- Details
- Category: Discipline
- Hair, J. F., Black, W. C., Babin, B. J., & Anderson, R. E. (2018). Multivariate Data Analysis (8th ed.). Cengage Learning. James, G., Witten, D., Hastie, T., & Tibshirani, R. (2013). An Introduction to Statistical Learning: with Applications in R. Springer. McKinney, W. (2017). Python for Data Analysis: Data Wrangling with Pandas, NumPy, and IPython (2nd ed.). O'Reilly Media.
- Computer Applications for Data Science
- 6382
- 23559
- Analysis and Treatment of Multivariate Data
- IPLUSO6382-23559
- 2
- 5
- 0
- 4
- Não
- Português
- Project-Based Learning (PBL): Promotes practical application, allowing students to work on real datasets, proposing and implementing solutions to concrete problems. Interactive Coding Platforms: Using tools such as Jupyter Notebooks or RStudio Cloud to facilitate experimentation and real-time data visualization. Peer-to-Peer Discussion Groups: Fostering the exchange of ideas and collaboration, allowing students to learn from each other and share different perspectives.
- Mandatory
- Knowledge: Students will acquire a deep understanding of the nature and complexity of multivariate data and the statistical techniques and algorithms used in their analysis. Skills: They will be able to perform exploratory analyzes of multivariate data, identifying patterns, correlations and anomalies. Additionally, they will develop capabilities to apply dimensionality reduction methods, such as PCA and t-SNE, and clustering and classification techniques. Skills: Students will be proficient in specific tools and software for processing multivariate data. They will also gain the ability to effectively communicate the results of their analyses, transforming complex data into actionable insights and data-driven solutions to real-world problems. Overall, they will be able to make informed decisions based on analysis of multivariate datasets, making a valuable contribution to any data science team.
- Introduction to Multivariate Data: Basic concepts, types and structures of multivariate data. Exploratory Data Analysis (AED): Multivariate data visualization, outlier detection and statistical description. Correlation and Causality: Differences, calculation methods and implications. Dimensionality Reduction: Techniques such as Principal Component Analysis (PCA) and t-SNE. Clustering and Segmentation: Algorithms such as K-means and DBSCAN. Multivariate Classification: Introduction to models such as Multinomial Logistic Regression and Support Vector Machines. Validation and Interpretation of Models: Evaluation methods, metrics and interpretation of results. Practical Applications: Case studies and projects in specific domains, using tools such as R, Python and their specific libraries.
Descrição
Data limite
Ponderação
Teste de avaliação
17-11-2025
30%
Projeto Final
19-01-2026
70%
- Semestral
- The Curricular Unit "Analysis and Processing of Multivariate Data" is an essential component of the professional technical course in Computer Applications for Data Sciences. Within the field of action, this course focuses on the study and manipulation of data sets with multiple variables, exploring the complexities and interrelationships between them. The area of ¿¿expertise encompasses advanced statistical techniques, machine learning algorithms and visualization methods for multivariate data. As for the intervention domain, it addresses both the underlying theory and practical application, using modern software and tools specific to the processing of multivariate data. The relevance of the UC in the study cycle is unquestionable, as understanding and processing multivariate data is a central pillar in data science, allowing students to extract deeper insights and develop more accurate predictive models from complex data sets.
- Details
- Category: Discipline
- Câmara, P. B.; Guerra, P. B. & Rodrigues, J. V. (2016). Humanator XXI Recursos Humanos e Sucesso Empresarial , Edições D. Quixote, 7ª Edição; Rego, A.; Cunha, M. P.; Gomes, J. F. S.; Cunha, R. C.; Cabral-Cardoso, C. & Marques, C. A. (2015). Manual de Gestão de Pessoas e do Capital Humano , Edições Sílabo, 3ª Edição; Sousa, M. J.; Duarte, P.; Sanches, P. G. & Gomes, J. (2006). Gestão de Recursos Humanos, métodos e práticas , Lídel Editora, 4ª Edição.
- Information Systems Management
- 6030
- 523
- Human Resources Management
- IPLUSO6030-523
- 2
- 5
- 0
- 4
- Não
- Português
- Students will work in groups to collect data from companies in one of the human resources areas. The goal is to help students understand how human resources concepts are applied in practice and to gain exposure to business life (small businesses).
- Mandatory
- LO1 - Describe the historical origins of the HR function and frame it within the organisational context. Define HRM and highlight its main objectives/challenges. LO2 - Describe the various activities/functions/responsibilities that may be related to the HR function. LO3 - Reflect on the issues of diversity, discrimination, and harassment in organisations. LO4 - Present the main Human Resources processes and techniques.
- PC1. Basic concepts and perspectives on HRM; PC2. Organisational climate and the importance of communication; PC3. Diversity, discrimination, and harassment; PC4. Recruitment and selection in organisations; PC5. Employee welcome, integration, and socialisation; PC6. Reward and compensation systems; PC7. Training; PC8. Performance evaluation; PC9. Time management and work organisation.
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
A agendar
50%
Trabalho de grupo (Escrito e Apresentação)
A agendar
30%
Participação e atividades nas aulas
20%
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...
Para os alunos com o estatuto de trabalhador-estudante ou outro estatuto semelhante, o docente pode solicitar um trabalho extra para complementar a avaliação de conhecimentos da UC.
- Semestral
- The Human Resource Management course syllabus covers the basic theoretical and practical foundations of Human Resource Management in organisations. Its relevance to the study cycle is due to the growing importance of Human Resources in creating competitive advantages for organisations.
- Details
- Category: Discipline
- Accounting and Finance
- 7157
- 22411
- Business English
- IPLUSO7157-22411
- 3
- 3
- 0
- 4
- Não
- Português
- Semestral
- Details
- Category: Discipline
- Commercial Management
- 6814
- 21221
- Product Management
- IPLUSO6814-21221
- 2
- 6
- 0
- 4
- Não
- Português
- Semestral
- Details
- Category: Discipline
- Halperin, E. C.; Wazer, D. E.: Perez, C. A. & Brady, L. W. (2013). Perez & Brady's Principles and Practice of Radiation Oncology. 6th Ed. USA: Lippincott Williams & Wilkins. Symonds, P.; Deehan, C.; Meredith, C. & Mills, J. (2012). Walter & Miller’s textbook of radiotherapy: radiation physics, therapy and oncology. 7th Ed.. UK: Churchill Livingstone Hoskin, P. (2006). Radiotherapy in Practice: External Beam Therapy. Oxford: Oxford University Press. Hoskin, P. (2012). External Beam Therapy (Radiotherapy in Practice). 2nd Ed. OUP Oxford. Levitt, S. H.; Purdy, J. A.; Perez, C. A. & Vijayakumar, S. (2006). Technical Basis of Radiation Therapy: Pratical Clinical Applications. 4th Ed. Berlin: Springer
- Medical Imaging and Radiotherapy
- 4097
- 19640
- Methodologies in Radiotherapy I
- IPLUSO4097-19640
- 2
- 6
- 0
- 4
- Não
- Português
- Classes will be taught using slides and videos. The contents will be transmitted in the expository form. Topics will be discussed among all students. Continuous assessment will involve the completion of two individual written tests. The minimum grade required in each of the frequencies is 9.0 values. The practical evaluation may include group work with presentation and discussion, written test or worksheet on the topics developed together with the evaluation of participation in practical classes. The minimum grade required in each of the evaluations is 9.0 values. Calculation of the final classification: arithmetic mean of the theoretical component - 50% and of the practical component - 50%. The classification of all assessment instruments is expressed on a scale of 0 to 20 values, and the weighted value of the classifications obtained must be equal to or greater than 9.5 values.
- Mandatory
- • Describe the theoretical foundation inherent to external beam radiotherapy techniques. • Apply treatment methods and techniques in external radiotherapy to different pathologies. • Apply patient positioning and immobilization procedures. • Identification of side effects. • Apply and adapt the communication style to the user.
- Techniques, procedures and control of the treatment, side effects and communication with the patient in the following pathologies: Tumors of the breast Prostate Tumors Gynecological tumors Tumors of head and neck Tumors of the central nervous system Radiotherapy with a palliative purpose 2. Emergency in Radiotherapy
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
Testes de avaliação da componente T
a definir
50%
Avaliação prática
a definir
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
- The Curricular Unit of Methodologies in Radiotherapy I will provide students with fundamental knowledge for the application of external radiotherapy techniques, namely in relation to the methods and techniques applicable in treatment in external radiotherapy for different pathologies.
