- Details
- Category: Discipline
- The Independent Film Producer¿s Survival Guide, a business and legal sourcebook (Gunnar Erickson, Harris Tulchin and Mark Halloran)
- Audiovisual Content Production
- 6142
- 22275
- Production Workshop
- IPLUSO6142-22275
- 1
- 4
- 0
- 4
- Não
- Português
- Innovative methodologies to support the teaching-learning process are used according to the projects.
- Mandatory
- Provide students with tools and knowledge of practical production based on theoretical knowledge, in order to enable their future autonomy in the job market in the area of ¿¿Audiovisual Production. How to equate a project from the point of view of its Technical, Artistic, Logistical and Financial requirements. Study and reflection from IDEA to SCREEN
- Production Design, Production Definition and Structure, Positions, Functions and Responsibilities of the different cinematographic areas, Production Phases and their implications; Structuring documents of the cinematographic activity. Study and elaboration of the General Production Schedule, Work Maps, Budget, Service Sheets and Production Dossier, Authorization Requests, Introduction to the applied and practical study of the Movie Magic/Scheduling software; Support and financing
Descrição dos instrumentos de avaliação (individuais e de grupo) ¿ testes, trabalhos práticos, relatórios, projetos... respetivas datas de entrega/apresentação... e ponderação na nota final.
Exemplo:
Descrição
Data limite
Ponderação
Teste de avaliação
dd-mm-yyyy
30%
Portfolio
dd-mm-yyyy
40%
(...)
Adicionalmente poderão ser incluídas informações gerais, como por exemplo, referência ao tipo de acompanhamento a prestar ao estudante na realização dos trabalhos; referências bibliográficas e websites úteis; indicações para a redação de trabalho escrito...
- Semestral
- The Pre-Production CU aims to provide students with essential knowledge for the preparation and survey of an audiovisual production. To this end, it addresses the essential areas ranging from writing to distribution as areas to be taken into account when preparing a project.
- Details
- Category: Discipline
- Gouveia, José & Magalhães, Alberto - Redes de Computadores - Curso Completo. 10ª Edição. FCA, 2013. ISBN:9789727227815. Martins, José Legatheaux - Fundamentos de Redes de Computadores Ilustrados com Base na Internet e nos Protocolos TCP/IP. 1a Edição Digital. Nova.FCT Editorial, 2018. https://legatheaux.eu/book/cnfbook-pub.pdf Kozierok, Charles M. - The TCP/IP Guide. http://www.tcpipguide.com/free/t_toc.htm
- Development for the Web and Mobile Devices
- 6378
- 15889
- Networks and Data Communication
- IPLUSO6378-15889
- 1
- 5
- 0
- 4
- Não
- Português
- Use of project-based learning methodology through which students are encouraged to develop solutions for problems that are posed to them, and that address most of the topics taught. This methodology aims for the creation of a "product", which represents a solution to the proposed problem.
- Mandatory
- Upon conclusion of this course the student should: Understand the basic concepts related to digital data communication; Understand the role of the layered models' approach to the description of data communication networks; Recognise and characterise the major components in a local area network; Understand the dynamic IP configuration of hosts using DHCP; Recognise the main protocols of the TCP/IP family, including their functions and relations; Analyze network traffic (IP, TCP, UDP and others) to solve problems and assess security risks; Understant the operation of the main applications used in the Internet; Understant the importance of the most common security related protocols, including SSL/TLS and SSH; Solve problems in a TCP/IP network using a variety of tools, including protocol analyzers, ping and traceroute, and ARP and DNS cache manipulation.
- Introduction to computer networks Components of a data comunicatio network Network classification Layered Models - the OSI model and the TCP/IP model Local Area Networks The standards IEEE 802.3 and IEEE 802.11 Ethernet and Wi-Fi networks Main components: transceivers , repeaters, hubs , switches and access points. MAC addresses General overview of the TCP/IP protocol family Origins and historic overview Documentation (RFCs) The Internet network layer - IP protocol Main functions and message basic structure IP addressing IP address types, notations and structure Auto configuration (DHCP) The Internet transport layer - TCP and UDP protocols Main functions and message basic structure Ports The Internet application layer The name service - DNS protocol The World Wide Web - HTTP protocol Electronic Mail - SMPT, POP and IMAP protocols Security - SSL/TLS and SSH protocols
Descrição dos instrumentos de avaliação (individuais e de grupo) ¿ testes, trabalhos práticos, relatórios, projetos... respetivas datas de entrega/apresentação... e ponderação na nota final.
Exemplo:
Descrição
Data limite
Ponderação
Trabalhos e questionários
20-06-2026
60%
Testes
20-06-2026
40%
Exame de recurso
11-07-2026
100%
As componentes.prática (trabalhos e questionários) e teórica (testes) são requeridas em todas as épocas de avaliação.
Assim, a época de recurso pode consistir em:
- Exame escrito: para quem não teve aproveitamento na componente teórica.
- (Re)Submissão dos trabalhos: para quem não teve aproveitamento na componente prática.
- Exame + (re)submissão dos trabalhos: para quem não teve aproveitamento nem na componente teórica nem na componente prática.
- Semestral
- The widespread use of the Internet as a communications infrastructure, used in a wide range of areas in everyday life, has resulted in a growing demand for skills and competences in the field of computer networks. For this reason, network and data communication professionals increasingly have a fundamental role in organizations. This CU addresses the basic concepts related to data communication networks, with a special focus on the practical aspects related to their use in problem solving. The CU also addresses the TCP/IP protocol family that is at the base of the functionality offered by both the Internet and the vast majority of the organizations' intranets. By providing a solid background in this domain, this CU prepares the students for the challenges posed both by the next phases of the cycle of studies, and by their future participation in a job market where these type of skills are increasingly necessary.
- Details
- Category: Discipline
- Carvalhosa, S. (2010). Prevenção da Violência e do Bullying em Contexto Escolar. Lisboa: Climepsi Editores Dignifee, F. (Coord.) (1990). Acteur social et delinquance ? Une grille de lecture du système de justice pénale. Liège-Bruxelles: Pierre Mardaga. Lyman, M. (2014).Drugs in society: causes, concepts and control. USA: Routledge Matos, M. & Equipa do Projecto Aventura Social (2003). A saúde dos adolescentes portugueses (Quatro anos depois). Lisboa: Edições FMH Negreiros, J., Simões, C., Gaspar, T, Matos, M. (2009). Populações em risco e tipos de intervenção. In. Filho, H. e Ferreira-Borges, C. (coord.). Violência, Bullying e Delinquência. Lisboa, Coisas de Ler Edições, 55 -95. Ornelas, J. (2008). Psicologia Comunitária. Lisboa: Fim de Século
- Monitoring Children and Young People
- 6149
- 22302
- Preventing Risky Behavior in Children and Young People
- IPLUSO6149-22302
- 2
- 7
- 0
- 4
- Não
- Português
- The subjects will be presented using exposition, but favoring the participation of students; to this end, after the problem is equated, students will be sought to participate in the debates established among all, in which references from national and international scientific literature will always be presented. Practical cases will be discussed, preceded by prior preparation, being the object of analysis, discussion and proposals for action with a developed character. Practical knowledge will be prioritized. The evaluation will consist of two moments: (a) the constitution of a prevention program to be designed by the student and subsequent oral presentation (individual work); and (b) frequency; each of these evaluative moments corresponds to 50% of the final classification.
- Mandatory
- This course aims to provide students with specialized information on the construction, planning and implementation of prevention programs, learning how to prioritize and implement actions in different scenarios with potential recipients. The different headings of the program focus on areas in which social calls for prevention, including in the circuit work with local IPSS and CPCJ, including the preparation of intervention/prevention programs for risk situations, behaviors and circumstances, particularly in primary and secondary prevention, operationalizing actions with the different devices and entities with competence in matters of childhood and youth.
- 1. Deviance, Deviant Behavior and Vulnerabilities: A brief theoretical approach 2. From risk to protection 2.1 Risk factors 2.1.1 Individual domain 2.1.2 Primary socialization agents: family, school and peer group. 2.1.3. secondary socialization agents: community domain 2.2 Protective factors 2.2.1 Individual domain 2.2.2 Primary socialization agents: family, school and peer group 2.2.3. secondary socialization agents: community domain 3. Populations at risk and types of prevention. 4. Competences and attributions in the judicial and social sphere: Juvenile Courts and Commissions for the Protection of Children and Young People. Social Network 5. Prevention of behaviors and risk situations. Prevention strategies. 6. Social Diagnosis. Interventional methodologies: potentialities and limits.
Descrição dos instrumentos de avaliação (individuais e de grupo) ¿ testes, trabalhos práticos, relatórios, projetos... respetivas datas de entrega/apresentação... e ponderação na nota final.
Exemplo:
Descrição
Data limite
Ponderação
Teste de avaliação
Janeiro
50%
Trabalho individual
Apresentação dos trabalhos em Dezembro
50%
(...)
Adicionalmente poderão ser incluídas informações gerais, como por exemplo, referência ao tipo de acompanhamento a prestar ao estudante na realização dos trabalhos; referências bibliográficas e websites úteis; indicações para a redação de trabalho escrito...
- Semestral
- This UC aims to foster in students the need for knowledge and understanding of the main concepts of prevention, especially with regard to intervention techniques with children and young people. It also aims to initiate students in the analysis and reflection of the constructs present in professional practice, as well as the principles and rules underlying the methodology and elaboration of prevention programs, boosting rigorous work and adaptation to formal and informal situations in intervention devices. informal situations in intervention devices.
- Details
- Category: Discipline
- Russell, S. J., & Norvig, P. (2021). Artificial intelligence: A modern approach (4th ed.). Pearson Education. Géron, A. (2022). Hands-on machine learning with Scikit-Learn, Keras, and TensorFlow (3rd ed.). O’Reilly Media. Mitchell, T. M. (1997). Machine learning. McGraw-Hill. Goodfellow, I., Bengio, Y., & Courville, A. (2016). Deep learning. MIT Press. Sutton, R. S., & Barto, A. G. (2018). Reinforcement learning: An introduction (2nd ed.). MIT Press.
- Automation and Computer Systems
- 6865
- 2129
- Artificial Intelligence
- IPLUSO6865-2129
- 3
- 5
- 0
- 4
- Não
- Português
- The course adopts active, student-centred methodologies, combining theoretical-practical classes with guided problem solving and small project development. Practical examples and Python scripts are used to illustrate AI concepts and promote learning through experimentation. Critical analysis of results, classroom discussion, and guided exercises foster autonomous reasoning. The use of up-to-date computational tools and real or synthetic datasets brings the teaching and learning process closer to professional contexts, promoting technical, analytical, and critical thinking skills.
- Mandatory
- By the end of the course, students should be able to: (i) explain core AI, ML, DL and RL concepts; (ii) formulate problems and select suitable models/algorithms; (iii) implement, train and evaluate models in Python using appropriate metrics and validation; (iv) interpret results and recognise data requirements, bias and limitations; (v) integrate AI solutions in automation and computing scenarios while respecting ethical and scientific good practices
- The course covers the fundamentals of Artificial Intelligence, starting with core concepts, terminology, and historical background, as well as the relationship between AI, machine learning, and deep learning. Intelligent agents, knowledge representation, and problem-solving techniques are introduced. The main learning paradigms are studied, including supervised, unsupervised, and reinforcement learning, addressing datasets, training, validation, and performance metrics. Classical classification and regression models, clustering techniques, and introductory artificial neural networks are explored. The course also includes reinforcement learning and practical examples applied to automation and computing systems. Finally, limitations, risks, and ethical aspects related to the use of AI systems are discussed.
Descrição dos instrumentos de avaliação (individuais e de grupo) ¿ testes, trabalhos práticos, relatórios, projetos... respetivas datas de entrega/apresentação... e ponderação na nota final.
Exemplo:
Descrição
Data limite
Ponderação
Teste de avaliação, nota minima 8 valores
S15
30%
Projeto em grupo (2 alunos): implementação + relatório técnico/artigo curto + demonstração
S12-S15
50%
Labs Guiados (individuais): submissão de scripts Python + respostas curtas (Lab 1 e Lab 2)
S10-11
20%
- Semestral
- The Artificial Intelligence course unit is offered in the 3rd year of the Bachelor’s degree in Automation and Computer Systems and aims to provide a structured and rigorous introduction to the fundamental principles, models, and techniques of Artificial Intelligence (AI). The course covers the main AI paradigms, with particular emphasis on machine learning, reinforcement learning, and their practical application in engineering and computational systems. The scope of the course includes both theoretical and practical components, enabling students to understand the conceptual foundations of AI, its application domains, and inherent limitations, while also developing skills in the implementation of algorithms and models in a computational environment. The course promotes a critical and applied perspective, preparing students to integrate AI-based solutions into automation systems, networks, intelligent systems, and industrial and technological applications.
- Details
- Category: Discipline
- Murteira, B, Ribeiro, C.S., Silva,J.A. e Pimenta,C. (2015) Introdução à Estatística. Escolar editora. Pestana,d. e Velosa,H. (2006) Introdução à Probabilidade e Estatística. Fundação Calouste Gulbenkian. Reis, E., Melo, P. , Andrade,R. e Calapez,T. (2007) Estatística Aplicada, vol.1 e 2. Edições Sílabo. Ross,S. (2009) Introduction to Probability and Statistics for Engineers and Scientists, 4th edition. Elsevier Academic Press.
- Computer Engineering and Applications
- 6615
- 620
- Probabilities and Statistics
- IPLUSO6615-620
- 2
- 6
- 0
- 4
- Não
- Português
- Application of acquired knowledge to the study of real problemas and use of statistical software.
- Mandatory
- Be able to calculate and interpret the most important desciptive statistical measures and identify their properties; to calculate probabilities using different concepts; to calculate conditional probability and apply the principles of multiplication, total probability and Bayes' theorem. Be able to use the concept of random variable and to operate with probability functions and distributions. Know the most important discrete and continuos distributions and some of their properties. Calculate confidence intervals and apply hypothesis tests and interpret the obtained results. Know the Linear Regression Model and evaluate the adjustment of the model to data.
- Descriptive statistics: Basic concepts. Measures of location, measures of dispersion. Graphic presentation. Random experiment. Events. Sample space. Algebra of events. Probability concepts. Axiomatic of Kolmogorov. Conditional probability. Independence. Bayes theorem Discrete and Continuous random variables. Probability and distribuition functions. Mean value, variance and standard deviation Discrete distributions: Uniform, Binomial, Negative Binomial and Poisson distributions Continuous distributions: Uniform, Normal, Exponential, Chi-square and t-Student distributions Statistical inference. Sample distributions. Central limit theorem Estimation by points or by intervals. Confidence interval for mean (know and unknow variance, large and small sample). Confidence interval for variance and standard deviation. Confidence interval for proportion Hypothesis Testing The Linear Regression Model
Descrição dos instrumentos de avaliação (individuais e de grupo) ¿ testes, trabalhos práticos, relatórios, projetos... respetivas datas de entrega/apresentação... e ponderação na nota final.
Exemplo:
Descrição
Data limite
Ponderação
1ºteste
40%
2ºteste
40%
2 Trabalhos (10%+10%)
20%
- Semestral
- Provides a wide range of basic knowledge, skills and tools essential for data analysis.
