- Details
- Category: Discipline
- Pinto, J. K. (2019). Project Management: Achieving Competitive Advantage. London: Pearson. Kerzner, Harold (2017). Project Management: A Systems Approach to Planning, Scheduling, and Controlling. New Jersey: John Wiley & Sons.
- Data Science
- 6321
- 7428
- Project Management
- ISMAT6321-7428
- 2
- 5
- 0
- 12
- Não
- Português
- TM1. Theoretical exposition of the main contents of the Syllabus (S); TM2. Peer instruction; TM3. Analysis and discussion of teaching cases; TM4: Problem-based learning.
- Mandatory
- At the end of this course, students should be able to: LG1. Recognize the main project methodologies used in the market; LG2. Identify the basic steps of a project and its management needs; LG3. Understand the role of the project manager and other team members; LG4. Develop a logical project structure, considering issues related to: scope, risk, financing and budget, resource management, evaluation and control and implementation.
- S1 - Introduction to Project Management 1.1 - Overview on the main methodologies 1.2 - Considerations about the organizational context: strategy, structure and culture S2 - Project Selection and Portfolio Management 2.1 - Scope Management 2.2 - Risk Management 2.3 - Cost Estimation and Budgeting S3 - Project Scheduling 3.1 - Networks, Duration Estimation, and Critical Path 3.2 - Lagging, Crashing, and Activity Networks 3.3 - Agile e critical chain 3.4 - Evaluation and Control 3.5 - Closeout and termination S4 - Leadership and the Project Manager 4.1 - Team building, conflict and negotiation 4.2 - Resource management S5 - Project Proposal
Avaliação:
- Estudos de caso ao longo do curso (40%);
- Trabalhos em grupo: apresentações e trabalho final (40%);
- Participação ativa nas aulas (20%).
- Semestral
- The curricular unit Project Management belongs to the scientific area of Management and provides knowledge of the principles, methodologies and tools of project management. It develops skills to plan, execute, monitor and control projects, promoting teamwork and the efficient management of resources, time, costs and risks.
- Details
- Category: Discipline
- Law
- 530
- 217
- Political Economics
- ISMAT530-217
- 1
- 6
- 0
- 12
- Não
- Português
- Semestral
- Details
- Category: Discipline
- Tourism Management
- 6029
- 21638
- Innovation and Entrepreneurship in Tourism
- ISMAT6029-21638
- 1
- 5
- 0
- 12
- Não
- Português
- Semestral
- Details
- Category: Discipline
- Human Resources Management and Organisational Intervention
- 6349
- 23317
- Labour Law and Labour Relations
- ISMAT6349-23317
- 1
- 6
- 0
- 12
- Não
- Português
- Semestral
- Details
- Category: Discipline
- Carmo, H. & Ferreira, M. (1998). Metodologia da investigação: guia para auto-aprendizagem. Lisboa: Universidade Aberta. Carvalho, J.E. (2009). Metodologia do Trabalho Científico. (2ª ed.). Forte da Casa: Escolar Editora. Gil, A.C. (2010). Como elaborar projetos de pesquisa. (5ª ed.). São Paulo: Atlas. Lakatos, E.M. & Marconi, M.A. (2010). Fundamentos de metodologia científica. (7ª ed.). São Paulo: Atlas.
- Data Science
- 6321
- 7334
- Scientific Research Methodologies
- ISMAT6321-7334
- 2
- 5
- 0
- 12
- Não
- Português
- TM1. Theoretical exposition of the main contents of the Syllabus (S) TM2: Presentation of seminars by invited experts TM3. Research activities
- Mandatory
- LO1: Understand the basic concepts of scientific research; LO2: Knowing how to use processes, methodologies and practices associated with scientific research in Data Science; LO3: Develop the spirit of scientific criticism; LO4: Develop the capacity to produce scientific texts; LO5: Know the main scientific databases; LO6: Prepare the Final Course Work Project.
- S1. Research methods S2. Structure of a scientific work S3. Academic databases S4: Research topics in Data Science S5: Final Course Work Project
Avaliação:
- Apresentação de um seminário (30%)
- Projeto do Trabalho Final de Curso (70%)
- Semestral
- The curricular unit Scientific Research Methodologies belongs to the scientific area of Research Methodology and aims to develop skills to plan, conduct and communicate scientific research in Data Science. It addresses the different stages of the research process, promoting scientific rigor, critical thinking and the use of appropriate research methods.
