- Details
- Category: Discipline
- Hastie, T., Tibshirani, R., & Friedman, J. (2009). The elements of statistical learning: Data mining, inference, and prediction (2nd ed.). Springer
- Computer Applications for Data Science
- 6382
- 23084
- Data Science Foundations
- IPLUSO6382-23084
- 1
- 4
- 0
- 4
- Não
- Português
- _
- Mandatory
- _
- _
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
Realização de exercícios/trabalhos em aula
várias datas
40%
Projecto final
Final do semestre
60%
(...
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
- _
- Details
- Category: Discipline
- Livros Damas, Luís (2017). SQL (14ª edição). FCA Date, C. J. (2003). An Introduction to Database Systems (8 edition). Boston: Pearson. Sites Recursos educativos do SQL - SQL Server | Microsoft Learn. (n.d.). Retrieved September 26, 2025, from https://learn.microsoft.com/pt-pt/sql/sql-server/educational-sql-resources?view=sql-server-ver17
- Information Systems Management
- 6030
- 1792
- Databases
- IPLUSO6030-1792
- 1
- 5
- 0
- 4
- Não
- Português
- Real world scenario simulation, using, whenever possible and applicable, integration with backend development with common used languages (e.g. PHP or Python) Use of modular case studies, allowing students to develop different yet complementary components, producing more comprehensive solutions
- Mandatory
- The objectives are to provide students with the theoretical and practical knowledge required to design, construct and analyze relational databases: namely, to obtain the following skills and competences: 1. Understand the reasons for implementing relational databases in the business world 2. Transpose from a requirements analysis to an entity-association model to design databases; 3. Apply the concepts of the relational database model, transforming the entity-association model into a physical data model; 4. Apply the techniques of normalization of tables; 5. Understand architecture and main components of Database Management Systems; 6. Use the base and advanced SQL language for creating, querying, and modification of databases;
- The syllabus of the curricular unit is: A) Theorical concepts Introduction Entity-Relationship Model The Relational Model Schema refinement: Normalisation and Transactions concept Architecture of DBMS and some Advanced SQL B) Lab component Introduction to SQL language; Instructions: DDL, DML (DQL) and DCL Operations: WHERE, ORDER BY, GROUP BY; Advanced concept in SQL: Error control Relational Operators: Union, Intersection, and Subtraction Cartesian Product (external) Complex queries (filter with aggregated values) and sub-queries Set DDL; CREATE statement; Data types; Nullity; ALTER and DROP statements INDICES and VIEWS Exception handling Procedures (SP) and Triggers Tables: Cursors
O apuramento de resultado final terá 2 componentes:
- Teórica, valendo 40%, composta por:
- 2 Testes - 30%
- Participação, assiduidade e pontualidade: 10%
- Prática, valendo 60%, composta por:
- Trabalhos a realizar em aula ou em casa : 10%
- Trabalhos intercalares, 2 entregas: 20%
- Trabalho final: 30%
A época de recurso terá 1 exame teórico (40%) e 1 trabalho único (60%) com conteúdos equivalentes à junção dos trabalhos intercalares e trabalho final de avaliação continua
As notas positivas de avaliação continua são retidas para recurso, só sendo requerido ao aluno repetir componentes para as quais não tenha obtido avaliação mínima.
Todas as provas, independentemente de tipo ou época têm nota miníma de 9,50 valores, arredondado à centéssima
- Semestral
- This curricular unit aims to present the importance of Data Management within a company, to guarantee both the daily operation of the business, as well as the support to the strategic decision. This unit will reinforce the framework for structuring and methodologies for creating databases.
- Details
- Category: Discipline
- Accounting and Finance
- 7157
- 27486
- Corporate Finance in the Digital Age III
- IPLUSO7157-27486
- 2
- 6
- 0
- 4
- Não
- Português
- Semestral
- Details
- Category: Discipline
- Artur F. Costa (2018). Alguns elementos sobre funções reais de variável real - Funções polinomiais e racionais. Universidade Lusófona (internal publishing). Guimarães, R. C. e Cabral, J. A. S. (2007). Estatística, Editora McGraw-Hill de Portugal, Alfragide. Hoaglin, D.C., Mosteller, F., Tukey, J.W. , Análise exploratória de dados Técnicas Robustas, Lisboa,Edições Salamandra, LDA. Maria Helena Pestana e João Nunes Gageiro (2014), Análise de Dados para Ciências Sociais A complementaridade do SPSS, 6.ª ed., Edições Sílabo, Lisboa , Portugal. Ribeiro, S. S., Pimenta, C., Pimenta, F., , Murteira, B., e Silva, J. A. (2023). Introdução à Estatística, 4ª ed. Apontamentos a fornecer durante as aulas / Handouts provided throughout the lessons by teachers
- Commercial Management
- 6814
- 4944
- Quantitative Methods
- IPLUSO6814-4944
- 1
- 6
- 0
- 4
- Não
- Português
- This course unit will use active learning methodologies, such as Flipped Classroom. Student engagement and timely access to learning materials will be key to supporting participation. The choice of tools is also relevant, with digital resources such as Excel and SPSS selected to match the topics covered. Connecting prior knowledge to practical exercises enhances learning, consolidates knowledge, and helps identify difficulties. Tutorial support sessions will play an essential role in fostering self-directed learning. Continuous assessment and two in-class tests will further help keep students motivated to achieve the intended learning outcomes.
- Mandatory
- It is intended that the student internalizes the variable and random nature of phenomena and the need to treat data and results taking this aspect into account. Thus, the objective is to ensure that the student acquires essential concepts about functions and their graphical representation and the ability to statistically treat different sets of data, being able to draw conclusions. At the same time, he or she must also associate probabilities with some everyday events, learn to apply some theoretical statistical distributions in various situations and also master statistical inference tools, hypothesis testing and variance analysis. In order to achieve the proposed objectives, the teaching sessions will consist of dynamic presentations of theoretical concepts alternating with the resolution of exercises in individual or group mode. The student will be motivated to use Excel and SPSS to achieve several of the previous objectives.
- Fundamentals of mathematics. 1.1. Fundamentals about Cartesian referentials and plane analytic geometry. 1.2. Fundamentals about functions and their graphical representation. 1.3. Interpretation of the graph of a function. 2. Statistics. 2.1. General concepts. 2.2. Sampling. 2.3. Descriptive statistics. 2.4. Correlation and Regression. 2.5. Introduction to probability theory and distributions. 2.6. Statistical Inference: point and interval estimation. 2.7. Hypothesis testing. 2.8. Variance analysis.
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
Trabalho de grupo (apresentação e defesa)
09-12-2025
40%
Teste de avaliação
20-01-2026
50%
Participação, atitude e assiduidade
10%
Nota: em nenhum momento de avaliação pode a nota ser inferior a 8 valores, numa escala de 0 a 20. A média de aprovação é de 10 valores. Os alunos que não obtiverem a nota mínima de aprovação (10 valores) poderão inscrever-se para realizar o exame, em que a ponderação é 100%, cobrindo toda a matéria.
- Semestral
- Review and consolidate basic mathematical knowledge, particularly regarding the graphical representation of functions; Understand the importance of statistical analysis of data and results; Master sampling techniques, identifying and avoiding common errors; Organize and process data sets, perform mathematical adjustments to bivariate data, and interpret the results; Understand the concept of probability and recognize key theoretical distributions; Apply statistical inference methods, including point and interval estimation, hypothesis testing, and analysis of variance; Use tools such as Excel and SPSS to apply the concepts covered.
- Details
- Category: Discipline
- Westbrook, C.; Roth, C. K. & Talbot, J. (2011). MRI in Practice. 5th Ed. Blackwell Science Westbrook, C. (2014). Handbook of MRI Technique. 4th Ed. Wiley-Blackwell Dendy, P. P. & Heaton, B. (1999). Physics for Diagnostic Radiology. 2nd Ed. Series in Medical Physics and Biomedical Engineering. Pope, J. A. (1999). Heinemann Advanced Science Medical Physics - Imaging. Heinemann Advanced Science: Physics Brown, B. H.; Smallwood, R. H.; Barber, D. C.; Lawford, P. V.; Rose, D. R. (1998). Medical Physics and Biomedical Engineering. CRC Press. Schmidt, G.; Greiner, L. & Nuernberg, D. (2014). Differential Diagnosis in Ultrasound Imaging by Guenter Schmidt. 2nd Ed. Thieme. Schmidt, G. (2005). Differential Diagnosis in Ultrasound Imaging: A Teaching Atlas. Thieme
- Medical Imaging and Radiotherapy
- 4097
- 19629
- Electronics and Instrumentation in IMR
- IPLUSO4097-19629
- 2
- 5
- 0
- 4
- Não
- Português
- The student may complete the course through continuous assessment or a final exam. The course is organized into 3 modules: I) Radiology, II) Radiotherapy, and III) Nuclear Medicine, each with equal weight in the final grade (1/3). In each module, the student is assessed in a Theoretical component (60%) and a Practical component (40%), and the minimum passing grade at each assessment point is 9.5 points.
- Mandatory
- The Medical Imaging and Radiotherapy Equipment discipline aims to apply the main concepts and fundamentals in understanding the systems involved. The main focus will be on the technical aspects of diagnosis and therapy, from a review of basic concepts to the design of systems. The development of Hospital Information Systems will be discussed and analyzed, integrating the student within the logic of supporting Information Communication Technologies and Medical Imaging that support activity in Nuclear Medicine, Radiotherapy and Radiology.
- 1. General Electronics 1.1 Analog Electronics 1.2 Digital Electronics 1.3 Instrumentation 2. Radiology Equipment 2.1 Radiography 2.2 Mammography 2.3 Computed Tomography 3. Nuclear Medicine Equipment 3.1 Gamma Camera: SPECT images 3.2 Basics on Positron Emission Tomography 3.3 Dose calibrator and Geiger-Muller counter 4. Radiotherapy Equipment 4.1 Simulator 4.2 Linear Accelerator 4.3 Tomotherapy, Gamma Knife and Cyberknife 5. Signal and image processing 6. Health Information Systems
Descrição
Data limite
Ponderação
Componente Teórica
1 teste de avaliação - módulo de radiologia (1/3 da nota final)
1 teste de avaliação - módulo de radioterapia (1/3 da nota final)
1 teste de avaliação - módulo de medicina nuclear (1/3 da nota final)
No final de cada módulo
60%
Componente Prática
1 teste de avaliação - módulo de radiologia (1/3 da nota final)
1 teste de avaliação - módulo de radioterapia (1/3 da nota final)
1 teste de avaliação - módulo de medicina nuclear (1/3 da nota final)
No final de cada módulo
40%
Adicionalmente, ou em substituição de qualquer um dos momentos de avaliação da componente PL, podem ser utilizados outros instrumentos de avaliação, como trabalhos/relatórios/apresentações orais, à consideração do respetivo docente.
- Semestral
- The Curricular Unit of Electronics and Instrumentation in Medical Imaging and Radiotherapy allows students to obtain the foundations of knowledge necessary to understand the structure and functioning of the main equipment used in clinical practice in Nuclear Medicine, Radiotherapy and Radiology services. The aim is to provide a theoretical approach to the principles that govern the functioning of medical equipment. Whenever possible, Practical classes should prioritize contact with clinical reality, namely through the promotion of classes in a clinical context and/or study visits to Nuclear Medicine, Radiotherapy and Radiology centers.
