- Details
- Category: Discipline
- Não
- Databases are at the heart of modern commercial application development. In addition, their use extends to many other environments and domains where large amounts of data must be stored for efficient update, retrieval, and analysis. This course provides an introduction to fundamental principles, methodologies for effective database design, and to the SQL language. The course will be driven by a set of practice activities, conducted along the semester, that will allow the students to acquire the required skills.
- Semestral
AVALIAÇÃO
Descrição
Data limite
Ponderação
Trabalhos práticos e participação nas aulas
Final das aulas do semestre
60%
Testes de avaliação
Final das aulas do semestre
40%
Exames (prático + teórico)
Final da época de exames
100%
- 1. Introduction to Databases and DBMS. What are DB and why are they essential. Difference between structured vs. unstructured data. Traditional file systems vs. database management systems (DBMS).. Overview of database types (Relacional, NoSQL). Introduction to Database Management Systems (DBMS). 2. Relational Model & Database Design Data models. Tables, Rows and Columns. Constraints, Primary Keys, Foreign Keys. Relationships in a Database. Introduction to Entity-Relationship (ER) Diagrams. Normalization concepts. 3. SQL Language What it is and why it's used. Data Definition (CREATE, ALTER, DROP). Data Manipulation (INSERT, UPDATE, DELETE). Basic Queries: (SELECT, WHERE, ORDER BY). Advanced Queries (JOIN, GROUP BY, aggregate funciotns, sub-queries and nested queries) Concurrency (COMMIT e ROLLBACK) Data Integrity (Constraints) Security (GRANT e REVOKE) 5. Database Backup and Recovery Strategies. Backups (Physical and Logical) and Data Recovery.
- At the end of this course, students will be able to: 1. Understand DBMS systems architecture and components 2. Undestand the relational model approach to data management. 3. Model Entity-Relationship diagrams for a database 4. Formulate queries using the SQL Language 5. Apply different normal forms to design a database 6. Identify suitable Indices for effective storage and retrieval of data. 7. Undestand how access control is performed in a DBMS.
- Mandatory
- Use of problem-based learning methodology, w hich allows the student to acquire knowledge, at the same time that carrying out the set of procedures for solving problems allows them to develop skills and competences. This methodology promotes learning as part of the activity developed to solve the problem.
- Português
- Garcia-Molina, H., Jeffrey David Ullman, & Widom, J. (2014). Database systems: the complete book. Pearson, Cop. Damas, Luís – SQL - Structured Query Language, 14ª Edição atualizada (2020). FCA (2020). ISBN13: 978-972-722-829-4
- 4
- 0
- 4
- 1
- IPLUSO6382-23552
- Data Communication Bases
- 23552
- 6382
- Computer Applications for Data Science
- Details
- Category: Discipline
- Não
- The course "Introduction to Operating Systems" aims to provide a solid foundation on the functioning and management of operating systems, covering areas such as process management, memory, storage, and file systems. This course is essential for understanding the interaction between hardware and software, as well as for developing skills in system administration, software development, and cybersecurity. Its relevance is reinforced by the versatility of the knowledge acquired, which serves as a foundation for advanced subjects and for professional performance in areas such as software engineering, network administration, and system monitoring. This course prepares students to face contemporary technological challenges, offering a critical and technical perspective on system efficiency and robustness.
- Semestral
Descrição
Data limite
Ponderação
Trabalhos práticos
ultima semana de aulas
50%
Testes práticos
ultima semana de aulas
50%
Exame de recurso Época de recurso
100%
Cada avaliação tem uma nota minima de 8 Valores. A média final dos trabalhos e testes práticos terá de ser no minimo 10 valores.
- Introduction to Operating Systems: Definition, functions, and types. Structure and Architecture: Kernel and hardware-software interaction. Process Management: Processes, threads, scheduling, and synchronization. Memory Management: Physical and virtual memory, paging, and segmentation. File Systems: Structure, types, operations, and permissions. Device and I/O Management: Controllers, buffers, and DMA. Storage: Hierarchy, disks, SSDs, and RAID. Security: Policies, access control, and vulnerabilities. Virtualization: Virtual machines, hypervisors, and containers. Mobile Operating Systems: Differences and resource management.
- The learning objectives of the "Introduction to Operating Systems" course are to provide students with knowledge of the fundamental principles of operating systems, covering areas such as process management, memory, storage devices, and file systems. Students will develop the ability to analyze and solve problems related to the administration and configuration of operating systems, as well as to interpret system logs and optimize system performance. This course also aims to equip students with the skills to efficiently administer and monitor operating systems, apply security concepts, and adapt to different platforms and environments such as Windows, Linux, and others. As a result, students will be prepared to face the challenges of the job market, with a technical and critical understanding of the architecture, operation, and security of operating systems.
- Mandatory
- The course combines slide presentations with practical work, such as operating system installations, to integrate theory and practice. The slide presentations facilitate the understanding of theoretical concepts, while the practical tasks allow students to apply this knowledge in real-world scenarios, such as the installation and configuration of operating systems (Windows, Linux, etc.). This practical approach promotes the development of essential technical skills and problem-solving abilities, ensuring an active and interactive learning experience.
- Português
- Silberschatz, A., Galvin, P. B., & Gagne, G. (2020). Operating system concepts (10th ed.). Wiley. ISBN 978-1-119-32091-3 Tanenbaum, A. S., & Bos, H. (2015). Modern operating systems (4th ed.). Pearson. ISBN 978-0-13-359162-0 Stallings, W. (2018). Operating systems: Internals and design principles (9th ed.). Pearson. ISBN 978-0-13-467095-9
- 4
- 0
- 4
- 1
- IPLUSO6382-13127
- Introduction to Operating Systems
- 13127
- 6382
- Computer Applications for Data Science
- Details
- Category: Discipline
- Não
- The Course Unit of Object-Oriented Programming (OOP) aims to provide students with solid knowledge of the programming paradigm that underpins most current programming languages and software development technologies. Its scope lies in introducing and deepening the fundamental concepts of object orientation, fostering the ability to apply these principles in the development of robust, scalable, and reusable applications. The unit also seeks to stimulate logical and abstract reasoning skills, preparing students to solve complex problems in diverse contexts through the practical application of modeling and implementation techniques in Java. The relevance of this unit stems from the fact that OOP constitutes the essential conceptual and practical foundation for progression into more advanced areas of software engineering and development.
- Semestral
Descrição
Data limite
Ponderação
Entrega, Apresentação e Defesa do Projeto
20-01-2026
65%
Entrega do Portefólio Individual
20-01-2026
35%
Exame de Recurso
-
100%
A avaliação contínua inclui a realização, individualmente ou em pequenos grupos, de um projeto que materializa a aplicação dos conceitos da POO, representando 65% da nota final, e a elaboração de um portefólio individual, no qual cada estudante reflete de forma crítica sobre as aprendizagens realizadas, documenta exercícios desenvolvidos e avalia a sua evolução ao longo do semestre, correspondendo a 35% da nota final. Esta distribuição assegura um equilíbrio entre o desempenho técnico e a capacidade reflexiva, garantindo uma avaliação integral e formativa do processo de aprendizagem. Em alternativa à avaliação contínua, os estudantes que não obtenham aprovação podem realizar um exame escrito de recurso, com um peso de 100% da nota final.
- Introduction to the Object-Oriented Programming (OOP) paradigm What is OOP and Benefits of OOP Concepts used in OOP (methods, fields, classes, objects, etc.); connection with algorithmics may be addressed again. Objects and classes in OOP; Definition of classes Creation of objects; Constructors Inheritance What inheritance is in OOP Extension of classes Method overriding through the superclass Polymorphism; Method overloading Dynamic methods in OOP Encapsulation Access modifiers Getters and setters in OOP Abstraction Abstract classes; Interfaces Relevant topics in OOP Exceptions and their handling File systems (I/O) Inner classes and static members Structures and code organization Organization and structure of code and their importance
- At the end of the course unit, the student should be able to: Understand the fundamental principles of Object-Oriented Programming. Define classes, objects, and methods in Java, correctly applying constructors. Apply the concepts of encapsulation, inheritance, polymorphism, and abstraction to concrete problems. Develop solutions using interfaces, abstract classes, and method overloading and overriding mechanisms. Implement exception handling, input/output operations, and modular code organization. Work collaboratively in a team in the development of software solutions. Present and defend developed solutions, providing well-founded arguments. Critically reflect on the process of learning and software development, producing appropriate technical documentation.
- Mandatory
- The course unit adopts active teaching and learning methodologies, privileging the articulation between theory and practice. Project-Based Learning (PBL) constitutes the structuring axis of the process, promoting autonomy and the resolution of real problems, which ensures greater motivation and engagement. In addition, the completion of practical exercises and the resolution of cases in class, individually and/or collaboratively, allows for the immediate application of the concepts presented. Collaborative work and peer assessment foster discussion, critical reflection, and the sharing of different perspectives, developing social and communication skills that are fundamental in professional contexts. Throughout the entire process, formative assessment, with continuous feedback from the lecturer, ensures that students can identify and overcome difficulties, progressively consolidating their knowledge and competences.
- Português
- Schildt, H. (2022). Java: The Complete Reference. McGraw-Hill Education Coelho, P. (2016). Programação em Java - Curso Completo. 5a Edição Atualizada. FCA.ISBN 9789727228409
- 4
- 0
- 4
- 1
- IPLUSO6382-11144
- Object-Oriented Programming
- 11144
- 6382
- Computer Applications for Data Science
- Details
- Category: Discipline
- Não
- Many programming projects involve solving complex computational problems, for which simplistic or naive solutions may not be efficient enough. The focus of this course is on how to design good algorithms, and how to analyze their correctness and efficiency. This is among the most basic aspects of good programming which has progressively become a major concern. This is therefore a particularly relevant CU for the the studies’ cycle.
- Semestral
Descrição Data Ponderação Teste de avaliação (A definir com os alunos) 40% Trabalhos práticos (A definir com os alunos)
60% A avaliação final baseia-se numa componente prática, baseada em trabalhos práticos, e, e numa componente teórica baseada num teste escrito sobre os diferentes tópicos abordados. A componente prática terá um peso de 60% e a componente teórica terá um peso de 40%, na nota final. A nota mínima de ambas as componentes será de 8 valores.
Os alunos poderão ainda ser avaliados por exame de recurso, este valerá 100% da nota final.
- CP1: Complexity, classes, typical functions and algorithm analisys; CP2: Complexity and recursivity (set of recursive problems); CP3: Sorting and selection algorithms; CP4: Sorting algorithms: Insertion Sort, Selection Sort, Merge Sort and Quicksort; CP5: Compare the complexity of sorting algorithms (Quicksort programming); CP6: Abstract data types: Stack and Queue; CP7: Circular arrays, simple lists and linked lists; CP8: Implementing Queue and List (programming using arrays and lists); CP9: Using Dictionaries and Sets; CP10: Binary Trees; CP11: Progrmming binary trees; CP12: Basic notions of graphs.
- The students that successfully finish this curricular unit will be able to: OA1. Know, understand and use fundamental algorithms and data structures; OA2: Analyze e design recursive algorithms; OA3. Analyze the correctness, complexity and performance of simple algorithms; OA4. Make a reasoned choice of the best suited data structures to each problem and apply them to its resolution; OA5. Design linked data structures and algorithms for it's manipulation
- Mandatory
- Use of ecercise-based learning methodology through which students are encouraged to autonomously develop solutions for problems that are posed to them, and that address most of the topics taught.
- Português
- Cormen, Thomas H. - Algorithms Unlocked. Cambridge, Massachusetts: MIT Press, 2013. Tamassia, Roberto, Goldwasser, Michael H., Goodrich, Michael T. - Data Structures and Algorithms in Python. First Edition. USA: Wiley, 2013
- 4
- 0
- 5
- 1
- IPLUSO6382-18752
- Algorithms and Data Structures
- 18752
- 6382
- Computer Applications for Data Science
- Details
- Category: Discipline
- Não
- _
- Semestral
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...
- _
- _
- Mandatory
- _
- Português
- Hastie, T., Tibshirani, R., & Friedman, J. (2009). The elements of statistical learning: Data mining, inference, and prediction (2nd ed.). Springer
- 4
- 0
- 4
- 1
- IPLUSO6382-23084
- Data Science Foundations
- 23084
- 6382
- Computer Applications for Data Science
