- Details
- Category: Discipline
- Safety at Work Engineering
- 1181
- 12981
- Materials and Construction Technology
- ISLA Gaia1181-12981
- 1
- 7
- 0
- 27
- Não
- Português
- Semestral
- Details
- Category: Discipline
- Frada, J.J.C. (2015). Guia Prático Multinormas. 14a ed. Lisboa: Edições Clinfontur. Marconi, M.A. & Lakatos, E.M. (2017). Fundamentos de Metodologia Científica. 8a ed. São Paulo: Editora Atlas. Marconi, M.A. & Lakatos, E.M. (2017). Metodologia do Trabalho Científico. 8a ed. São Paulo: Editora Atlas.
- Multimedia Product Development
- 2011
- 814
- Traineeship
- ISLA Gaia2011-814
- 2
- 30
- 0
- 27
- Sim
- Português
- Active methodologies
- Mandatory
- To know, understand, use and distinguish the basic procedures that the academic community uses in the collection, treatment, interpretation and dissemination of scientific information. Prepare an internship report.
- The formal rules for presenting a written work: cover; index; introduction, object, objectives, theoretical foundation, methodology, enunciation of subthemes in the chapters; theme development; conclusion; bibliography; quotes; pagination; appendices and attachments. The organization of the research: the formulation of a starting question; the literature review; definition of the problem; construction of the analysis model; the formulation of hypotheses. Data collection techniques: the different sources of information; Sampling; The questionnaire survey; the interview. Case analysis (participant observation, life stories and monograph). Analysis and interpretation of results: content analysis; analysis and treatment of quantitative data. Organization and writing of the internship report.
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
Ante-projecto de estágio
15%
Relatório de Estágio
85%
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 student, through the internship report, will prove the effective acquisition of the skills previously agreed with the host institution of the internship.
- Details
- Category: Discipline
- BUHALIS, D. e Laws, E. (2004) Tourism Distribution Channels, Thomson. COOPER, C.; Fletcher, J.; Wanhill, S.; Gilbert, D. e Shepherd, R. (2001) Turismo Princípios e Prática, Porto Alegre: Bookman. GOELDNER, C. e RITCHIE, B. (2006) Tourism, Principles, Practices, Philosophies, John Wiley and Son. NUNO ABRANJA; Ana Afonso Alcântara; Carla Norte Braga; Ana Patrícia Marques e Rira Nunes Gestão de Agências de Viagens e Turismo; Edição e Distribuição Lidel - edições técnicas, lda. SILVA, M.J. (2009), A Distribuição Turística e as Redes de Agências de Viagens em Portugal, TRAVELPORT (2016), Manual do Aluno Galileo Reservas.
- Tourism, Hotel and Restaurant Management
- 2046
- 15752
- Tourist Operations and Reservation Systems
- ISLA Gaia2046-15752
- 1
- 6
- 0
- 27
- Não
- Português
- practical lesson at a travel agency
- Mandatory
- The main objective of this course is to consolidate and develop knowledge about tour operators and travel agencies using case studies, texts and seminars. Students will have to recognize the functioning of an TO, TA, their legislation and how to prepare a tourist package. At the same time they will have practical classes on the reservation system
- 1) Intermediation in tourism History and evolution of travel agencies 2) Tourist Distribution - Tourism Distribution Structure - Travel agency functions - Legislation and procedures - Main, ancillary and mandatory activities 3) Travel Agency Technique and Practice - Accommodation - Packages and Operators - Other complementary services - Transport - Airport organization and operation - Check-in, luggage and lost and found 4) GDS - Main GDS and system functionalities - Decoding and reservation procedures - Online tools
. A avaliação é continua e é constituída de seguinte forma:
Descrição
Data limite
Ponderação
Teste
junho
50%
trabalho escrita e oral
junho
40%
Assiduidade e participação
10%
2. Avaliação Final
Os estudantes que não tenham sucesso na avaliação continua podem realizar exames nas épocas de avaliação definidas pela instituição.
- Semestral
- This Curricular Unit aims to provide students with the necessary information to understand and analyse the tourist distribution and its stakeholders, as well as preparing students for the techniques and practices of tourism operations, particularly travel agencies (Transport, Tour Operators, Complementary Services). Students will also be able to know the main GDS and its functionalities.
- Details
- Category: Discipline
- Business Management
- 1206
- 4580
- Taxation I
- ISLA Gaia1206-4580
- 2
- 6
- 0
- 27
- Não
- Português
- Semestral
- Details
- Category: Discipline
- Gama, J. et al. (2015). Extração de Conhecimento de Dados. Sílabo. Han, J., Kamber, M., & Pei, J. (2012). Data Mining: Concepts and Techniques. Morgan Kaufmann. Sharda, R., Delen, D., & Turban, E. (2017). Business Intelligence, Analytics, and Data Science: A Managerial Perspective (4th ed.). Pearson. Witten, I. H., Frank, E., Hall, M. A., & Pal, C. J. (2016). Data Mining: Practical Machine Learning Tools and Techniques. Morgan Kaufmann. Ward, M. O., Grinstein, G., & Keim, D. (2015). Interactive Data Visualization: Foundations, Techniques, and Applications. CRC Press. Data Analytics for Business Intelligence: A Multi¿Industry Approach — Sun, Zhaohao. Chapman & Hall / CRC Press. 1ª ed., Dezembro 2024. Trata de dados, analytics e inteligência aplicada a múltiplos setores. Microsoft Power BI Cookbook – Third Edition — Deckler, Greg & Powell, Brett. Packt Publishing. Julho 2024. Um guia prático de Power BI com técnicas actualizadas, ideal para modelação, DAX, visuais, integração com Python.
- Technology and Web Systems Engineering
- 6158
- 22491
- Data Knowledge Extraction
- ISLA Gaia6158-22491
- 1
- 6
- 0
- 27
- Não
- Português
- The applied methodology is an expository methodology, in the theoretical contents and laboratory practice in the contents of practical application. Problem-based learning.
- Mandatory
- At the end of the course, students should be able to: Understand the complete cycle of data extraction, transformation, and loading (ETL); Design and implement data warehouse models and OLAP cubes; Apply supervised learning algorithms (Logistic Regression, Random Forest) and unsupervised learning algorithms (K-Means) in Data Mining; Develop adaptive Business Intelligence models, integrating Python with Power BI; Interpret results and indicators from analysis and forecasting systems; Create interactive dashboards with DAX and smart visualisations; Assess the quality, consistency, and usefulness of the knowledge extracted.
- Data Mining – Processes and Procedures ETL Process (Extract, Transform & Load) Tools (Data Warehouses, OLAP, BI) - Data Warehouse – SQL Design - Integration Services - ETL process - Analysis Services with OLAP Cube Adaptive Business Intelligence - Business Intelligence Architecture Knowledge Discovery in Databases (Data Mining in Python) - Preparation and feature engineering - Classification (K-NN + Random Forest) - Clustering (K-Means) for segmentation - Association rules (market basket) - Power BI — Model, DAX, and Visuals (with integrated Python) - Data integration - DAX measures - Python in the Power BI
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 prático de grupo
35%
Teste de avaliação
24-01-2026
50%
Trabalhos realizados em sala de aula
15%
Haverá aulas de orientação tutorial remotas a acompanhar o desenvolvimento do trabalho prático.
A falta na apresentação de um dos momentos de avaliação condiciona a época de avaliação.
- Semestral
- The course aims to provide students with technical and analytical skills in the area of knowledge extraction and data transformation into useful information to support organizational decision-making.Students should understand and apply ETL, Data Warehousing, Business Intelligence, and Data Mining methodologies, exploring integration with Power BI and Python.
