation is based on a project (50%) and a final exam (50%).
The project has two evaluation phases, mid-term delivery and a final oral examination.
Final grade is the average from the project and the exam grades

Mandatory

Saeed B. Niku, "Introdução a Robótica: Análise, Controle, Aplicações , 2ªedição LTC Editora
J. Norberto Pires, "Robótica Insdustrial Industria 4.0" ,Lidel, Lisboa, 2018.
Norberto J. Pires , "Automação e Controlo Industrial",Lidel, Lisboa, 2019
P. Oliveira, ?Curso de Automação Industrial?, ETEP, LIDEL, 2008

Optional

--

S1 Solution space: ideation of the best technological solution relative to the project, development of user requirements, storyboarding, user/costumer journey, iterative prototyping cycles (low fidelity - lo-fi, high fidelity - hi-fi, minimum viable product - MVP), heuristic evaluation of the solution with experts and evaluation with end users.
S2 Production of solution design documentation, including, where applicable, architecture, technical specifications, hardware and software configuration, installation, operation and use manuals.
S3. Experimental deployment of the solution with the potential to be triple sustainable (with economic, social and environmental value creation), safeguarding the applicable legal framework.
S4. Audiovisual communication on the Web and social networks. Communication in public and its structure. Presentation to relevant actors.
S5. Demonstration in workshop with relevant actors

UC in periodic assessment, not contemplating final exam, given the adoption of the project-based teaching method applied to real situations. Presentations, demonstrations and discussion are carried out in groups.
Evaluation weights:
R1 Solution Ideation Report, with Storyboard, User Journey, User Requirements, Technical Specifications and its audiovisual presentation: 20%.
R2 Solution Prototyping: Lo-fi and Hi-fi Prototypes and Minimum Viable Prototype - MVP (on GitHub), its Demonstration and Evaluation Report: 40%
R3 Solution Design Report with the following elements (if applicable): Architecture (UML Package Diagram, UML Component Diagram), Hardware and Software Configuration, Installation Manual (UML Deployment Diagram, Configuration Tutorial), Operation Manual, User Manual: 20%
R4 Audio-visual presentation of the solution and its demonstration in a Workshop: 20%.

Mandatory

·
HarperCollins, 2009, ISBN-13: 978-0062856623, Change by Design: How Design Thinking Transforms Organizations and Inspires Innovation, 2009, ·, ·
Lewrick, M, Link, P., Leifer, L. / Wiley, ISBN 9781119629191, The Design Thinking Toolbox, 2020, ·, ·
Knapp, J., Zeratsky, J., & Kowitz, B. / Bantam Press, Sprint: How to Solve Big Problems and Test New Ideas in Just Five Days., 2016, ·, ·

Optional

·
Ries, E. / capítulos 3 e 4, Penguin Group, The Lean Startup: How Today's Entrepreneurs Use Continuous Innovation to Create Radically Successful Businesses, 2017, ·, ·
·, Scrum Institute, The Kanban Framework 3rd Edition, 2020, ·, www.scrum-institute.org/contents/The_Kanban_Framework_by_International_Scrum_Institute.pdf acedido em 02/2023
Darrell Rigby, Sarah Elk, Steve Berez / Scrum Institute (2020), The Scrum Framework 3rd Edition, Doing Agile Right: Transformation Without Chaos Hardcover Scrum Institute (2020), The Scrum Framework 3rd Edition, 2020, ·, www.scrum-institute.org/contents/The_Scrum_Framework_by_International_Scrum_Institute.pdf
Jeff Sutherland, J.J. Sutherland, Scrum: The Art of Doing Twice the Work in Half the Time, 2014, ·, ·
Project Management Institute / 6th ed. Newton Square, PA: Project Management Institute, A guide to the project management body of knowledge (PMBOK guide), 2017, ·, ·
Gwaldis M., How to conduct a successful pilot: Fail fast, safe, and smart, 2019, ·, https://blog.shi.com/melissa-gwaldis/ acedido em 02/2023

CP1. Introduction to communication networks based on the OSI (Open Systems Interconnection) model. Architecture of office and industrial automation networks.
CP2. Computer networks (Ethernet, IP, UDP, TCP, sockets).
CP3. Industrial communication networks (Modbus, Profibus).
CP4. Industrial Ethernet (Modbus TCP, Profinet).
CP5. Data sharing and logging using the OPC (Open Platform Communications) platform.
CP6. Supervisory systems (SCADA).

Continuous evaluation consists of interim tests, laboratory projects and/or bibliographic research works.
In case of reproval, the continuous assessment will be replaced by a final written exam.

Mandatory

4) "Automation, production systems, and computer integrated manufacturing, 5th ed.", Mikell Groover, Pearson, 2019
3) "Fieldbus and Networking in Process Automation", Sunit Kumar Sen, CRC Press, 2014, ISBN 978-1-4665-8677-2
2) "TCP/IP Teoria e Prática", Fernando Boavida e MArio Bernardes, FCA Editora de Informática
1) "Computer Networks", Andrew Tanenbaum, Prentice Hall

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. 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/

P1. Real Variable Functions:
1.1. Polynomial, rational, trigonometric, and exponential functions
1.2. Logarithmic and inverse trigonometric functions
1.3. Inverse and composite functions
1.4. Limits and indeterminate forms
1.5. Continuity

P2. Differential Calculus:
2.1. Rates of change
2.2. Derivative at a point and tangent line
2.3. Differentiation rules
2.4. Chain rule
2.5. Intervals of monotonicity and concavity of the graph
2.6. Taylor approximations

P3. Integral Calculus:
3.1. Definite integral, fundamental theorem of calculus, and primitives
3.2. Integration techniques
3.3. Applications of integration
3.4. Improper integrals and convergence

P4. Sequences and Series:
4.1. Sequences: monotonicity and convergence
4.2. Numerical series: sums and convergence criteria

Passing requires a grade of no less than 10 out of 20 in one of the following modalities:
- Assessment throughout the semester: 1 midterm mini-test (10%) + 1 group project of 3-4 members (20%) + Autonomous work (10%) + 1 final test on the first exam date (60%). A minimum grade of 8 out of 20 is required in both the final test and the average of other assessment moments throughout the semester.
- Assessment by exam (100%): Individual written test in any exam period.
- An oral assessment may be conducted after any assessment moment to validate the final grade.

Mandatory

Stewart, James, Daniel K. Clegg, and Saleem Watson. Calculus. Cengage Learning, 2020.
Anton, Howard, Irl C. Bivens, and Stephen Davis. Calculus: early transcendentals. John Wiley & Sons, 2021.

Optional

Campos Ferreira, J., Campos Ferreira, J. (2018) Introdução à Análise Matemática, Fundação Calouste Gulbenkian, 2018, null
Stewart, J., Stewart, J. (2013) Cálculo, Vol I, Cengage Learning, (7ª Ed.), 2013, null
Strang, G., Strang, G. (2007) Computational Science and Engineering, Wellesley-Cambridge Press, 2007, null
Solomon, Justin, Solomon, Justin (2015) Numerical Algorithms, CRC Press., 2015, null
Goldstein, L., Goldstein, L. (2011) Matemática Aplicada à Economia. Administração e Contabilidade, (12a edição) Editora Bookman., 2011, null

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 data analysis – types, sources, and data lifecycle.
CP2: Organizing and cleaning data in Excel – formats, filters, validation. Basic and advanced Excel functions – statistics, logic, search, and reference.
CP3: Basics of Descriptive Statistics: Types of variables. Frequency tables and graphical representations. Measures of central tendency, dispersion, skewness, and kurtosis. Exploratory data analysis.
CP4: Basics of predictive data modeling: Simple and multiple linear regression, logistic regression.
CP5: Data visualization – graphs, conditional formatting, simple dashboards.

Assessment throughout the semester includes:

- Practical data analysis project completed in a group (maximum 3 students), including a report (15%), with mandatory midterm submission (15%) and oral defense with individual grading (20%). Minimum grade of 8 points.
- Individual exam (30%) to assess theoretical knowledge.
- In-class exercises and weekly assignments (20%).

The use of AI tools (e.g., ChatGPT) is permitted for technical support and must be clearly referenced with the prompts used.

The Final Exam is a written, individual, closed-book exam covering all material.

Those who do not opt ​​for assessment throughout the semester take the final exam in Period 1.

Those who did not successfully complete the assessment throughout the semester, or the exam in Period 1, with a score greater than or equal to 9.5 (out of 20), take the final exam in Period 2.

Mandatory

Wayne L. Winston, Microsoft Excel Data Analysis and Business Modeling (Office 2021 and Microsoft 365), 7th Edition (2021)

Elizabeth Reis, Estatística Descritiva, 7ª Edição, Edições Silabo (2008)

Cole Nussbaumer Knaflic, 'Storytelling with data: a data visualization guide for business professionals', John Wiley & Sons, Inc., 2015.

Optional

Será disponibilizada consoante os interesses dos estudantes e atualizações tecnológicas relevantes.

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. 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.
Grunwald, A. (2018). Technology Assessment in Practice and Theory. London: Routledge.
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.

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.

CP 1. Models, unities and calculus
CP 2. Unidimensional movement
CP 3. Bidimensional movement
CP 4. Newton's laws
CP 5. Conservation of Energy
CP 6. Electric Field and Magnetic Field
CP 7. Plane Waves and Transverse Waves
CP 8. Propagation of Electromagnetic Waves

Passing requires a grade of no less than 10 out of 20 in one of the following modalities:
- Assessment throughout the semester: 1 midterm mini-test (20% - minimum grade of 7 out of 20 is required) + autonomous work (10%) + 1 final test on the first exam date (70%);
- Assessment by exam (100%): Individual written test in any exam period.
- An oral assessment may be conducted after any assessment moment to validate the final grade.

Mandatory

Marcelo Alonso e Edward J. Finn, Física, Escolar Editora, 2012
Paul Tipler e Gene Mosca, Physics for Scientists and Engineers, McGraw Hills Companies, Inc., New York, 2022
Paul G. Hewitt, Física: Princípios e Problemas, Editora Artmed, 2019
David Halliday, Robert Resnick e Jearl Walker, Fundamentos de Física, Editora LTC, 2021.

Optional

Adilson J. S. Pereira e Ricardo M. F. de Oliveira, Física: Conteúdo e Prática, Editora Pearson, 2020
Raymond A. Serway e John W. Jewett, Physics for Scientists and Engineers, Cengage Learning, 2019
Hugh D. Young e Roger A. Freedman, University Physics with Modern Physics, Pearson, 2019
R. P. Feynman, Feynman Lectures on Physics, Edição Addison Wesley, 2011

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 Concept of vector space (VS) and subspace. Linear dependence of vectors and basis of a VS.
PC2 Points and vectors in the plane and in space. Distance between two points and from a point to a line. Plane sections and spherical surface.
PC3 Vectors and operations. Internal product. Parallelism and perpendicularity of vectors. Relative position of lines and planes.
PC4 Vector director and equation of a line.
PC5 Cross product. Vector normal to a plane and equations of the plane.
PC6 Parametrization of curves in plane and in space. Normal and tangent vectors to a curve. Intersection of curves. Polar coordinates.
PC7 Matrices and operations. Inverse of a non singular matrix. Determinant of a square matrix.
PC8 Systems of linear equations. Matrix form and resolution. Linear transformations.
PC9 Quadratic equations. Complex numbers in algebraic and polar forms. Euler's formula.
PC10 The set of complex numbers as real VS . Moivre's formula. Roots of a complex number.

Approval with an overall grade of at least 10 points (scale 1-20) in one of the following modes:
- Assessment Throughout the Semester: Test 1 (35%) + Test 2 (35%) + practical group work (15%) + exercises solved on Moodle and/or in class (15%). A minimum score of 8 out of 20 is required for each assessment component.
- Exam Assessment: In any exam period, with an individual written exam (100%).

There is the possibility of conducting oral examinations.

Mandatory

[1] Cabral, I., Perdigão C. e Saiago, C. (2018). Álgebra Linear: Teoria, Exercícios Resolvidos e Exercícios Propostos com Soluções, Escolar Editora.
[2] Strang, G., (2007). Computational Science and Engineering, Wellesley-Cambridge Press.
[3] Goldstein, L. (2011). Matemática Aplicada ? Economia. Administração e Contabilidade, (12ª edição) Editora Bookman.
[4] Hanselman, D., Littlefield, B. and MathWorks Inc. (1997). The Student Edition of MATLAB, 5th Version, Prentice-Hall
[5] Materiais científico-pedagógicos (slides, notas de desenvolvimento, código e pseudo código, fichas de exercícios e problemas) disponibilizados pela equipa docente
Scientific-pedagogical materials (slides, lectures, code and pseudo code, exercise sheets, problems) provided by the teaching team.

Optional

David C. Lay, Linear Algebra and its Applications, Addison Wesley, Pearson

CP1. Characteristics of the industrial manufacturing company
a. The Digital Transformation and Industry 4.0
b. Operation and organizational structure of the company
CP2. Operations and business process management
a. Operations and logistics management.
b. Organizational architecture and industrial processes
c. Business Process Management (BPM)
d. Visual process modeling (with BPMN)
CP3. Information systems in manufacturing
a. Management and information systems
b. IS requirements
c. Automation of production and logistics processes (ERP, WMS, TMS)
CP4. applied project

Evaluation throughout the semester
Group assignment (report + presentation + final discussion) 40%
Individual report (thematic or field visit) 20%
Individual final test 40%

In order to get approval, students must score, at least, 8 points (over 20) in every evaluation component with a weight over 30%.

Final exam
Final exam 100%

Mandatory

Object Management Group, Business Process Model and Notation, http://www.bpmn.org/."
Dumas, M.; La Rosa, M.; Mendling, J.; Reijers, H.A. (2018), Fundamentals of Business Process Management, 2nd edition, Springer (www. http://fundamentals-of-bpm.org/)
Laudon, K., Laudon, J., 2016, Management Information Systems - Managing the Digital Firm, 14th Edition, Global Edition.
Documentação de apoio ao software utilizado (ERP Primavera ou outro, Bizagi, etc.)
Slack, N. e Brandon-Jones, A. (2019) Operations Management, 9ª Edição, Pearson
"Slides, handouts

Optional

--

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

European Commission. (2024). PM² Guide - Open Edition 3.5 (ISBN: 978-92-76-60378-4). Publications Office of the European Union. https://op.europa.eu/pt/publication-detail/-/publication/97cc2f12-c648-11ee-95d9-01aa75ed71a1
Kerzner, H. (2022). Project management: A systems approach to planning, scheduling, and controlling (13th ed.). John Wiley & Sons.
Project Management Institute. (2021). A guide to the project management body of knowledge (PMBOK® guide) (7th ed.). Project Management Institute.
Rigby, D. K., Elk, S., & Berez, S. (2020). Doing agile right: Transformation without chaos. Harvard Business Review Press.
Schwaber, K. (2004). Agile project management with Scrum. Microsoft Press.

Optional

European Commission. (n.d.). PM² Project Management Methodology – Resources. European Commission. https://pm2.europa.eu/pm2-resources_en
European Commission. (n.d.). PM² Essentials: Project Management Methodology. EU Academy. https://academy.europa.eu/courses/pm-c1-pm-essentials-project-management-methodology
European Commission. (n.d.). PM² Agile Essentials. EU Academy. https://academy.europa.eu/courses/pm-a1-pm-agile-essentials
International Organization for Standardization. (2020). ISO 21502:2020—Project, programme and portfolio management: Guidance on project management. ISO.

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. Basic concepts of descriptive statistics, inferential statistics, probabilities and normal distribution
S2. Estimation
S2.1 Confidence intervals for the mean and proportion
S2.2 Determining sample size
S3. Hypothesis tests: parametric and non-parametric tests
S3.1 One-sample t-test
S3.2 t/Mann-Whitney test for two independent samples
S3.3 One-factor ANOVA/Kruskal-Wallis
S3.4 Chi-squared test of independence
S4: Correlation and Regression Line

Pass with a mark of not less than 10 in one of the following ways:
- Assessment throughout the semester: 1 mini-test taken in class (20%) + Final written test taken on the date of the 1st period (60%) + group project (20%),
All assessment elements are compulsory and have a minimum mark of 8.
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

Afonso, A. & Nunes, C. (2019). Probabilidades e Estatística. Aplicações e Soluções em SPSS. Versão revista e aumentada. Universidade de Évora.
Laureano, Raul (2020) - Testes de Hipóteses e Regressão, Lisboa, Edições Sílabo.
Marôco, J. (2018) - Análise Estatística com o SPSS Statistics (7ªed.), Pêro Pinheiro, ReportNumber.
Mehmet, M. and Jakobsen, Tor G. (2022). Applied Statistics Using Stata: A Guide for the Social Sciences (2nd ed.). SAGE Publications.

Optional

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

CP1: Basic notions of electrical components and circuits
CP1.1: Units and scales
CP1.2: Voltage and current sources
CP1.3: Ohm's Law
CP1.4: Kirchhoff's Laws
CP2: Analysis of electrical circuits
CP2.1: Linearity and overlap
CP2.2: Thevenin and Norton theorems
CP2.3. Maximum Power Transfer Theorem (MPTT)
CP3: Capacitors and coils
CP3.1: Capacitors
CP3.2: Coils
CP3.3: RLC Circuits
CP4: DC Bridges and Operational Amplifiers
CP4.1: AmpOps Basics
CP4.2: Linear operation
CP4.3: DC Circuits and Bridges
CP4.4: Circuits, DC Bridges and Operational Amplifiers

Assessment throughout the semester:

A1: Laboratory and Reports (30%)
A2: 1st Written Test (30%)
A3: 2nd Written Test (40%)

Minimum mark in Laboratory and Report: 8.5
Minimum mark in Written Tests: 8.5
(final average greater than or equal to 9.5)


The possibility of assessment throughout the semester is conditional on:
- Attendance at laboratory classes (100%) *,
- Attendance at lectures (50%),
- Attendance at theoretical-practical classes at least (50%).
*If laboratory absences are recorded for objective reasons, a way of making up the missed laboratory will be agreed with the teacher.


Assessment by exam:

Exam (100%) in the 1st, 2nd and special exam periods.
The exam will include, in addition to the content of the theoretical and practical classes, some content related to the laboratory work carried out.

Mandatory

Electric Circuits, Global Edition: Global Edition, 11th Edition, by James W. Nilsson, Susan Riedel;
Schaum's Outline of Basic Circuit Analysis, Second Edition, by John O'Malley;
Manuel de Medeiros Silva, Introdução aos Circuitos Eléctricos e Electrónicos, 2ª Ed., Fundação Calouste Gulbenkian, 2001;
Hayt, Kemmerly, Durbin, "Engineering Circuit Analysis", 9th Edition, McGraw Hill, 2008;

Optional

J. David Irwin, Basic Engineering Circuit Analysis, 11ª Ed., Wiley, 2015;
Richard C. Dorf, James Svoboda, Introduction to Electric Circuits, 9ª Ed., Wiley, 2013;
James W. Nilsson, Susan A. Riedel, Introductory Circuits for Electrical and Computer Engineering, Prentice-Hall, 2002;
Vítor Meireles, Circuitos Eléctricos, Lidel, 2001;
John O'Malley, Análise de Circuitos, Colecção Schaum, McGraw-Hill, 1993;

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

P1. Human factors, user models, user experience, and usability.
P2. User-centred design, prototyping, and evaluation of interactive systems.
P3. Basics of visualization and interaction.
Q4. Fundamentals of human-robot interaction and social robotics.
Q5. Graphical, natural, and multimodal interfaces in robotics.
P6. Interfaces based on virtual reality and mixed reality in robotics.
P7. Simulation of human-robot systems.
P8. Testing and validation of human-robot systems.

- Periodic Assessment: Group project (60%) + Individual written test (40%).
- Assessment by Exam: Individual written exam (100%).

Mandatory

? Bartneck, C., Belpaeme, T., Eyssel, F., Kanda, T., Keijsers, M., & ?abanovi?, S. (2020). Human-robot interaction: An introduction. Cambridge University Press.
? Alan Dix, Janet E. Finlay, Gregory D. Abowd, and Russell Beale. 2003. Human-Computer Interaction (3rd Edition). Prentice-Hall, Inc., USA.

Optional

--

CP1 Classification sensors; analog and digital sensors, operation, applications.
CP2: Actuators: classification, operation and applications
CP3: Signal conditioning: amplification, analog signal processing -analog filtering, specific control circuits for actuators:
CP4 Elements about analogue and analogue digital conversion..
CP5 Digital signal processing: time-domain and frequency-domain signal analysis; digital filtering algorithms.
CP6 Implementation of digital processing algorithms on real-time computing platforms
CP7 Systems design with sensors and actuators and signal processing modules and applications::industrial, cities and smart homes, transport, precision agriculture.

Laboratory (40%) + Written exam (60%)
Minimum grade in the laboratory: 8
Minimum exam grade: 8
The possibility of taking the written exam in the normal or special season is subject to:
- Presence in laboratory classes (100%) *,
- Presence in theoretical classes at least (50%),
- Presence in theoretical-practical classes at least (50%).
*If for objective reasons absences are registered in the laboratory, a way to recover the missing laboratory will be agreed with the professor.

Mandatory

Clarence W. de Silva, Sensors and Actuators, Engineering System Instrumentation, Second Edition, CRC press 2015.
Octavian Postolache,Eletronica Programada e Processamento digital de SinaisI: Guia de laboratórios, ISCTE-IUL, 2021;
Allen B. Downey,Think DSP: Digital Signal Processing in Python, O'Reilly Media; 1st edition, 2016
Clarence W. de Silva,Sensors and Actuators: Engineering System Instrumentation, Second Edition, CRC Press 2015

Optional

William Bolton, Instrumentation and Control Systems, Newnes; 3rd edition, 2021
NJATC NJATC Fundamentals of Instrumentation 2nd Edition
John G. Webster, Halit Eren Measurement, Instrumentation, and Sensors Handbook, CRC press 2014

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

CP1: Introduction
CP2: Combinational Logic
CP3: Sequential Logic
CP4: Programming Languages
CP5: Algorithms
CP6: Finite Automation
CP7: Programmable Industrial Automation

Compulsory attendance of the student in 90% of Curricular Unit activities. Completion and presentation in laboratory of group project. Assessment weights:
- 5% - Attendance and participation in class.
- 70% - 4 group project work assignments.
- 25% - Mini-test with multiple answers.
The student waives the exam with 10 marks. In case of failure in the regular season the student has access to the exam of the resource season.

Mandatory

J. N. Pires, ?Automação Industrial?, 3a Edição. Lidel, 2007.
J. R. C. Pinto, ?Técnicas de Automação?, Lidel, Lisboa, 2004.
A. Francisco, ?Autómatos Programáveis (Programação, GRAFCET, Aplicações)?, 4a Edição, Lidel, 2007

Optional

Mandado Pérez et al, Autómatas Programables, entorno y aplicaciones, Thomson, ed. Siemens, 2005;
W. Bolton , Programmable Logic Controllers - 6th Edition, Elsevier

CP1: General Concepts on measurement and measuring instruments and on the control of industrial processes,
CP2: Industrial instrument for measuring process quantities: pressure, force, level, flow, temperature, heat, humidity, density, viscosity and pH.
CP3: Signal conditioning for industrial instruments: amplifiers, measuring bridges.
CP4: Valves and Actuators and Motor Control - Applications
CP5:Control modes and digital controllers.
CP6: Programmable Logic Circuits and Applications
CP7: Communication protocols with application in industrial instrumentation and control systems.

Laboratory (40%) + Written exam (60%), Continuous Evaluation
Minimum grade in the lab: 8
Minimum exam grade: 8
The possibility of taking the written exam in the normal or special season is subject to:
- Presence in laboratory classes (100%) *,
- Presence in theoretical classes at least (50%),
- Presence in theoretical-practical classes at least (50%).
*If for objective reasons absences are registered in the laboratory, a way to recover the missing laboratory will be agreed upon with the professor.

Mandatory

William Dunn, Fundamentals of Industrial Instrumentation and Process Control, Second Edition, Mc Graw Hill Education 2018.
Octavian Postolache, Instrumentação e Controlo Industrial : Guia de laboratórios, ISCTE-IUL, 2021;
William Bolton, Instrumentation and Control Systems, Newnes; 3rd edition, 2021

Optional

Wiliam Bolton Instrumentation and Control 2nd edition, Elsevier, 2015
NJATC NJATC Fundamentals of Instrumentation 2nd Edition
John G. Webster, Halit Eren Measurement, Instrumentation, and Sensors Handbook, CRC press 2014

CP1:Typical architecture and internal units of a microcontroller,
CP2: Memory types and organization.
CP3: Analog and Digital Signal Interface.
CP4: Timing/counting, Interrupts
CP5:Serial communications (UART,SPI, I2C).
CP6Program development using C and dedicated libraries
CP7Planning and realization of a microcontroller based project.

Written test (40%)
Laboratory Work (30%)
Final mini-project (30%)
Minimum grade 8

Mandatory

·, Simon Monk, Programming Arduino, 2016, ·, ·
·, Microcontroladores - Guia de Laboratório, 2023, ·, ·
·

Optional

Tero Karvinen, Kimmo Karvinen, V. Valtokari / MalerMedia, Sebastopol, Make Sensors, 2015, ·, ·

CP1. Introduction to Electronics: Semiconductors, Diodes and transistors. Analog and digital electronics.
CP2. Introduction to Power Electronics: Power electronics applications; Power electronics converters classification;
CP3. Single and three phase uncontrolled rectifiers, natural and forced commutation: Applications and semiconductor type selection; Half and full bridge converter
CP4. DC-DC Converters
CP5. Introduction to resonant converters and switched-mode sources: Advantages of this type of converters; Isolated and multiple output switched-mode sources.
CP6. Single-Phase and Three-Phase Inverters
CP7. AC-AC converters without DC Bus Intermediate: Single-phase configurations

Laboratory (40%) + Written exam (60%)
Minimum grade in the laboratory: 8
Minimum exam grade: 8
The possibility of taking the written exam in the normal or special season is subject to:
- Presence in laboratory classes (100%) *,
- Presence in theoretical classes at least (50%),
- Presence in theoretical-practical classes at least (50%).
*If for objective reasons absences are registered in the laboratory, a way to recover the missing laboratory will be agreed with the professor.

Mandatory

"Introduction to modern power electronics", Andrzej M. Trzynadlowski, JohnWiley & Sons, Third edition, 2016.
"Electronics Fundamentals: Circuits, Devices & Applications", Thomas Floyd, David Buchla, 8th Edition, 2014

Optional

Robert W. Erickson , Dragan Maksimovi?, Fundamentals of Power Electronics 3rd ed. Edition, Springer, 2020