Seminars - Tourism and Hospitality Management

Category: Discipline
  • Tourism Management
  • 6029
  • 21640
  • Seminars - Tourism and Hospitality Management
  • ISMAT6029-21640
  • 3
  • 5
  • 0
  • 12
  • Não
  • Português
  • Semestral

The Public Service Employment Contract

Category: Discipline
  • Labor and Social Security Law
  • 6852
  • 25582
  • The Public Service Employment Contract
  • ISMAT6852-25582
  • 1
  • 5
  • 1163
  • 12
  • Não
  • Português
  • Optional
  • Semestral

Business Project

Category: Discipline
  • Business Management
  • 490
  • 10552
  • Business Project
  • ISMAT490-10552
  • 3
  • 12
  • 0
  • 12
  • Não
  • Português
  • Semestral

Decision Support Systems

Category: Discipline
  • Harrison, M. (2016) Pandas Library: Python Tools for Data Munging, Data Analysis, and Visualization. Treading on Python Series. Hastie, T.; Tibshirani, R.; Friedman, J. (2009). The Elements of Statistical Learning Data Mining, Inference, and Prediction, New York: Springer McKinney, W. (2018) Python for Data Analysis: Data Wrangling with Pandas, Numpy, and Python. USA: O’Reilly.  Santos, M. Y., Ramos I. (2017). Business Intelligence – Da Informação ao Conhecimento (3.ª ed.). Lisboa: FCA Editora.  
  • Data Science
  • 6321
  • 21902
  • Decision Support Systems
  • ISMAT6321-21902
  • 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 and without the use of a computer. The assessment is made by continuous assessment or written exam. The continuous assessment consists of one group work. 
  • Mandatory
  • LO1. Understand the concepts of Business Intelligence, Analytics, and Decision Support. LO2. Be able to analyze and map business processes in dimensional modeling. LO3. Understand the architecture for implementing Data Warehousing solutions. LO4. Understand the phases of the knowledge discovery process in databases. LO5. Develop ways of information visualization, including dashboards. LO6. Distinguish and apply data analysis techniques for exploratory, explanatory, or predictive purposes. LO7. Address business questions through the application of Descriptive and Inferential Statistics techniques. LO8. Apply Machine Learning techniques and explore how to use them in Decision Support Systems. LO9. Distinguish situations where clustering, regression, and classification techniques are applicable. LO10. Utilize Python for data acquisition, preparation, visualization, and analysis.  
  • S1. Overview of Decision Support Systems, Business Intelligence, and Analytics Business Intelligence Indicators Analytics Data Warehousing Online Analytical Processing   S2. Knowledge Discovery in Databases Phases of the process CRISP-DM Methodology   S3. Information Visualization ETL (Extract, Transform and Load) Tools Business Reporting, Visual Analytics, and Dashboards   S4. Statistical Data Analysis Descriptive Statistics Inferential Statistics   S5. Machine Learning in Decision Making Machine Learning and its Use in Decision Support Systems Supervised and Unsupervised Learning Machine Learning Applications in Decision Making: Clustering, Regression, and Classification   S6. Python for Decision Support Systems
  • Avaliação:

    Projeto entregue em duas fases: TP1 (50%) + TP2 (50%)   

    Datas dos momentos de avaliação:

    Entrega da 1ª fase do projeto - a indicar

    Entrega da 2ª fase do projeto - a indicar

    Apresentação do projeto - a indicar

     

     
  • Semestral
  • The ability to develop decision support systems is highly valued in the job market because it helps organizations make more informed and effective decisions, optimizing processes and resources, reducing risks, and creating competitive advantages. This makes professionals with these skills essential in an increasingly data-driven world. In this course, we cover the fundamentals and explore the capabilities of Python for acquiring, organizing, manipulating, visualizing, and analyzing data. The emphasis is on acquiring and integrating data from various sources, preparing data for analysis, creating informative visualizations, and conducting statistical analyses to describe situations, investigate associations, identify patterns, and develop predictive models.

Tax Law II

Category: Discipline
  • Law
  • 530
  • 2237
  • Tax Law II
  • ISMAT530-2237
  • 2
  • 5
  • 0
  • 12
  • Não
  • Português
  • Semestral
  1. Business Plan and Business Simulation in Tourism
  2. Option II
  3. Completion of course work
  4. Ethics and Data Security

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