- Details
- Category: Discipline
- Maroco, J. (2018). Análise Estatistica com o SPSS Statistics 7ª ed., Lisboa: Report Number. Pestana, M.H. & Gageiro, J. (2014) Análise de Dados para Ciências Sociais: A complementaridade do IBM_SPSS, 6ª edição. Edições Sílabo. Lisboa. Reis, E. (1996). Estati¿stica descritiva. Lisboa: Edições Sílabo. Ross, ( ) Introduction to Probability and Statistics for Engineers and Scientists
- Accounting and Management
- 3564
- 18870
- Data Analysis and Processing
- IPLUSO3564-18870
- 2
- 5
- 0
- 4
- Não
- Português
- The curricular unit includes: 1 - theoretical-practical classes explaining the program contents, complemented with the resolution and discussion of practical exercises. 2 - Practical classes in a computer laboratory that will allow learning and use of the software to carry out the statistical analyzes covered in the UC and the corresponding interpretation of the results. The final grade corresponds to a weighted average of two evaluation components: i) two moments of continuous assessment whose value will be 60% for tests and 30% for practical group work, ii) participation worth 10% of the final grade. The weighted average of the components, rounded to the nearest unit, must be at least 10 values ¿¿to be approved. At no point in the evaluation can the grade be lower than eight points. FINAL EXAM: If the student chooses not to be in continuous assessment, they will be subject to a final exam.
- Mandatory
- Students are expected to: A.Understand the basic concepts of descriptive statistics; B) have learnt the basic concepts of probability theory and random variables, and how to apply them correctly; C) master the most important theoretical distributions (discrete and continuous), in particular the Normal distribution, Binomial and t of "Student"; D) master basic concepts of sampling and sample distributions; E) know how to use point estimation and confidence intervals; F) be familiar with the SPSS statistical software.
- Program: 1. Descriptive statistics -Basic concepts (Variables, population and sample) - Frequency distributions. - Measures of central tendency and non-central - Measures of absolute and relative dispersion and measure of distribution. 2 - Probability theory. - Probability concepts. - Conditional probabilities. - Independent events. - Bayes Theorem. 3 - Random variables: Concept of random variables. - Probability and distribution functions. 4 - Distributions of discrete variables ( Binomial, Poisson¿) 5 - Distributions of continuous variables (Uniform, Exponential and Normal) 6. Central limit theorem 7 Correlation and Regression
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
21-11-2025
60%
Portfolio - trabalho de grupo
12-12-2025
30%
(participação)
10%
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
- Awaken in the student a sensitivity that leads in the future to realize when to perform statistical methods again; enable the student to critically analyze the statistical analysis results that will be presented without tracking their future professional activity
- Details
- Category: Discipline
- Duarte, C. e Esperança, J.P. (2014). Empreendedorismo e Planeamento Financeiro. 2ª edição. Edições Sílabo. Menezes, H.C. (1999). Princípios de Gestão Financeira. 7ª edição, Lisboa, Editorial Presença, Mota, A. G. & Custódio, C. (2012). Finanças da Empresa. 7.ª Edição, Bnomics Soares, J.O., Fernandes, A.V., Março, A.A. e Marques, J.P.P. (1999). Avaliação de Projectos de Investimento na Óptica Empresarial. Edições sílabo. Soares, I., Moreira, J., Pinho, C. e Couto, J. (2020). Decisões de Investimento – Análise Financeira de Projectos. 4ª edição. Rdições Sílabo.
- Information Systems Management
- 6030
- 18085
- Project and Investment Analysis
- IPLUSO6030-18085
- 2
- 5
- 0
- 4
- Não
- Português
- Expositional Methodology and Self-study Methodology: Knowledge acquisition will be measured through a test. Participative Methodology and Active Methodology: Skill development will be assessed through team work, and consists of a presentation and discussion of a case study
- Mandatory
- This CU aims to develop the student knowledge, skills and competences that are listed: 1. Know how to explain concepts of investment analysis; 2. Know how to make a business plan; 3. Describe a business model; 4. Describe sources of financing; 5. Know how to analyses the economic and financial situation of a company; 6. Know how to evaluate investment projects.
- 1. Introduction to Investment analysis: Concepts of; Investment, Project, Profitability, Cash Flow, Present Value Calculations: Interest rate and Discount cash flow 2. The Business Plan and its importance for the analysis and evaluation of the investment. 3. Investment analysis and evaluation 4. Sensitivity analysis 5. Conclusion and project evaluation 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
Teste de avaliação
05-12-2024
45%
Portfolio
9-01-2024
Data limite
45%
Participação, atitudes e assiduidade(...)
10%
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
- This UC aims to provide the necessary skills for understanding concepts and modeling investment projects in business, with regard to techniques for their construction, evaluation criteria, risk analysis and conclusions.
- Details
- Category: Discipline
- Dhar, V. (2013). Data science and prediction. Communications of the ACM, 56(12), 64-73. James, G., Witten, D., Hastie, T., & Tibshirani, R. (2013). An introduction to statistical learning. New York: Springer. McKinney, W. (2012). Python for data analysis. Sebastopol, CA: O'Reilly Media, Inc.
- Computer Applications for Data Science
- 6382
- 814
- Traineeship
- IPLUSO6382-814
- 2
- 30
- 0
- 4
- Sim
- Português
- Project-Based Learning (PBL): Students work on real challenges proposed by partner companies, promoting the direct application of knowledge and skills. Mentoring: Experienced professionals in the field of Data Science act as mentors, offering guidance, feedback and practical insights into the sector. Interactive Platforms: Use of online platforms that simulate real data analysis environments, allowing students to experiment and learn in a practical context. Peer Learning: Students are encouraged to teach and learn from each other, leveraging each other's different skills and perspectives.
- Mandatory
- Knowledge: Understand the real functioning and dynamics of an organization or company that uses Data Science in its daily operations. Familiarize yourself with the specific tools and platforms used in the professional environment. Skills: Practically apply the techniques and concepts learned throughout the course, adapting to the specific needs and challenges of the internship location. Develop communication skills to present findings and insights derived from data analysis. Skills: Work as a team and integrate into an organizational structure, respecting hierarchies, deadlines and guidelines. Demonstrate initiative, proactivity and adaptability, responding effectively to the challenges presented. Establish professional networks that can be valuable for future career opportunities.
- Introduction to the Professional Environment: Contextualization of the role of Data Science in the organization, main departments and stakeholders involved. Tools and Platforms: Deep dive into specific software and tools used in the company or institution, which may vary from those covered in the course. Project Management in Data Science: Life cycle of a project, definition of objectives, collection and processing of data, implementation and evaluation of solutions. Communication of Results: Preparation of reports, dashboards and presentations; storytelling techniques with data. Ethics and Privacy: Practical approach to ethical issues, legislation and best practices in data processing and analysis. Networking and Professional Development: Strategies for building and maintaining professional relationships, and tips for career advancement Note: There are fortnightly seminars to support the program and monitor students.
Descrição
Data limite
Ponderação
Relatório de estágio
12-01-2024
80%
Discussão
12-01-2024
20%
- Semestral
- The "Internship" curricular unit is intended to provide students with practical experience in professional environments related to Data Science. The field of action covers companies and organizations that apply data analysis in their operations, from technological startups to large corporations and research institutions. The area of ¿¿expertise involves the application of techniques and tools learned throughout the course, including exploratory analysis, modeling, visualization and data interpretation. The intervention domains vary, allowing students to specialize in specific niches, such as business intelligence, machine learning or predictive analysis. This UC is vital in the study cycle, as it connects theory and practice, facilitating students' transition to the job market and reinforcing the relevance and applicability of their acquired knowledge.
- Details
- Category: Discipline
- A designar, mediante a natureza dos trabalhos a desenvolver.
- Accounting and Management
- 3564
- 18260
- Traineeship
- IPLUSO3564-18260
- 2
- 30
- 0
- 4
- Sim
- Português
- n/a.
- Mandatory
- Develop technical-professional skills related to the course's CUs and acquire knowledge and skills in the face of the professional reality contact resulting from the internship. The Internship Report (ER), should describe the tasks developed during the internship period. The specific objectives are: - Application of theoretical and practical knowledge acquired during the academic training; - To facilitate the professional insertion of the future graduate in the labor market; - To rehearse practices adjusted to the needs of the labor market; - To evaluate the interest and profile of the trainee for the exercise of a profession and his/her availability for the execution of differentiated tasks, according to the areas concerned; - Strengthening the IES with the partners of the labor market.
- The program contents are described in the Regulation.
Descrição
Data limite
Ponderação
Relatório Final de Estágio
A agendar
75%
Apresentação Pública do Relatório e Defesa
A agendar
25%
(...)
- Semestral
- The Internship Report represents the final balance of a professional experience that allowed the trainee to acquire and/or strengthen skills. It is, therefore, a document organized in such a way as to make clear, for the Teacher who will evaluate the document. The Project aims to enable the student to test his/her abilities to carry out, on his/her own, research work.
- Details
- Category: Discipline
- CUNHA, Paulo Olavo, Direito Empresarial para Economistas e Gestores (3ª ed), Almedina, Coimbra, 2020 ANTUNES, José Engrácia, Direito do Consumo, Almedina, Coimbra, 2019 / Legislação indicada
- Marketing Management
- 6375
- 23517
- Commercial and Consumer Law
- IPLUSO6375-23517
- 1
- 6
- 0
- 4
- Não
- Português
- The teaching of a legal discipline to a MArketingManagement course requires a strong practical sense and a clear connection to the reality of the professional universe in question. Thus, in the context of the learning of the fundamental principles and rules already mentioned, the use of concrete examples facilitates the acquisition of the competences that constitute its transversal (as already mentioned) domain. Two written tests are carried out and attendance and participation (including papers oral presentation) are considered in the following ways: First test: 30% of final assessment Second test: 40% of final assessment Assiduity and participation: 30% of final assessment.
- Mandatory
- The UC Commercial and Consumer Law aims to provide students with knowledge and cross-sectional mastery of the framing and treatment of the main issues raised in the initial framework of the study of legal conformation of business management and its relationship with the market, as well as the fundamental principles and rules of a set of relevant diplomas in the framework of the regulation of economic activities and, in particular, trade, as well as in the sphere of consumer protection.
- 1. Economic Constitutional Law. 2. European Business Law 3. Commercial Companies Code. 4. Consumer Protection Law (and related legislation). 5. Advertising Code. 6. General Data Protection Regime. 7. E-commerce Legal Regime.
Participação em aula: 30%
Teste final: 70%
- Semestral
- The UC Commercial and Consumer Law is dedicated to the study, analysis and discussion of thematic / problematic of the main issues that arise in the context of the legal conformation of business management and its relationship with the market.
