- Details
- Category: Discipline
- Chanyakorn, O. A. (2023). Architectural scale from inside-out. In EAEA16 Conference Proceedings. Ching, F. D. K. (2015). Architecture: Form, space, and order (4th ed.). Wiley. Dornburg, J. (2000). Arte e arquitetura: Novas afinidades. Editorial Gustavo Gili. Bachelard, G. (2005). A poética do espaço. Martins Fontes. Campo Baeza, A. (2018). A ideia construída. Caleidoscópio. Fonatti, F. (1988). Princípios elementares de la forma en arquitectura. Gustavo Gili. Sola-Morales, I. de. (2002). Territórios. Gustavo Gili. Távora, F. (2008). Da organização do espaço. FAUP. Zumthor, P. (2005). Pensar a arquitectura. Gustavo Gili.
- Architecture
- 367
- 512
- Project II
- ISMAT367-512
- 1
- Bachelor; Master Degree
- 10
- 0
- 12
- Não
- Português
- EN
- M1: Theoretical-practical classes M2: Practical project development classes M3: Collective critique sessions M4: Guided independent work M5: Tutoring and individual supervision
- Mandatory
- By the end of the semester, students should achieve the following learning outcomes: O1: Respond autonomously and with well-founded reasoning to the design challenges proposed, developing a coherent design concept. O2: Integrate sensory concerns into the design process, articulating spatial composition, formal expression, and scale. O3: Critically address architectural issues in a broad sense, relating the design exercise to wider disciplinary questions. O4: Demonstrate mastery of basic representation tools, using them appropriately for the communication of the design project.
- DAAD - Department of Architecture, Arts and Design
- S1: Conception of the design idea Identification and formulation of the idea Critical reading and interpretation Architectural references S2: Design and exploration of the brief Analysis and organisation Relationship between brief/use/user S3: Composition and spatial organisation Principles of architectural composition (solid/void, rhythm, proportion, balance) Spatial organisation/exploration of the idea Interior/exterior S4: Scale and proportion Human scale/built space Basic proportion, modulation and dimensioning Perception of scale through drawings/models and reference elements S5: Representation of the project Sketches/collages/diagrams/schemes - instruments of thought and exploration Models - instruments of thought, exploration and final representation Technical drawing - rigorous communication of the proposal S6: Communication of the project Presentation panels Models and portfolio Short reflective texts on the design idea Oral presentation and critical argumentation of the proposal
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
Exercício 1
11-03-2026
30%
Exercício 2
17-06-2026
60%
Assiduidade e Participação
-----
10%
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 second-semester Design Studio has as its main objective the consolidation of students' competencies in spatial design and in the development of their own design process, making a decisive contribution to the formation of a solid architectural mindset.
- Details
- Category: Discipline
- Rehabilitation of Buildings and Sites
- 6641
- 24490
- Fundamentals of Conservation and Restoration
- ISMAT6641-24490
- 1
- 5
- 0
- 12
- Não
- Português
- Semestral
- Details
- Category: Discipline
- Cowpertwait, P. & Metcalfe, A. (2009). Introductory time series with R . New York: Springer. Maindonald, J. & Braun, W. J. (2010). Data analysis and graphics using R: an example-based approach. (3rd ed.). United Kingdom: Cambridge University Press. Tabachnick, B. & Fidell, L. (2012) Using multivariate statistics . (6ª ed.) Boston: Pearson Education. Tufféry, S. (2011). Data mining and statistics for decision making . United Kingdom: John Wiley & Sons Ltd.
- Business Management
- 490
- 22680
- Prediction Mathematical Models
- ISMAT490-22680
- 3
- 5
- 0
- 12
- Não
- Português
- Active, problem-solving-oriented methodologies (PBL) are used for all content.
- Mandatory
- At the end of this Curricular Unit, students should be able to: LO1: Identify appropriate techniques for making data-based predictions; LO2: Create, manipulate and reduce the dimensionality of data; LO3: Apply cluster analysis techniques; LO4: Develop and compare predictive models of regression and classification; LO5: Model time series and use the models for predictive purposes; LO6: Use softwares (R and jamovi) for model development and forecasting; LO7: Critically analyze the predictions obtained, taking into account the context of the problems.
- S1: Introduction to data-based forecasting models S2: Pre-processing and data dimensionality reduction Collection and manipulation of data Principal components and factor analysis Reliability and validity of scales S3: Cluster analysis Hierarchical methods of cluster analysis Non-hierarchical methods of cluster analysis S4: Predictive models of classification and regression Linear and logistic regression Classification and regression trees Comparison of performance of predictive models S5: Time Series Notation and nomenclature Trend and seasonality Moving averages and exponential smoothing Identification, estimation, diagnosis and prediction with ARIMA and SARIMA models S6: Business Management applications using data analysis softwares (R and jamovi).
Descrição
Data limite
Ponderação
Teste de avaliação
04-12-2025
40%
Trabalho de grupo
08-01-2026
40%
Fichas no Moodle
30-11-2025
20%
- Semestral
- The increasing amount of data available to organizations and its importance for making decisions based on evidence, make it essential to master statistical methods, as well as computational resources that allow them to be implemented. This Curricular Unit (UC) addresses several statistical methods, which allow analyzing dependency and interdependence relationships between economic, environmental, social, marketing variables, among others, and developing predictive models. There are frequent situations in which decision-making depends on the analysis of the evolution of sets of observations made over time (time series), which is why methods of analyzing time series are also addressed in this UC.
- Details
- Category: Discipline
- Ryza, Sandy et al. (2017). Advanced Analytics with Spark: Patterns for Learning from Data at Scale. O'Reilly Media. Ofer Mendelevitch, O., Stella, C. & Eadline, D. (2016). Practical Data Science with Hadoop and Spark: Designing and Building Effective Analytics at Scale. Addison-Wesley. Li, Kuan-Ching et al. (2015). Big Data: Algorithms, Analytics, and Applications. Chapman and Hall/CRC.
- Data Science
- 6321
- 23091
- Big Data Processing
- ISMAT6321-23091
- 3
- 6
- 0
- 12
- Não
- Português
- The teaching methodology includes the expository method (TM1) to present the contents, the demonstrative method (TM2) to illustrate its application to practical cases and the active method (TM3) to solve classroom exercises, with the use of a computer. The assessment is made by continuous assessment or written exam. The continuous assessment consists of two written tests with a weight of 30% each and a group work (40%).
- Mandatory
- LO1: Know the technologies for processing large data sets; LO2: Apply techniques and algorithms to extract information and develop models from large amounts of data. LO3: Develop recommendation systems
- S1: Programming for large scale S2: Data stream analysis S3: Machine learning for large scale S4: Analysis of hyperlinks S5: Recommendation systems
As componentes de avaliação são as seguintes:
Descrição
Data limite
Ponderação
Teste de avaliação 1
A definir
30%
Teste de avaliação 2
A definir
30%
Trabalho prático
A definir
40%
- Semestral
- The primary objective of the Big Data Processing course is to introduce students to the technologies, techniques, and algorithms used to process and analyze large volumes of data. In a context where organizations generate and collect data on a massive scale, mastering methods capable of transforming this data into useful information, actionable knowledge, and predictive models is essential. This course covers fundamental topics such as large-scale programming, data stream analysis, machine learning in large-scale environments, link analysis, and the development of recommendation systems.
- Details
- Category: Discipline
- KOSTOF, Spiro - A History of Architecture: Settings and Rituals . Oxford: oxford University Press, 1995. NORBERG-SCHULTZ, Christian - Arquitectura Occidental . Barcelona: Gustavo Gili, 2000. ROTH, Leland M - Understanding Architecture: Its Elements, History and Meanings . Abingdon Routledge, 2018 LLERA, Ranón Rodriguez - Breve História da Arquitectura, Lisboa, Editorial Estampa, 2006 MOFFET, Marian, FAZIO, Michael, WODEHOUSE, Lawrence, A World History of Architecture, Singapura, Laurence King Publishing, 2003
- Architecture
- 367
- 11374
- Architecture History III
- ISMAT367-11374
- 2
- Bachelor; Master Degree
- 4
- 0
- 12
- Não
- Português
- EN
- Each theme to be developed must be framed in the intellectual and cultural conjuncture, in general, and, in the artistic one, in particular. Drawing will be used insofar as it provides a better understanding of the architectural object and is a fundamental instrument in the formulation of its synthesis. There will also be use of written language in the form of descriptive synthesis and training in the observation of the architectural object. The specific vocabulary of each moment in history is thought of as a means of relating the architectural object with the respective construction methods, materials, meanings, etc. Abstracting from language and other specific constraints of each historical moment to relate the object under analysis with other contemporaries is also proposed. Students are called to participate in all classes either through more direct answers to concrete questions or through reflections that emerge from the ongoing discourse.
- Mandatory
- Understanding the practical and theoretical architectural panorama of the Renaissance and Classicism as an attitude contrary to medieval barbarism, without, however, ignoring the precious plastic and constructive contribution of the Romanesque and Gothic styles. Focus students on understanding the evolutionary process of architecture and consequently its presence in current architectural practices and theory. Understanding the History and Theory of Architecture in the broader cultural context throughout History. Understanding the relationship between theoretical and technical/technological propositions. Understanding of the past and how it can be instrumental in thinking about the new problems that will arise in Architecture in the present and in the future. Understanding of History as an instrumental discipline in thinking or projecting in Architecture.
- DAAD - Department of Architecture, Arts and Design
- 1. Italian Renaissance 1.1 The discovery of Perspective and its design 1.2. The reinterpretation of the classic models of Antiquity 2. Mannerism 2.1. The Reformation and the Counter-Reformation 2.2.Mannerism as a language "in the manner of" and of slow transition to the Baroque 2.3. Jesuit architecture 3. Baroque 3.1. italian baroque 3.2. Central European Baroque, in particular French and Germanic. Anglo-Saxon Baroque. 3.2.1 Rococo 3.2.1 Rococo in Central Europe 4. Neoclassical 4.1. Neoclassical in Continental Europe 4.2. Anglo-Saxon Neoclassical
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
18-12-2025
40%
Portfolio
13-11-2025
30%
Assiduidade e participação em aula - avaliação contínua
30%
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 will address as themes the various manifestations of Renaissance architecture, and its consequences in Mannerism up to Baroque and Rococo. It will also address the passage to the neoclassical as a result of the Enlightenment, but above all the tiredness of the Baroque-Rococo. Like the other History of Architecture disciplines, it aims, beyond its scope, to constitute itself as a conceptual and instrumental basis for project disciplines. Understanding architecture in history will be fundamental, both to formulate new proposals and to intervene on what has already been built. This UC also intends to be a contribution for the student to look at architecture through the human and poetic.
