The program consists of 2 semesters and a half of teaching component and 1 semester and a half for the preparation of the dissertation.
In the 1st year, students have courses from each of the scientific areas of the master (Programming Sciences and Technologies, Information Systems, Multimedia, Artificial Intelligence and Security) and can choose from different specializations. In the 2nd year, a large part of the workload will be for the preparation of the dissertation, and there are also, in the 1st semester, some compulsory and specialization courses.
Expected duration and workload
4 semesters, for a total of 120 ECTS. The course is planned for a full-time occupation. Students who intend to take the course alongside other.
occupations are recommended to consider the possibility of part-time enrollment.
Programme Structure for 2024/2025
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2nd Year
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Faculty
Objectives
After completing this course unit the student should be able to:
LO1. To know the technical, social and business forces that drive architectural choices.
LO2. To identify the main characteristics of a quality model for software architectures.
LO3. To describe an architecture using an adequate description language.
LO4. To recognize the major architectural styles of existing software systems.
LO5. To propose architectural alternatives for a problem and discuss their adequacy.
Program
PC1. What Is Software Architecture and why it is Important
PC2 Understanding Quality Attributes (e.g. Availability, Interoperability, Modifiability, Performance, Testability)
PC3. Architectural Tactics and Patterns
PC4. Quality Attribute Modeling and Analysis
PC5. Architecture in Agile Projects
PC6. Architecture and Requirements
PC7. Designing an Architecture
PC8. Documenting Software Architectures
PC9. Architecture, Implementation, and Testing
PC10. Architecture Reconstruction and Conformance
PC11. Architecture Evaluation
PC12. Architecture and Software Product Lines
Evaluation process
The practical nature of this curricular unit and the need for knowledge assessment to be carried out essentially through the ability of students to apply knowledge in the conception, design, implementation, validation, verification, deployment, maintenance and evolution of a software project, leads to the choice of a project-based evaluation method.
In the 1st season or normal season, evaluation throughout the semester, with no obligation of minimum attendance, with 3 evaluation moments of the group project:
- Presentation of progress mid-semester weighting 20% of the final grade;
- Final project report weighting 15% and software delivered weighting 35% of the final grade;
- Final presentation weighting 10% and discussion weighting 10% of the final grade.
The evaluation is based on the performance and individual contribution of each member of the group.
Or evaluation at the end of the semester (1st season), by individual project with 2 evaluation moments:
- Project report weighting 20% and software delivered weighting 45% of the final grade;
- Presentation of the work weighting 10% and discussion weighting 15% of the final grade.
In the 2nd season, grade improvement or special season (under the terms of the RGACC), assessment by individual project, available to students who request it:
- Project report weighting 20% of the final grade;
- Software delivered weighting 45% of the final grade;
- Presentation of the work weighting 10% of the final grade;
- Discussion of the work weighting 15% of the final grade.
All assessment periods include an assessment component carried out on the eLearning platform, with a weight of 10% (2 out of 20) in the final grade.
All assessment components, in all assessment periods, have a minimum score of 9.5 (out of 20).
Bibliography
Mandatory Bibliography
Title: Gamma, E., Helm, R., Johnson, R., & Vlissides, J. (1994). Design patterns. Boston, MA: Addison Wesley.
Fowler, M. (2012). Patterns of Enterprise Application Architecture. Addison-Wesley Educational.
Bass, L., Kazman, R., & Clements, P. (2021). Software Architecture in Practice. Addison-Wesley Educational.
Authors:
Reference: null
Year:
Optional Bibliography
Title: Selected readings and tutorials made available in the eLearning platform throughout the semester.
Richardson, C. (2019). Microservice patterns. New York, NY: Manning Publications.
Richards, M., & Ford, N. (2020). Fundamentals of software architecture. Sebastopol, CA: O’Reilly Media.
Authors:
Reference: null
Year:
Faculty
Elsa Alexandra Cabral da Rocha Cardoso
Objectives
LO1: Research user needs and the implications of modality and social conduct for interaction and experience.
LO2: Analyse multimodal interaction, groups of users, their communications, activities and contexts of use with respect to rich media.
LO3: Design input modalities, output media and interactive content to appeal to an audience.
LO4: Create and reflect upon critical design practice.
LO5: Understand the fundamental principles of data visualization for an effective communication.
LO6: Design analytic interfaces for business intelligence systems.
LO7: Compare and criticise different analytic interfaces.
LO8: Implement novel human-computer interactions adapted to different contexts.
LO9: To know how to analyse and quantify interface usability and user experience.
Program
PC1: Understanding Contexts of interaction in human-computer interfaces
User Experience, Engagement and Communication
Analysis of users? needs
PC2: Designing User Experience (In Context)
Participatory Design
Designing Mobile Experiences and intelligent Environments
Designing for Multiple Channels
Designing for Participation (online communities and social computing)
Creative use of storyboarding
PC3: Challenges of visualization or information in human-computer interfaces.
Applied to a wide variety of contexts for communication.
Applied to Business Intelligence and decision support systems
PC4: Fundamental principles of data visualization
PC5: Design of analytic interfaces for decision support:
Reporting
Dashboards
PC6: Crucial concepts of storytelling
PC7: Prototyping of human-computer interfaces
PC8: Evaluating Usability and User Experience:
formative evaluation;
evaluating mobile interaction;
usability heuristics.
Evaluation process
The student has two assessment methods: assessment throughout the semester and assessment by exam (for 100% of the grade). Given the practical nature of this course, we recommend the semester-long assessment method, which includes the development of a practical assignment.
Assessment throughout the semester consists of the following components:
- Project (in groups) (45%): includes the delivery of a report, final prototype and video.
- Presentation and discussion of the project (45%), with an individual grade.
- Data visualization exercise (in groups): 10%
Eligibility criteria for evaluation throughout the semester: minimum class attendance of 60% (30% user experience and 30% data visualisation classes) .
Minimum mark of 10 in all components. The working groups have 3 to 4 members. Given the large number of students, it is not possible to carry out individual projects.
The project has two binding partial deliveries to continue to be assessed throughout the semester. The first delivery (typically in week 7) includes the initial version of the user research, with the definition of the questionnaires to be carried out with users. The second delivery (typically in week 11) includes the complete version of the user research, with the analysis of the data from the user questionnaires. Each group will receive informal and formative feedback to improve the quality of the final project. Those who fail to complete the two partial deliveries will be assessed by exam.
The orals for the presentation and discussion of the project and the data visualization exercise will be held via Zoom, on a date to be agreed with each group. The marks for the orals are individual and all members of the group must be present at the oral.
Alternatively, the student can be assessed by a final exam worth 100% of the grade, in the 1st period, 2nd period and special assessment period.
Bibliography
Mandatory Bibliography
Title: - Allen, J., Chudley,J. Smashing (2012) UX Design: Foundations for Designing Online User Experiences, Wiley
- Preece, J., Rogers, Y., and Sharp, H., (2007) - Interaction Design: Beyond HCI. Wiley
- Caddick, R, Cable, S. (2011) Communicating the user experience: a practical guide for useful UX documentation. Wiley
- Saffer, D. (2009) Designing for Interaction: Creating Innovative Applications and Devices. New Riders
- Norman, D. (2013) The Design of Everyday Things (revised and expanded edition). Basic Books
- Meirelles, I. (2013). Design for Information. Rockport Publishers.
- Nussbaumer Knaflic, C. (2015) Storytelling with data. Wiley
- Nussbaumer Knaflic, C. (2019) Storytelling with data: let’s practice! Wiley
- Wexler, S., Shaffer, J., and Cotgreave, A. (2017) The Big Book of Dashboards: Visualizing Your Data Using Real-World Business PCenarios. Wiley
- Cairo, A. (2016). The Truthful Art: Data, Charts, and Maps for Communication. New Riders.
Authors:
Reference: null
Year:
Optional Bibliography
Title: - ISO/IEC 9241-11. (1998). Ergonomic requirements for office work with visual display terminals (VDT) - Part 11: Guidance on usability. Geneva, Switzerland: International Organization for Standardization.
- ISO/IEC 9241-210. (2015). Ergonomics of human-system interaction - Part 210: Human-centred design for interactive systems. Geneva, Switzerland: International Organization for Standardization.
- Nielsen, J. (1993). Usability Engineering. Morgan Kaufmann.
- Shneiderman, B. (1992). Designing the user interface strategies for effective human-computer interaction. 2nd Ed. Massachusetts: Addison-Wesley.
- Shneiderman, B. (1996). The eyes have it: a task by data type taxonomy for information visualizations. In Proceedings of the 1996 IEEE Symposium on Visual Languages (pp. 336-343).
- Evergreen, S. (2016). Effective Data Visualization: The Right Chart for the Right Data. SAGE Publications Ltd.
- Lima, M. (2017) The Book of Circles: Visualizing Spheres of Knowledge. Princeton Architectural Press. New York.
- Ware, C. (2012). Information Visualization: Perception for Design (3rd ed.), Morgan Kaufmann
- Garret, J.J. (2011). The elements of user experience: user-centered design for the Web and beyond. 2nd Ed. Berkeley, CA: New Riders.
- Rogers, Y., Sharp, H., & Preece, J. (2013). Interaction design: beyond human-computer interaction. 3rd edition. John Wiley & Sons.
Authors:
Reference: null
Year:
Faculty
Objectives
The Information Systems Management (GSI) Curricular Unit (UC) aims to promote knowledge, planning, development and exploration of Information Systems, from different perspectives, allowing each student to have “their own path” in the program content . In this way, each student will have obtained a differentiated set of knowledge, supported by the Program and capable of supporting the learning objectives identified below.
Program
I. Management and Management of ISs in the Company
The. Manage the organization and manage Information Systems and Technologies (ITS)
B. Concerns of STI Managers
w. Impact of STIs on Organizations
II. Information Systems and Technologies Planning
The. STI Strategy in Organizations
B. Business Vision by STIs
w. Align STI strategy with Business strategy
III. Develop Information Systems and Technologies
The. Architecture Concept in ITS
B. Frameworks and Reference Models for STI
w. Information Management and Knowledge Management
IV. Explore Information Systems and Technologies
The. Project management
B. Telecommunications, the Internet and wireless technologies
w. IS security
Evaluation process
Continuous evaluation:
1. Group Work – 70% of the final grade
Classroom presentation 20% (min grade 9.5 val.)
Final Report – submission in Moodle 50% (min grade 9.5 val.)
2. Individual Work – 30% of the final grade
Chapter summary in research format 20% (min grade 9.5 val.)
Note: one submission per student (of one of the four chapters) – Moodle submission of support pdf
Intervention in the room per pitch of 5 minutes 10% (min. score 9.5 val.)
Note: one pitch per student – Moodle submission of support pdf
Rating by Exam:
Exam 1st Season, 2nd Season, and Special Season (alternative to the previous ones)
Written Test (50%) + Case Report (50%) – statement to be provided by the teacher and submitted in Moodle
Bibliography
Mandatory Bibliography
Title: Bach, S. O. (2001). A Gestão dos Sistemas de Informação, Centro Atlântico.
Laudon, K., & Laudon, J. (2021). Management Information Systems: managing the digital firm (17th Edition). Pearson Education.
Santos, A. J. R. (2008). Gestão Estratégica: conceitos, modelos e instrumentos, Escolar Editora.
Authors:
Reference: null
Year:
Optional Bibliography
Title: Elia, S., Giuffrida, M., Mariani, M. M., & Bresciani, S. (2021). Resources and digital export: An RBV perspective on the role of digital technologies and capabilities in cross-border e-commerce. Journal of Business Research, 132, 158?169. https://doi.org/10.1016/j.jbusres.2021.04.010
Saberi, S., Kouhizadeh, M., Sarkis, J., & Shen, L. (2019). Blockchain technology and its relationships to sustainable supply chain management. International Journal of Production Research, 57(7), 2117?2135. https://doi.org/10.1080/00207543.2018.1533261
Authors:
Reference: null
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Faculty
Objectives
At the end of the course the student should be able to:
OA1. Identify the main historical milestones of ML.
OA2. Know its relations with other scientific areas.
OA3. Enumerate and recognize some of its applications.
OA4. Know the characteristics of the main algorithms in the field of Machine Learning.
OA5. Know, and be able to explain, the main concepts of an algorithm that exemplifies: Supervised Learning (symbolic and sub-symbolic), Unsupervised Learning, Reinforcement Learning and Search Algorithms.
OA6. Explain in full detail one of the learning algorithms studied.
OA7. Implement a learning algorithm or use one in a non-trivial problem.
Program
CP1. Historical notes on Machine Learning. Relationship with other displines. Applications.
CP2. Machine Learning problems and approaches;
CP3. Unsupervised Learning;
CP4. Supervised Learning (symbolic and sub-symbolic);
CP5. Reinforcement Learning;
CP6. Search methods and Genetic/Evolutionary Algorithms;
CP7. Data pre-processing, results validation;
CP8. Speedup of ML algorithms;
CP9. ML algorithm implementation.
Evaluation process
Approval for this course can only be obtained through assessment throughout the semester; the exam modality is not considered.
Assessment elements:
- 4 practical exercises (10% each), including code and a report, in groups of 2 members during the academic period with an in-person discussion;
- 4 mini-tests (5% each) during the academic period;
- A project (40%) in groups of 2 members that includes a report (limited to 10 pages), code, and an oral presentation (approximately 10 minutes), to be conducted during any of the assessment periods — the project must be submitted up to one week before the chosen assessment period.
The special assessment period will consist of the project, done individually, to be submitted one week before the special period, and a written test that replaces the practical exercises and mini-tests. The weights of these assessment elements are the same as previously indicated.
Attendance is not used as a criterion for evaluation or failure.
Bibliography
Mandatory Bibliography
Title: Ethem Alpaydin, Introduction to Machine Learning, Fourth Edition, 2020, https://mitpress.mit.edu/9780262043793/introduction-to-machine-learning/
Authors:
Reference: null
Year:
Optional Bibliography
Title: - Tom Mitchell, Machine Learning, 1997, http://www.cs.cmu.edu/~tom/mlbook.html
- Simon Haykin, Neural Networks and Learning Machines, Third Edition, 2009, https://cours.etsmtl.ca/sys843/REFS/Books/ebook_Haykin09.pdf
- R. Duda and P. Hart, Pattern Classification and Scene Analysis., 1973, https://www.amazon.com/Pattern-Classification-Scene-Analysis-Richard/dp/0471223611
Authors:
Reference: null
Year:
Faculty
Objectives
At the end of the course, the student should be able to:
1. Be able to understand and determine the security environment in information systems;
2. Understand and define access control policies;
3. Understand and apply some security controls and standards;
4. Offer advice on information and network security;
5. Develop and apply security plans and policies;
6. Reviewing and advising on certain security operations;
7. Designing plans to guarantee business continuity and resilience;
8. Understand and explain the role of cryptography in information security;
9. Establish policies and procedures for managing security incidents;
10. Understand software development problems and their security aspects.
Program
1. introduction to information security
2. Legal, Regulatory, Ethical and Professional Aspects of Information Security
3. Information Security Planning
4. Information Security Risk Management
5. Security of the Organisation's Assets
6. Information Security Architecture and Engineering
7. Identity Management and Access Controls
8. Security Evaluation and Testing
9. Security in Applications and Software Development
Evaluation process
Assessment throughout the semester:
- Carrying out a set of group projects and activities (50%) throughout the semester.
- Two individual mid-term tests (50%) [minimum mark of 6 for each test]. The first test takes place in the middle of the semester and the other on the date of the first term.
Attendance at a minimum number of classes is not compulsory for the assessment throughout the semester.
Assessment by exam:
For students who opt for this process or for those who fail the assessment throughout the semester process, with 3 seasons under the terms of the RGACC.
Bibliography
Mandatory Bibliography
Title: Andress, J. (2014). The Basics of Information Security: Understanding the Fundamentals of InfoSec in Theory and Practice. Syngress.
Kim, D., Solomon, M. (2016). Fundamentals of Information Systems Security. Jones & Bartlett Learning.
Stallings, W., & Tahiliani, M. P. (2014). Cryptography and network security: principles and practice. London: Pearson.
Gordon, A. (Ed.). (2015). Official (isc) 2 Guide to the CISSP Cbk. CRC Press.
Stewart, J. M., Chapple, M., & Gibson, D. (2012). CISSP: Certified Information Systems Security Professional Study Guide. John Wiley & Sons.
Authors:
Reference: null
Year:
Optional Bibliography
Title: Conjunto de artigos, páginas web e textos que complementam a informação bibliográfica da unidade curricular, e que serão fornecidos pela equipa docente.
Anderson, R. J. (2010). Security engineering: a guide to building dependable distributed systems. John Wiley & Sons.
Whitman, M., & Mattord, H. (2013). Management of information security. Nelson Education.
Whitman, M., Mattord, H. (2017). Principles of Information Security. Course Technology.
Katz, J., & Lindell, Y. (2014). Introduction to modern cryptography. CRC press.
Buchmann, J. A., Karatsiolis, E., & Wiesmaier, A. (2013). Introduction to public key infrastructures. Springer Science & Business Media.
Zúquete, A. (2018). Segurança em redes informáticas. FCA-Editora de Informática.
Correia, M. P., & Sousa, P. J. (2015). Segurança no software. Lisboa: FCA.
Stuttard, D., & Pinto, M. (2011). The web application hacker's handbook: finding and exploiting security flaws. John Wiley & Sons.
Sullivan, B., & Liu, V. (2011). Web application security, a beginner's guide. McGraw-Hill Education Group.
Schneier, B. (2007). Applied cryptography: protocols, algorithms, and source code in C. john wiley & sons.
Authors:
Reference: null
Year:
Faculty
Objectives
OA1. Develop skills of inquiry and reflection on the social and ethical impact of computing, and evaluate possible ethical and technical responses to those questions.
OA2. To think critically on the impact of introducing a given technology or product in a given environment. Will this product or technology enhance or degrade quality of life? What will the impact be upon individuals, groups and organizations?
OA3. Identify values that guide the day-to-day activities of professional practices of computing and communication technologies, debating and becoming familiar with standards of good practice, codes of conduct and codes of ethics established by professional associations.
OA4. To learn or discuss approaches to ethical aligned design methods, which seek to align technologies with defined values and ethical principles that prioritize human well-being.
Program
1·Ethics, computing, and society: The specificity of ethical issues in ICTs; Human rights in the digital age.
2·The responsibility of engineers. Active and passive responsibility. The context of technological development.
3·Normative ethics: Values, norms and virtues; Utilitarianism, Kant, Virtue ethics; normative argumentation.
4·Applied computer ethics and policy gaps: Ethical decision making and case studies.
5·Privacy and data protection: The GDPR.
6·Intellectual and industrial property: Copyright, the legal protection of computer programs; patents.
7·Artificial Intelligence: ethical principles and the AI act.
Evaluation process
The evaluation in the 1st term is carried out throughout the semester or by exam.
The evaluation in the 2nd term is by exam only.
If the student opts for evaluation throughout the semester, it includes:
Group assignment: 60%
Individual written test: 38%
Attendance/participation: 2%
Both the group assignement and the written test have a minimum grade of 7 out of 20.
To obtain 100% in the attendance component, the student must attend at least 70% of the classes.
Bibliography
Mandatory Bibliography
Title: Ethics, Technology, and Engineering: An Introduction. Ibo van de Poel, Lamber Royakkers, Wiley-Blackwell, 2011.
Bynum, Terrell Ward, and Simon Rogerson, (2004), Computer Ethics and Professional Responsibility: Introductory Text and Readings. Oxford: Blackwell, 2004.
Cordeiro, A.B.N (2020). Direito da Proteção de Dados à luz do RGPD e da Lei n.º 58/2019, Edições Almedina.
Authors:
Reference: null
Year:
Optional Bibliography
Title: - Ética para engenheiros, Arménio Rego e Jorge Braga, 2017 (edição atualizada), Lidel Edições Técnicas.
- Reforma de 2018 das regras de proteção de dados da UE, Regulamentos e orientações da Comissão Europeia, https://ec.europa.eu/commission/priorities/justice-and-fundamental-rights/data-protection/2018-reform-eu-data-protection-rules_pt
- Regulamento Inteligência Artificial: Proposta de 2019 do regulamento do parlamento europeu e do conselho que estabelece regras harmonizadas em matéria de Inteligência Artificial e altera determinados atos legislativos da União, https://eur-lex.europa.eu/legal-content/PT/TXT/?uri=CELEX:52021PC0206
- A gift of fire : social, legal, and ethical issues for computing technology / Sara Baase, 2013, 4th ed.
- The Handbook on European data protection law, 2018 edition, http://fra.europa.eu/en/publication/2018/handbook-european-data-protection-law-2018-edition
- Floridi, Luciano, editor (2010). The Cambridge handbook of information and computer ethics. Cambridge University Press.
- Ethically Aligned Design, First Edition, Delivering ‘A Vision for Prioritizing Human Well-being with Autonomous and Intelligent Systems’, 2019, The IEEE Global Initiative on Ethics of Autonomous and Intelligent Systems
- Dignum, Virginila (2019). Responsible Artificial Intelligence, how to develop and use AI in a Responsible Way, Virginia Dignum, Springer.
- Smith, BC (1996). Limits of correctness in computers. In Computerization and controversy (2nd ed.), pp. 810-825, Academic Press, Inc. Orlando, FL, USA (C).
- Tavani, Hermani (2004). Ethics and Technology: Ethical Issues in Information and Communication Technology. New York: John Wiley & Sons.
- Saltz, J.S., Dewar, N. (2019). Data science ethical considerations: a systematic literature review and proposed project framework. Ethics Inf Technol 21.
- Outros textos ou artigos a indicar pelo docente ao longo do semestre.
Authors:
Reference: null
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Faculty
Objectives
O1. To understand basic ideas of management;
O2.To understand the historical approach of management;
O3.To understand the complexity of globalization;
O4.To understand the basic ideas of knowledge management.
O5.To understand the learning organization as knowledge discipline;
O6. To understand how important is the organizational culture to improve the organizational performance.
Program
1. Basic foundations of management
2. Pioneering ideas of management
3. Globalization phenomenon
4. Knowledge management
5. Organizational learning
6. Organizational culture
7. Knowledge management and innovation.
Evaluation process
OPTION 1:
Assessment throughout the term:
1.Involvement in class activities - 20%.
-Levels of attendance and punctuality.
-Participation in class.
-Answer of questions in class.
2. Test - 80%.
Passing grade is 10 points, with at least 7,50 points (out of 20) in the test.
OPTION 2:
End-of-term exam - 100%.
A positive evaluation means a grade of 10 or above (over 20).
Bibliography
Mandatory Bibliography
Title: Schein, E. H. (2004). Organizational culture and leadership. London: The Jossey-Bass Business.
Nonaka, I.; Takeuchi, H. (1995). The Knowledge-Creating Company: How Japanese Companies Create the Dynamics of Innovation. Oxford University Press.
Hofstede, G. (1991). Culture and Organizations: Software of the Mind. London: McGraw-Hill.
Fernandes, A. (2007). Tipologia da aprendizagem organizacional: Teorias e Práticas. Lisboa: Livros Horizonte.
Davenport, T.; Prusak, L. (1998). Working Knowledge. Cambridge, MA: Harvard Business School Press.
Chesbrough, H., (2003). Open Innovation - The New imperative for creating and profiting from technology. MA: Harvard Business School Press
Bartol, K. e Martin, D. (1998). Management (3ª Ed.). Boston, MA: McGraw-Hill.
Argyris, C.; Schon (1978). Organizational Learning: A Theory of Action Perspective. Reading: Addison-Wesley.
Authors:
Reference: null
Year:
Optional Bibliography
Title: Nonaka, Ikujiro, & Hirotaka Takeuchi. 1995. The Knowledge-Creating Company: How Japanese Companies Create the Dynamics of Innovation. New York, NY: Oxford University Press.
Hofstede, Geert. (2001) Culture's Consequences : Comparing Values, Behaviors, Institutions, and Organizations across Nations. 2nd ed. Thousand Oaks, CA: Sage Publications.
Iskandar, K., Jambar, M., Kosala, R. & Prabowo, H. (2017). Current Issue of Knowledge Management System for Future Research: A Systematic Literature Review. Procedia Computer Science 116 (2017) 68-80
Ferreira, M. P., Santos, J. C., Reis, N. & Marques, T., (2010) Gestão Empresarial. Lisboa: Editora LIDEL.
Donnely, J. (2000) Administração: Princípios de Gestão Empresarial. 10ª Ed., Lisboa: McGraw Hill.
Davenport, Thomas H., & Lawrence Prusak (1998) Working Knowledge: How Organizations Manage What They Know. Cambridge, MA: Harvard Business School Press.
workers . Boston, MA : Harvard Business School Press .
Davenport , T. (2005) Thinking for a living, how to get better performance and results from knowledge
Dalkir, K. (2011) Knowledge Management in Theory and Practice. Cambridge, Massachusetts: the MIT Press.
Authors:
Reference: null
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Faculty
Objectives
After completing this course unit the student should be able to:
LO1. Know the fundamentals of functional programming
LO2. Apply meta-programming mechanisms
LO3. Design APIs (application programming interfaces)
LO4. Develop reusable software
Program
PC1. Introduction to Kotlin programming language
PC2. Meta-programming and annotations
PC3. Design patterns for extensibility
PC4. Plugin-based systems
Evaluation process
Periodic assessment:
- In-class quizzes (20%)
- Mid-term project evaluation (20%), to present during the semester
- Project (60%), to deliver and defend during the exam season
It is compulsory to attend at least 50% of the scheduled lectures and lab classes.
Project is the only form of evaluation, it is not possible to be evaluated through an exam. Evaluation in Época Especial requires delivering and defending the Project, with the requirement that its development should have been supervised during the semester classes.
Bibliography
Mandatory Bibliography
Title: André L. Santos, Livro digital de apoio (Kotlin, padrões de desenho), 2021.
Authors:
Reference: null
Year:
Optional Bibliography
Title: Erich Gamma, Richard Helm, Ralph Johnson, John Vlissides. Design Patterns. Elements of Reusable Object-Oriented Software, Addison-Wesley, 1995.
Joshua Bloch, Effective Java (3ª edição), 2017.
Dmitry Jemerov and Svetlana Isakova, Kotlin in Action, Manning, 2017.
David Farley, Modern Software Engineering: Doing What Works to Build Better Software Faster, Addison-Wesley, 2021.
Authors:
Reference: null
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Objectives
Program
Evaluation process
Bibliography
Mandatory Bibliography
Optional Bibliography
Objectives
Program
Evaluation process
Bibliography
Mandatory Bibliography
Optional Bibliography
Faculty
Objectives
LO1: Know how to systematically review relevant literature in a given technical-scientific field, including technical reports, standards, white papers or tutorials, to substantiate a problem and propose a solution.
LO2: Have selected one or more methodological approaches to achieve the project?s objectives, resulting in one or more technical-scientific contributions.
LO3: Know how to validate the artifacts that constitute the solution to the chosen problem and identify the corresponding validity threats.
OA4: Have learned how to prepare a master's project with quality, both in form and content.
OA5: To be able to present a technical-scientific problem and its motivation, to describe the project carried out to produce a solution for the same and to argue about the validity of the same.
Program
1st SEMESTER
PC1:Motivation to the problem and preliminary design of the solution
It involves the review of technical-scientific literature, guided by a protocol and its conclusions should be confirmed by domain experts. This step should clarify the problem relevance and the preliminary design of its solution
PC2:Training of writing and presentation skills for technical-scientific works
Encompasses participating in seminars, cooperative workshops (e.g. posters session), mini courses and attending public defenses
2nd SEMESTER
PC3: Implementation and validation of the proposed solution
The implementation implies the refinement of the design. Validation implies compliance with the steps of the adopted methodological approach(es) and comparing the proposed solution with the state of the art and/or their dissemination in technical-scientific venue(s) with peer review (e.g. tool demo session in conference)
PC4: Project?s report writing
Evaluation process
Semestre evaluation (1st semester) includes: dissertation proposal, introduction chapter, literature review, planning of the next stages and a presentation on the work in progress.
Bibliography
Mandatory Bibliography
Title: Artigos científicos distribuídos ao longo do semestre.
Como fazer Investigação, Dissertações, Teses e Relatórios (segundo Bolonha), Maria José Sousa & Cristina Sales Baptista, Pactor, Junho 2011
Winter, R. (2008). Design Science in Europe. European Journal of Information Systems, 17, 470-475.
Hevner, Alan R.; March, Salvatore T.; Park, Jinsoo; and Ram, Sudha. 2004. "Design Science in Information Systems Research," MIS Quarterly, (28: 1).
Chapter 2, Performance and Quality Management of HE programmes, Elsa Cardoso,PhD thesis, 2011.
Research Methods for Business Students, Mark Saunders, 5th Edition ISBN: 9780273716860
Authors:
Reference: null
Year:
Optional Bibliography
Title: slide:ology: The Art and Science of Creating Great Presentations, Nancy Duarte, O'Reilly Media, 2008
Presentation Zen: Simple Ideas on Presentation Design and Delivery, Garr Reynolds, New Riders Press, 2008
Authors:
Reference: null
Year:
Objectives
The student should:
OA1: Know and apply good-practices of bibliography-research
OA2: Define, plan and be able to communicate a task of adequate complexity and magnitude
OA3: Execute a project of adequate dimension for the work-hours dedicated to this course
Program
CP1: Introduction to research methods
CP2: Problem and research objectives formulation
CP3: Best-practices to develop a state-of-the-art
CP4: Writing and presentation
CP5: Execution of the project.
Evaluation process
The intermediate evaluation (1st semester) include:
Project proposal, introduction chapter, literature review (and / or comparison with existing applications), planning and a presentation of the work in progress.
Final evaluation considers: intermediate evaluation (A), technical / scientific quality of the work, based on the Project report (B), quality of the public presentation and discussion (C), with the following weights: Final grade = 0.3*A + 0.5*B + 0.2*C
Bibliography
Mandatory Bibliography
Title: Artigos científicos distribuídos ao longo do semestre.
Como fazer Investigação, Dissertações, Teses e Relatórios (segundo Bolonha), Maria José Sousa & Cristina Sales Baptista, Pactor, Junho 2011
Winter, R. (2008). Design Science in Europe. European Journal of Information Systems, 17, 470-475.
Hevner, Alan R.; March, Salvatore T.; Park, Jinsoo; and Ram, Sudha. 2004. "Design Science in Information Systems Research," MIS Quarterly, (28: 1).
Chapter 2, Performance and Quality Management of HE programmes, Elsa Cardoso,PhD thesis, 2011.
Research Methods for Business Students, Mark Saunders, 5th Edition ISBN: 9780273716860
Authors:
Reference: null
Year:
Optional Bibliography
Title: slide:ology: The Art and Science of Creating Great Presentations, Nancy Duarte, O'Reilly Media, 2008
Presentation Zen: Simple Ideas on Presentation Design and Delivery, Garr Reynolds, New Riders Press, 2008
Authors:
Reference: null
Year:
Objectives
Program
Evaluation process
Bibliography
Mandatory Bibliography
Optional Bibliography
Objectives
Program
Evaluation process
Bibliography
Mandatory Bibliography
Optional Bibliography
Objectives
Program
Evaluation process
Bibliography
Mandatory Bibliography
Optional Bibliography
Recommended optative
There are several specializations (thematic areas) available:
Interactive Applications and Games*
Computational Data Science*
Intelligent Systems*
Digital Transformation Technologies
Internet of Things
Those marked above (*) are considered to be the most suitable.
The 1st year curricular unit specializations most related to this master:
Interactive Applications and Games (daytime hours):
• Programming and Generation of Virtual Worlds
• Sound, Video and Digital Content Authoring
Computational Data Science (after-hours, shares the 1st year, 2nd semester UC with the specialization of Intelligent Systems):
• Algorithms for Big Data
• Computational Intelligence and Optimization
Intelligent Systems (mixed schedule, shares the 1st year, 2nd semester UC with the specialization of Computational Data Science):
• Algorithms for Big Data
• Computational Intelligence and Optimization
We remind you that the opening of a curricular unit and specializations is limited to the choice of the curricular unit by a sufficient number of students. It is also important to consider that there are limitations to the number of enrolled per curricular unit.
Objectives
- Systematizing and solidifying knowledge in the basic areas of Informatics (Software Engineering, Information Systems, Artificial Intelligence, Computer Networks and Multimedia);
- Specializing knowledge in a specific area choosing sets of optional subjects recommended for each specialization;
- Encouraging the student to create the non-technical skills necessary for most current works in the area (reading, writing, presenting, directing and planning);
- Enabling the creation of an interdisciplinary culture, either due to the frequency of courses from other areas, or contacting with students and teachers from the various Iscte schools.
During the programme, students should acquire technical knowledge in the fundamental areas of Computer Engineering, as well as particular knowledge in their specialization. Furthermore, they should be able to demonstrate specific skills for the work of research.
It is expected that graduates will be able to:
- perform tasks of management in multidisciplinary and multicultural teams;
- elaborate the specification, design and development of multimedia projects and products, guaranteeing management that integrates the expectations of customers and end-users;
- elaborate the specification, design and development of projects and products of mixed and increased reality, ensuring an integrated way the management of the expectations of customers and end-users;
- elaborate the specification, design and development of interactive projects applied to areas such as health, education, entertainment;
- develop mechanisms to control the quality of the project/product in successive stages of testing, as well as technical and functional validation;
- manage the skills needed to deal with and accommodate change and organizational response to this change, using ITs;
- specify, design and develop systems that contemplate knowledge and apply it in order to generate value in its business context, not to mention its important impact in the organizational culture in which it is embedded;
- identify, design and implement technical solutions for knowledge management needs.
- propose organization processes/models that contribute smoothly but effectively to the management of knowledge.
These learning objectives are pursued through the specific objectives of each curricular unit, as specified in the respective of CUF of each course, which should correspond directly with at least one of the learning objectives of the course. The degree of completion of these objectives is measured in each curricular unit according to their CUF, which details the methodologies of evaluation used for each specific objective.
Thesis / Final work
To complete the course programme the student must either produce a dissertation of a predominantly scientific nature or develop an innovative professional project. These will account for 42 ECTS credits.
The choice between a dissertation or a professional project is given to students so that he or she may choose an option that best fits his or her personal profile, either as a student and technical staff member aiming to pursue a 2nd cycle training, or as a professional making direct intervention in the areas covered in this course programme. In either case, the student must develop work that addresses not only the application of the concepts acquired during their training, but also the integration of knowledge and techniques in order to demonstrate innovative work in the field of computer science engineering.
The dissertation work can be developed in Iscte or in other universities/research units or companies, through the participation in research and development projects, usually done in collaboration with companies and research units. In particular, we highlight the Instituto de Telecomunicações (IT) and ISTAR-IUL.
There are many fields/areas where the student may participate in applied or fundamental research, such as Information Systems, Multimedia and Knowledge Management, Virtual and Augmented Reality, Human Machine Interaction, Image and Audio Coding, Digital Networks, Mobile Computing, Operating Systems, Open Source Systems, Computer Security, Grid Computing, Electronic Commerce, Systems Modeling and Computer Simulation (including simulation of complex socio-economic systems), Artificial Intelligence, Intelligent Agents and Systems, and Programming Science and Technology, among others.
Accreditations
More
Accredited
6 Years
30 Jul 2019
Accreditation DGES
Initial registry R/A-Ef 1057/2011 de 18-03-2011
Update registry R/A-Ef 1057/2011/AL01 de 18-03-2016 | R/A-Ef 1057/2011/AL02 de 21-02-2020