English

Category: Discipline
  • Bruce, A. & Love, S. (2023). Presentation Essentials. New York: McGraw-Hill.  Evans, V, Dooley, J. & White, R. (2019). Career Paths - Human Resources. Newbury, UK: Express Publishing. Gordon Smith, D. (2007). English for Telephoning. Oxford: OUP. Grussendorf, M. (2007). English for Presentations. Oxford: OUP. Mascull, B. (2017). Business Vocabulary in Use. Intermediate. 3rd ed. Cambridge: CUP. Pledger, P. (2007). English for Human Resources. Oxford: OUP. Sandford, G. (2011). Cambridge English for Human Resources. Cambridge: CUP.  
  • Accounting and Management
  • 3564
  • 18343
  • English
  • IPLUSO3564-18343
  • 1
  • 5
  • 0
  • 4
  • Não
  • Português
  • Almost constant use of communicative activities to the detriment of lecture by the teacher, research and sharing of information the topics individually or in group, use of an interdisciplinary approach to the topics, flipped classroom methodology, feedforward processes. 
  • Mandatory
  • The main competencies to acquire/develop are: - The ability to communicate in English clearly, adequately and fluently, on topics pertaining to the world of human resources and talent management in organisations, using the appropriate register and terminology; - The ability to read and write short texts on human resources management and related topics; - The ability to interact with others politely and effectively in social and professional situations; - The ability to initiate and interact on the telephone, using suitable language; - The ability to make effective professional presentations in English, in a well-structured way, using suitable language; - The ability to discuss topics pertaining to their profession as well as general interest current topics
  • Fluency in English – revision of structures, identification of common errors. HRM topics:  Skills and competences; Leadership and management; Recruitment and selection; Motivation and job satisfaction (reward management); Cross-cultural management. Functional English: making, accepting and refusing requests; asking for and stating opinions (among others); speaking on the phone; making presentations.

  • 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 escrito

    7/01/26

    40%

    Apresentação individual

    15/01/26

    30%

    Assiduidade e participação

    semestre

    30%

     

     

    Adicionalmente poderão ser fornecidas 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 elaboração dos trabalhos a apresentar.
    A avaliação é contínua, pressupõe a presença e participação nas aulas, e todos os elementos da avaliação são obrigatórios . Falta a um dos momentos de avaliação implica reprovação, com a possibilidade de ida a exame de recurso. O exame tem duas componentes - uma componente escrita (60% da nota final) e uma componente oral (40% da nota final). 

     
  • Semestral
  • The CU of English aims to: - Foster students' command of vocabulary, language skills and fluency in English, enhancing their confidence and ability to communicate purposefully - Develop students' effective and idiomatic oral and written expression, using suitable vocabulary and language skills, namely in the areas of organizations, human resources management and related topics - Practice professional communication in English, in contexts pertaining to organisations, in particular making professional presentations and telephoning - Foster students’ awareness and critical thinking skills, particularly in (but not limited to) their chosen professional field.

Data Science Foundations

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
  • _

Databases

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.

Corporate Finance in the Digital Age III

Category: Discipline
  • Accounting and Finance
  • 7157
  • 27486
  • Corporate Finance in the Digital Age III
  • IPLUSO7157-27486
  • 2
  • 6
  • 0
  • 4
  • Não
  • Português
  • Semestral

Quantitative Methods

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.
  1. Electronics and Instrumentation in IMR
  2. Complementary Diagnostic Examinations I
  3. Tourism Marketing 
  4. Art and Identity

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