Accreditations
Programme Structure for 2025/2026
Curricular Courses | Credits | |
---|---|---|
Calculus
6.0 ECTS
|
Mandatory Courses | 6.0 |
Principles of Data Analysis
6.0 ECTS
|
Mandatory Courses | 6.0 |
Work, Organizations and Technology
6.0 ECTS
|
Mandatory Courses | 6.0 |
Electronic Circuit Analysis
6.0 ECTS
|
Mandatory Courses | 6.0 |
Electricity and Mechanics
6.0 ECTS
|
Mandatory Courses | 6.0 |
Introduction to Statistics
6.0 ECTS
|
Mandatory Courses | 6.0 |
Linear Algebra and Geometry
6.0 ECTS
|
Mandatory Courses | 6.0 |
Power Electronics
6.0 ECTS
|
Mandatory Courses | 6.0 |
Project Planning and Management
6.0 ECTS
|
Mandatory Courses | 6.0 |
Introduction to Design Thinking
2.0 ECTS
|
Transversal Skills | 2.0 |
Public Speaking with Drama Techniques
2.0 ECTS
|
Transversal Skills | 2.0 |
Academic Work with Artificial Intelligence
2.0 ECTS
|
Transversal Skills | 2.0 |
Microcontrollers
6.0 ECTS
|
Mandatory Courses | 6.0 |
Robotics and Advanced Automation
6.0 ECTS
|
Mandatory Courses | 6.0 |
Quality Control and Artificial Vision
6.0 ECTS
|
Mandatory Courses | 6.0 |
Entrepreneurship and Innovation I
6.0 ECTS
|
Mandatory Courses | 6.0 |
Manufacturing Management and Information Systems
6.0 ECTS
|
Mandatory Courses | 6.0 |
Programming Fundamentals
6.0 ECTS
|
Mandatory Courses | 6.0 |
Sensors Actuators and Signal Processing
6.0 ECTS
|
Mandatory Courses | 6.0 |
Entrepreneurship and Innovation II
6.0 ECTS
|
Mandatory Courses | 6.0 |
Instrumentation and Industrial Control
6.0 ECTS
|
Mandatory Courses | 6.0 |
Fundamentals of Automation
6.0 ECTS
|
Mandatory Courses | 6.0 |
Applied Project in Automation II
6.0 ECTS
|
Mandatory Courses | 6.0 |
Unsupervised Machine Learning
6.0 ECTS
|
Mandatory Courses | 6.0 |
Human-Machine Interaction and Simulation
6.0 ECTS
|
Mandatory Courses | 6.0 |
Technology, Economy and Society
6.0 ECTS
|
Mandatory Courses | 6.0 |
Industrial Networks and Supervision
6.0 ECTS
|
Mandatory Courses | 6.0 |
Applied Project in Automation I
6.0 ECTS
|
Mandatory Courses | 6.0 |
Calculus
By the end of this course unit, the student should be able to:
LO1: Understand and analyze real-variable functions, including polynomial, rational, trigonometric, and exponential functions.
LO2: Grasp and apply concepts of limits and continuity to solve problems involving indeterminate forms and asymptotic behavior.
LO3: Calculate and interpret derivatives and differentials, applying differentiation rules to solve problems involving rates of change.
LO4: Understand and apply definite and indefinite integrals, using integration techniques and exploring their applications.
LO5: Analyze sequences and series, understanding convergence criteria and applying them in mathematical contexts.
P1. Real Variable Functions:
1.1. Polynomial, rational, trigonometric, and exponential functions
1.2. Logarithmic and inverse trigonometric functions
1.3. Inverse and composite functions
1.4. Limits and indeterminate forms
1.5. Continuity
P2. Differential Calculus:
2.1. Rates of change
2.2. Derivative at a point and tangent line
2.3. Differentiation rules
2.4. Chain rule
2.5. Intervals of monotonicity and concavity of the graph
2.6. Taylor approximations
P3. Integral Calculus:
3.1. Definite integral, fundamental theorem of calculus, and primitives
3.2. Integration techniques
3.3. Applications of integration
3.4. Improper integrals and convergence
P4. Sequences and Series:
4.1. Sequences: monotonicity and convergence
4.2. Numerical series: sums and convergence criteria
Passing requires a grade of no less than 10 out of 20 in one of the following modalities:
- Assessment throughout the semester: 1 midterm mini-test (10%) + 1 group project of 3-4 members (20%) + Autonomous work (10%) + 1 final test on the first exam date (60%). A minimum grade of 8 out of 20 is required in both the final test and the average of other assessment moments throughout the semester.
- Assessment by exam (100%): Individual written test in any exam period.
- An oral assessment may be conducted after any assessment moment to validate the final grade.
Title: Stewart, James, Daniel K. Clegg, and Saleem Watson. Calculus. Cengage Learning, 2020.
Anton, Howard, Irl C. Bivens, and Stephen Davis. Calculus: early transcendentals. John Wiley & Sons, 2021.
Authors:
Reference:
Year:
Title: Campos Ferreira, J., Campos Ferreira, J. (2018) Introdução à Análise Matemática, Fundação Calouste Gulbenkian, 2018, null
Stewart, J., Stewart, J. (2013) Cálculo, Vol I, Cengage Learning, (7ª Ed.), 2013, null
Strang, G., Strang, G. (2007) Computational Science and Engineering, Wellesley-Cambridge Press, 2007, null
Solomon, Justin, Solomon, Justin (2015) Numerical Algorithms, CRC Press., 2015, null
Goldstein, L., Goldstein, L. (2011) Matemática Aplicada à Economia. Administração e Contabilidade, (12a edição) Editora Bookman., 2011, null
Authors:
Reference:
Year:
Principles of Data Analysis
After successfully completing the curricular unit, students should be able to:
OA1. Know and become familiar with different data formats.
OA2. Understand a complete data analysis cycle.
OA3. Know how to perform exploratory data analysis using R.
OA4. Know how to model a set of data.
OA5. Implement a data analysis solution to study a specific problem.
CP1. Introduction to Data Analysis
CP2. Introduction to R and RStudio
CP3. Knowledge of problems in data analysis, application examples
CP4. The complete cycle of data analysis
CP5. Data and data formats
CP6. Data preparation
CP7. Odds; descriptive statistics of data and exploratory data analysis
CP8. Data visualization
CP9. Modeling and machine learning of data models
CP10. Model evaluation methods
CP11. Reporting and publishing results
The assessment in the 'over the semester' format is based on two individual tests: a mid-term test and another at the end of the semester (20% each), and a group project (maximum of 3 students) with the preparation of two reports (20% each) and an oral presentation (20%) to be carried out by the group and this is graded individually.
A minimum attendance of at least 2/3 of the classes is required (students may miss 4 classes out of 12).
The Final Exam is a written, individual, closed-book exam covering all the material. Those who have not successfully completed the assessment throughout the semester, with an average grade higher than or equal to 10 (out of 20), take the final exam in period 1, 2 or special.
Title: Hadley Wickham, Mine Çetinkaya-Rundel, Garrett Grolemund, 'R for Data Science', 2nd Edition, O'Reilly Media, Inc. 2023.
Cole Nussbaumer Knaflic, 'Storytelling with data: a data visualization guide for business professionals', John Wiley & Sons, Inc., 2015.
Authors:
Reference: null
Year:
Title: Torgo, Luis. 'Data mining with R: learning with case studies' (2nd Edition), chapman and hall/CRC, 2016.
C. O'Neil, R. Schutt. 'Doing Data Science: Straight Talk from the Frontline', O'Reilly, 2013.
T. W. Miller, 'Marketing Data Science: Modeling Techniques in Predictive Analytics with R and Python?' O'Reilly, 2015.
Aggarwal, C. C. , 'Data mining: the textbook' (Vol. 1), Springer, 2015.
Han, J., Pei, J., & Tong, H. 'Data mining: concepts and techniques', Morgan Kaufmann, 2022.
P. Tattar, T. Ojeda, S. P. Murphy B. Bengfort, A. Dasgupta, 'Practical Data Science Cookbook', Second Edition, Packt Publishing, 2017.
Authors:
Reference: null
Year:
Work, Organizations and Technology
LO1: Understand the main theories, concepts, and issues related to Work, Organizations, and Technology;
LO2: Understand the main processes of the digital transition directly related to the world of work and its organizations;
LO3: Analyze the multiple social, economic, and political implications brought by the digital transition;
LO4: Explore cases, strategies, and application methods to understand the real impacts of the digital transition on professions, companies, and organizations.
PC1. Is work different today than it was in the past?
PC2. What rights and duties in the world of work?
PC3. How has theory looked at technology?
PC4. What digital technologies are changing work?
PC5. What future for work?
PC6. Is artificial intelligence really that intelligent?
PC7. Where does precariousness begin and end?
PC8. Who is to blame when the machine makes a mistake?
PC9. Do digital technologies change the relationship between unions and companies?
PC10. What digital transformation in Portugal?
Continuous assessment throughout the semester:
Each student will conduct a Flipped Classroom session, which represents 20% of the final grade.
Individual work accounting for 35% of the final grade.
Group work accounting for a total of 35% of the final grade (10% for the group presentation and 25% for the written work).
Attendance and participation in classes represent 10% of the final grade. A minimum attendance of no less than 2/3 of the classes is required.
Each assessment element must have a minimum grade of 8. The final average of the various elements must be equal to or greater than 9.5.
Examination evaluation (1st Period if chosen by the student, 2nd Period, and Special Period): in-person exam representing 100% of the final grade with a minimum grade of 9.5.
Title: Autor, David H., "Why Are There Still So Many Jobs? The History and Future of Workplace Automation.", 2015, Journal of Economic Perspectives, 29 (3): 3-30.
Benanav, A, Automation and the Future of Work, 2020, London: Verso
Boreham, P; Thompson, P; Parker, R; Hall, R, New Technology at Work, 2008, Londres: Routledge.
Crawford, C, The Atlas of AI. Power, Politics, and the Planetary Costs of Artificial Intelligence, 2021, Yale University Press.
Edgell, S., Gottfried, H., & Granter, E. (Eds.). (2015). The Sage Handbook of the sociology of work and employment.
Grunwald, A. (2018). Technology Assessment in Practice and Theory. London: Routledge.
Huws, U. (2019) Labour in Contemporary Capitalism, London, Palgrave.
OIT (2020), As plataformas digitais e o futuro do trabalho
Agrawal A, Gans J, Goldfarb A (2018), Prediction Machines, Boston, Massachusetts, Harvard Business Review Press.
Autor D (2022), The labour market impacts of technological change, Working Paper 30074, NBER Working Paper Series.
Authors:
Reference: null
Year:
Title: ✔ Autor D (2022), The labour market impacts of technological change, Working Paper 30074, NBER Working Paper Series.
✔ Braun J, Archer M, Reichberg G, Sorondo M (2021), Robotics, AI and Humanity, Springer.
✔ Cedefop (2022). Setting Europe on course for a human digital transition: new evidence from Cedefop’s second European skills and jobs survey, Publications Office of the European Union.
✔ Eurofound (2020), New forms of employment: 2020 update, Publications Office of the European Union.
✔ ILO (2018), The economics of artificial intelligence: Implications for the future of work, International Labour Office.
✔ ILO (2019), Work for a Brighter Future – Global Commission on the Future of Work. International Labour Office.
✔ Nowotny H (2021), “In AI we trust: how the Covid-19 Pandemic Pushes us Deeper into Digitalization”, Delanty G (ed.) (2021), Pandemics, Politics and Society, De Gruyter, 107-121.
✔ OECD (2019b), How’s Life in the Digital Age?, OECD Publishing.
✔ Wilkinson A, and Barry M (eds) (2021), The Future of Work and Employment, Edward Elgar.
✔ Zuboff S (2019), The Age of Surveillance Capitalism, PublicAffairs.
Authors:
Reference: null
Year:
Electronic Circuit Analysis
After successfully attending the curricular unit, students should be able to:
LO1: Components and laws
LO2: Analysis of electrical circuits
LO3: Circuits with DC Bridges and AmpOps
CP1: Basic notions of electrical components and circuits
CP1.1: Units and scales
CP1.2: Voltage and current sources
CP1.3: Ohm's Law
CP1.4: Kirchhoff's Laws
CP2: Analysis of electrical circuits
CP2.1: Linearity and overlap
CP2.2: Thevenin and Norton theorems
CP2.3. Maximum Power Transfer Theorem (MPTT)
CP3: Capacitors and coils
CP3.1: Capacitors
CP3.2: Coils
CP3.3: RLC Circuits
CP4: DC Bridges and Operational Amplifiers
CP4.1: AmpOps Basics
CP4.2: Linear operation
CP4.3: DC Circuits and Bridges
CP4.4: Circuits, DC Bridges and Operational Amplifiers
Assessment throughout the semester:
A1: Laboratory and Reports (30%)
A2: 1st Written Test (30%)
A3: 2nd Written Test (40%)
Minimum mark in Laboratory and Report: 8.5
Minimum mark in Written Tests: 8.5
(final average greater than or equal to 9.5)
The possibility of assessment throughout the semester is conditional on:
- Attendance at laboratory classes (100%) *,
- Attendance at lectures (50%),
- Attendance at theoretical-practical classes at least (50%).
*If laboratory absences are recorded for objective reasons, a way of making up the missed laboratory will be agreed with the teacher.
Assessment by exam:
Exam (100%) in the 1st, 2nd and special exam periods.
The exam will include, in addition to the content of the theoretical and practical classes, some content related to the laboratory work carried out.
Title: Electric Circuits, Global Edition: Global Edition, 11th Edition, by James W. Nilsson, Susan Riedel;
Schaum's Outline of Basic Circuit Analysis, Second Edition, by John O'Malley;
Manuel de Medeiros Silva, Introdução aos Circuitos Eléctricos e Electrónicos, 2ª Ed., Fundação Calouste Gulbenkian, 2001;
Hayt, Kemmerly, Durbin, "Engineering Circuit Analysis", 9th Edition, McGraw Hill, 2008;
Authors:
Reference: null
Year:
Title: J. David Irwin, Basic Engineering Circuit Analysis, 11ª Ed., Wiley, 2015;
Richard C. Dorf, James Svoboda, Introduction to Electric Circuits, 9ª Ed., Wiley, 2013;
James W. Nilsson, Susan A. Riedel, Introductory Circuits for Electrical and Computer Engineering, Prentice-Hall, 2002;
Vítor Meireles, Circuitos Eléctricos, Lidel, 2001;
John O'Malley, Análise de Circuitos, Colecção Schaum, McGraw-Hill, 1993;
Authors:
Reference: null
Year:
Electricity and Mechanics
LO1. Understand and Use Models and Units
Students should identify and apply physical models to solve problems related to measurement units and calculations in physics.
LO2. Analyze and Describe One-Dimensional and Two-Dimensional Motion
Students should understand and describe the motion of objects in one and two dimensions, using motion equations to solve kinematic problems.
LO3. Apply Newton’s Laws to Solve Real Problems
Students should use Newton’s Laws to analyze and solve dynamics problems, identifying the forces involved and applying these laws to determine the motion of bodies.
LO4. Explore and Apply Conservation of Energy
Students should understand the principles of energy conservation and apply them to practical problems.
LO5. Understand Electromagnetic Wave Propagation
Students should describe plane and transverse waves and understand the propagation of electromagnetic waves.
CP 1. Models, unities and calculus
CP 2. Unidimensional movement
CP 3. Bidimensional movement
CP 4. Newton's laws
CP 5. Conservation of Energy
CP 6. Electric Field and Magnetic Field
CP 7. Plane Waves and Transverse Waves
CP 8. Propagation of Electromagnetic Waves
The assessment throughout the semester includes two written tests with a weight of 60% in the final grade (30% T1 + 30% T2). Each written test has a minimum passing score of 7 points.
The individual work by the student has a weight of 10% in the final grade, and the submission of group reports carries a weight of 30% in the final grade.
A minimum score of 9.5 points in the sum of all assessment components (60% + 30% + 10%) is required, along with a minimum attendance of no less than two-thirds of the classes.
In the examination assessment mode:
The written exam accounts for 100% of the final grade, and a minimum score of 9.5 points.
Title: Paul G. Hewitt, Física: Princípios e Problemas, Editora Artmed, 2019.
David Halliday, Robert Resnick e Jearl Walker, Fundamentos de Física, Editora LTC, 2021.
Adilson J. S. Pereira e Ricardo M. F. de Oliveira, Física: Conteúdo e Prática, Editora Pearson, 2020.
Raymond A. Serway e John W. Jewett, Physics for Scientists and Engineers, Cengage Learning, 2019.
Hugh D. Young e Roger A. Freedman, University Physics with Modern Physics, Pearson, 2019.
Authors:
Reference: null
Year:
Title: R. P. Feynman, Feynman Lectures on Physics, Edição Addison Wesley, 2011.
Authors:
Reference: null
Year:
Introduction to Statistics
LO1. Understand and use a tool (Python or R) for statistical analysis
LO2. Understand the information gathered using statistics
LO3: Use the most important theoretical distributions to calculate probabilities in real-life problems
LO4: Identify and apply estimation and decision methods to real-life problems
S1: Univariate descriptive statistics
S2: Bivariate descriptive statistics
S3: Main theoretical distributions of discrete random variables
S4. Main theoretical distributions of continuous random variables
S5: Parameter estimation
S6. Decision-making
The approval in this course has to be with a mark of not less than 10, in one of the following methods:
- Periodic Assessment: 2 mini-tests (MT) taken in class (15% each) + Final test taken on the date of the first exam (40%) + autonomous work (10%) + group project (20%),
The average of the mini-tests ( (MT1+MT2)/2 ) has a minimum mark of 7.0.
The final test has a minimum mark of 7.0.
or
- Assessment by Exam (100%).
Title: Afonso, A. & Nunes, C. (2019). Probabilidades e Estatística. Aplicações e Soluções em SPSS. Versão revista e aumentada. Universidade de Évora. ISBN: 978-972-778-123-2
Reis, E., P. Melo, R. Andrade & T. Calapez (2015) Estatística Aplicada (Vol. 1), 6ª ed.Lisboa: Sílabo.
Reis, E., P. Melo, R. Andrade & T. Calapez (2016) Estatística Aplicada (Vol. 2), 5ª ed., Lisboa: Sílabo.-
Laureano, R. (2020) - Testes de Hipóteses e Regressão, Lisboa, Edições Sílabo.
Authors:
Reference: null
Year:
Title: Curto, J. D. (2021). Estatística com R: Aprenda Fazendo. ISBN: 979-8531511492
Farias, A. L. (2010). Probabilidade e Estatística. (V. único). Fundação CECIERJ. ISBN: 978-85-7648-500-1
Ferreira, P. M. (2012). Estatística e Probabilidade (Licenciatura em Matemática). Instituto Federal de
Educação, Ciência e Tecnologia do Ceará – IFCE III, Universidade Aberta do Brasil – UAB.IV. ISBN: 978-
85-63953-99-5
Haslwanter, T. (2016). An Introduction to Statistics with Python: With Applications in the Life Sciences. Springer. ISBN: 978-3-319-28316-6
Authors:
Reference: null
Year:
Linear Algebra and Geometry
LO1 Understand the concept of vector space, apply properties and determine a basis.
LO2 Classify sets of vectors with respect to linearity.
LO3 Represent points and vectors and calculate distances.
LO4 Operate with vectors and identify the relative position of planes and lines.
LO5 Determine equations of the line and plane.
LO6 Calculate and interpret inner and outer products.
LO7 Parametrize curves and calculate the normal and tangent vectors.
LO8 Operate with matrices, solve systems of linear equations by matrix calculation and interpret geometrically.
LO9 Calculate inverse matrix and determinant.
LO10 Understand the linear transformation between finite dimensional vector spaces.
LO11 Understand the necessity of complex numbers and the algebraic and polar forms.
LO12 Operate with complex numbers and apply Moivre's formulas and Euler's identity.
LO13 Acquire skills and reasoning adequate to solve problems in topics of Robotics and Intelligent Systems.
PC1 Concept of vector space (VS) and subspace. Linear dependence of vectors and basis of a VS.
PC2 Points and vectors in the plane and in space. Distance between two points and from a point to a line. Plane sections and spherical surface.
PC3 Vectors and operations. Internal product. Parallelism and perpendicularity of vectors. Relative position of lines and planes.
PC4 Vector director and equation of a line.
PC5 Cross product. Vector normal to a plane and equations of the plane.
PC6 Parametrization of curves in plane and in space. Normal and tangent vectors to a curve. Intersection of curves. Polar coordinates.
PC7 Matrices and operations. Inverse of a non singular matrix. Determinant of a square matrix.
PC8 Systems of linear equations. Matrix form and resolution. Linear transformations.
PC9 Quadratic equations. Complex numbers in algebraic and polar forms. Euler's formula.
PC10 The set of complex numbers as real VS . Moivre's formula. Roots of a complex number.
Approval with classification not less than 10 points (scale 1-20) in one of the following modalities:
- Assessment Throughout the Semester: 8 exercises completed during classes (35%) (only the 6 highest-scoring exercises are considered) + exercises solved on Moodle (5%) + final written test (60%). A minimum score of 7 out of 20 is required for each assessment component.
- Exam Assessment: In any exam period, with an individual written exam (100%).
A minimum attendance of 2/3 of the classes is required.
Title: [1] Cabral, I., Perdigão C. e Saiago, C. (2018). Álgebra Linear: Teoria, Exercícios Resolvidos e Exercícios Propostos com Soluções, Escolar Editora.
[2] Strang, G., (2007). Computational Science and Engineering, Wellesley-Cambridge Press.
[3] Goldstein, L. (2011). Matemática Aplicada ? Economia. Administração e Contabilidade, (12ª edição) Editora Bookman.
[4] Hanselman, D., Littlefield, B. and MathWorks Inc. (1997). The Student Edition of MATLAB, 5th Version, Prentice-Hall
[5] Materiais científico-pedagógicos (slides, notas de desenvolvimento, código e pseudo código, fichas de exercícios e problemas) disponibilizados pela equipa docente
Scientific-pedagogical materials (slides, lectures, code and pseudo code, exercise sheets, problems) provided by the teaching team.
Authors:
Reference: null
Year:
Title: David C. Lay, Linear Algebra and its Applications, Addison Wesley, Pearson
Authors:
Reference: null
Year:
Power Electronics
After attending the course, students should be able to:
OA1 - Know the basic electronic components.
OA2 - Design and test basic electronic circuits.
OA3 - Know how to analyse the correct operation of an electronic circuit.
OA4 - Know the main differences between natural and forced commutators.
OA5 - Analyse the operation of converters.
OA5.1- Analyse the operation of AC-DC converters.
OA5.2- Analyze the operation of DC-AC converters.
OA5.3- Analyse the operation of DC-DC converters.
OA5.4- Analyse the operation of AC-AC converters.
CP1. Introduction to Electronics: Semiconductors, Diodes and transistors. Analog and digital electronics.
CP2. Introduction to Power Electronics: Power electronics applications; Power electronics converters classification;
CP3. Single and three phase uncontrolled rectifiers, natural and forced commutation: Applications and semiconductor type selection; Half and full bridge converter
CP4. DC-DC Converters
CP5. Introduction to resonant converters and switched-mode sources: Advantages of this type of converters; Isolated and multiple output switched-mode sources.
CP6. Single-Phase and Three-Phase Inverters
CP7. AC-AC converters without DC Bus Intermediate: Single-phase configurations
Laboratory (40%) + Written exam (60%)
Minimum grade in the laboratory: 8
Minimum exam grade: 8
The possibility of taking the written exam in the normal or special season is subject to:
- Presence in laboratory classes (100%) *,
- Presence in theoretical classes at least (50%),
- Presence in theoretical-practical classes at least (50%).
*If for objective reasons absences are registered in the laboratory, a way to recover the missing laboratory will be agreed with the professor.
Title: "Introduction to modern power electronics", Andrzej M. Trzynadlowski, JohnWiley & Sons, Third edition, 2016.
"Electronics Fundamentals: Circuits, Devices & Applications", Thomas Floyd, David Buchla, 8th Edition, 2014
Authors:
Reference: null
Year:
Title: Robert W. Erickson , Dragan Maksimovi?, Fundamentals of Power Electronics 3rd ed. Edition, Springer, 2020
Authors:
Reference: null
Year:
Project Planning and Management
The objective of the UC is to develop a technological project in line with the scope of the Course. Contact will be established with project planning considering the main phases: Requirements analysis, development, partial tests and final tests and changes. Contact with laboratory equipment and tools is one of the goals for designing a software, hardware or both project.
I. Introduction to technological innovation along the lines of Europe
II. Planning a technological project and its phases
III. Essential aspects for the development of a project
IV. Definition of material resources
V. Budget of a project
VI. Partial and joint Test Plan
VII. Presentation of a technological project
VIII. Technological project demonstration
IX. Preparation of Technical Report
Periodic grading system:
- Group project: first presentation: 30%; second presentation and exhibition: 40%; final report: 30%. The presentations, demonstrations and defence are in group.
Title: Lester A. / 7th edition, Elsevier Science & Technology., Project Management Planning and Control, 2017, ·, ·
Tugrul U. Daim, Melinda Pizarro, e outros / Spinger, Planning and Roadmapping Technological Innovations: Cases and Tools (Innovation, Technology, and Knowledge Management), 2014, ·, ·
Authors:
Reference: null
Year:
Introduction to Design Thinking
LO1. Acquiring knowledge about the fundamentals and stages of the Design Thinking process
LO2. Develop skills such as critical thinking, collaboration, empathy and creativity.
LO3. To apply Design Thinking in problem solving in several areas, promoting innovation and continuous improvement.
S1. Introduction to Design Thinking and Stage 1: Empathy (3h)
S2. Steps 2 and 3: Problem Definition and Ideation (3h)
S3. Step 4: Prototyping (3h)
S4. Step 5: Testing and application of Design Thinking in different areas (3h)
Semester-long Assessment Mode:
• Class participation (20%): Evaluates students' presence, involvement, and contribution in class discussions and activities.
• Individual work (40%): Students will develop an individual project applying Design Thinking to solve a specific problem. They will be evaluated on the application of the stages of Design Thinking, the quality of the proposed solutions, and creativity.
• Group work (40%): Students will form groups to develop a joint project, applying Design Thinking to solve a real challenge. Evaluation will be based on the application of the steps of Design Thinking, the quality of the solutions, and collaboration among group members.
To complete the course in the Semester-long Assessment mode, the student must attend at least 75% of the classes and must not score less than 7 marks in any of the assessment components. The strong focus on learning through practical and project activities means that this course does not include a final assessment mode.
Title: Brown, T. (2008). Design Thinking. Harvard Business Review, 86(6), 84–92.
Lewrick, M., Link, P., & Leifer, L. (2018). The design thinking playbook: Mindful digital transformation of teams, products, services, businesses and ecosystems. John Wiley & Sons.
Lockwood, T. (2010). Design Thinking: Integrating Innovation, Customer Experience and Brand Value. Allworth Press.
Stewart S.C (2011) “Interpreting Design Thinking”. In: https://www.sciencedirect.com/journal/design-studies/vol/32/issue/6
Authors:
Reference: null
Year:
Title: Brown, T., & Katz, B. (2011). Change by design. Journal of product innovation management, 28(3), 381-383.
Brown, T., Katz, B. M. Change by Design: How Design Thinking Transforms Organizations and Inspires Innovation. HarperBusiness, 2009.
Liedtka, J. (2018). Why Design Thinking Works. Harvard Business Review, 96(5), 72–79.
Gharajedaghi, J. (2011). Systems thinking: Managing chaos and complexity. A platform for designing business architecture. Google Book in: https://books.google.com/books?hl=en&lr=&id=b0g9AUVo2uUC&oi=fnd&pg=PP1&dq=design+thinking&ots=CEZe0uczco&sig=RrEdhJZuk3Tw8nyULGdi3I4MHlQ
Authors:
Reference: null
Year:
Public Speaking with Drama Techniques
LO1. Develop specific oral communication skills for public presentations.
LO2. Know and identify strategies for effective use of the vocal apparatus.
LO3. Identify and improve body expression. LO4. Learn performance techniques.
The learning objectives will be achieved through practical and reflective activities, supported by an active and participatory teaching method that emphasizes experiential learning. The knowledge acquired involves both theatrical theory and specific oral communication techniques. Students will learn about the fundamentals of vocal expression, character interpretation and improvisation, adapting this knowledge to the context of public performances.
PC1. Preparing for a presentation.
PC2. Non-verbal communication techniques.
PC3. Voice and body communication, audience involvement. PC4. Presentation practice and feedback. The learning objectives will be achieved through practical and reflective activities, supported by the active and participatory teaching method which emphasizes experiential learning. Classes will consist of activities such as: Theatrical experiences and group discussions; Practical activities; Presentations and exhibitions of autonomous work; Individual reflection.
The assessment of the Public Presentations with Theatrical Techniques course aims to gauge the development of students' skills in essential aspects of public presentations. The assessment structure includes activities covering different aspects of the experiential learning process involving both theatrical techniques and specific communication techniques.
Assessment throughout the semester includes activities covering different aspects of the process of preparing a public presentation, including group and individual work activities:
Group activities (50%) [students are challenged to perform in groups of up to 5 elements, made up randomly according to each activity proposal].
1-Practical Presentations: Students will be assessed on the basis of their public presentations throughout the semester:
Description: each group receives a presentation proposal and must identify the elements of the activity and act in accordance with the objective.
The results of their work are presented in class to their colleagues (Time/group: presentation - 5 to 10 min.; reflection - 5 min.). Assessment (oral): based on active participation, organization of ideas and objectivity in communication, vocal and body expression, the use of theatrical techniques and performance. Presentations may be individual or group, depending on the proposed activities.
Individual activities (50%)
1-Exercises and Written Assignments (Autonomous Work):
Description: In addition to the practical presentations, students will be asked to carry out exercises and written tasks related to the content covered in each class. These activities include reflecting on techniques learned, creating a vision board, analyzing academic objectives, student self-assessment throughout the semester, answering theoretical questions and writing presentation scripts.
Assessment: (Oral component and written content), organization, content, correct use of the structure and procedures of the autonomous work proposed in each class, ability to answer questions posed by colleagues and the teacher. Communication skills and the quality of written work will be assessed, with a focus on clarity of presentation. These activities will help to gauge conceptual understanding of the content taught.
There will be no assessment by final exam, and approval will be determined by the weighted average of the assessments throughout the semester.
General considerations: in the assessment, students will be given feedback on their performance in each activity.
To complete the course in this mode, the student must attend 80% of the classes. The student must have more than 7 (seven) points in each of the assessments to be able to remain in evaluation in the course of the semester.
Title: Prieto, G. (2014). Falar em Público - Arte e Técnica da Oratória. Escolar Editora.
Authors:
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Title: Anderson, C. (2016). TED Talks: o guia oficial do TED para falar em público. Editora Intrinseca.
Luiz, P. (2019). Manual de Exercícios Criativos e Teatrais. Showtime. Rodrigues, A. (2022). A Natureza da Atividade Comunicativa. LisbonPress.
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Academic Work with Artificial Intelligence
LO1. Know the structure, language and ethical and normative (APA) procedures for writing academic texts.
LO2. Learn how to use generative models to write academic texts.
LO3. Discuss procedures for the analysis, relevance and reliability of data generated by AI.
LO4. Recognize the ethical implications of using generative AI in an academic context. The learning objectives will be achieved through practical and reflective activities such as:
- Group discussions;
- Analysis of texts;
- Oral defense;
- Practical exercises.
CP1. Introduction: academic writing and generative models:
- Understanding how Generative Artificial Intelligence works: the path towards using generative AI in the academic environment.
CP2. Procedures for planning and constructing argumentative texts with the help of AI:
- Identifying the possibilities and hallucinations in the answers produced by Generative AI.
CP3. Critical analysis of texts produced: identifying and referencing data sources and analyzing their relevance to the objectives of academic work:
- Exploring the possibilities of data validation and the potential use of Generative AI tools in the production of academic papers.
CP4. Opportunities and risks of using AI: good practice guide for accessing, sharing and using Generative AI in an academic context:
- Understand the dynamics in responsible and ethically committed use when carrying out academic work with Generative AI tools.
The assessment of the course aims to gauge the development of students' skills in the informed use of generative models as an aid to the production of academic work. Assessment throughout the semester includes the following activities:
1.Individual activities (50%)
1.1 Participation in activities throughout the semester (10%).
Description: this component aims to assess each student's specific contribution to the activities carried out.
Assessment: Interventions in the classroom; relevance of the student's specific contributions to the debates.
1.2 Simulations of prompts with AI tools in an academic context (20%).
Description: the student must create a clear/justified, well-structured prompt, according to the script proposed by the teacher in class.
Assessment: (submit on moodle), communication skills and teamwork based on the quality of the prompt simulations carried out.
1.3 Oral Defense - group presentation - 5 minutes; debate - 5 minutes (20%).
Description: Each student must present their contributions to the work carried out to the class.
Evaluation: after the student's presentation, there will be a question and answer session.2. group activities (50%)
[students are organized in groups of up to 5 elements, constituted randomly]
2.1 Group presentations, revisions, editing and validation of content produced by AI (20%):
Description: Formation of working groups to review and edit the texts, using the generative models.
Evaluation: (submit to moodle), collection of relevant information, clarity and the innovative nature of the use of properly structured promts.
2.2 Development of strategies for reviewing, editing and validating content produced by AI (10%).
Description: At the end of each stage of the activity, students will have to promote critical evaluations by reflecting on the ethical challenges of integrating AI into an academic environment.
Evaluation: (submit on moodle), work will be corrected and evaluated based on accuracy and compliance with the quality of revisions, edits and the participation of students in the feedback provided to colleagues.
2.3 Final Project Presentation Simulations (20%):
Description: the groups choose a topic and create a fictitious project following the structure of a technical report or scientific text, making a presentation of their project in class (5 minutes) and debating the topic (5 minutes).
Evaluation: (submit on moodle): organization, content, correct use of the structure and procedures of academic work.
General considerations: feedback will be given during the semester. The student must have more than 7 (seven) points in each of the assessments to be able to remain in evaluation in the course of the semester.
Title: Cotton, D. R., Cotton, P. A., & Shipway, J. R. (2023). Chatting and cheating: Ensuring academic integrity in the era of ChatGPT. Innovations in Education and Teaching International, 1-12.
D'Alte, P., & D'Alte, L. (2023). Para uma avaliação do ChatGPT como ferramenta auxiliar de escrita de textos académicos. Revista Bibliomar, 22 (1), p. 122-138. DOI: 10.18764/2526-6160v22n1.2023.6.
Kasneci, E., Seßler, K., Küchemann, S., Bannert, M., Dementieva, D., Fischer, F., ... & Kasneci, G. (2023). ChatGPT for good? On opportunities and challenges of large language models for education. Learning and Individual Differences, 103, 102274.
Ribeiro, A. & Rosa, A. (2024). Descobrindo o potencial do CHATGPT em sala de aula: guia para professores e alunos. Atlantic Books. "
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Title: Cowen, T., & Tabarrok, A. T. (2023). How to learn and teach economics with large language models, including GPT. GMU Working Paper in Economics No. 23-18, http://dx.doi.org/10.2139/ssrn.4391863 Lund, B. D., Wang, T., Mannuru, N. R., Nie, B., Shimray, S., & Wang, Z. (2023). ChatGPT and a new academic reality: Artificial Intelligence‐written research papers and the ethics of the large language models in scholarly publishing. Journal of the Association for Information Science and Technology, 74(5), 570-581. Strunk, William (1918) Elements of Style Korinek, A. (2023). Language models and cognitive automation for economic research (No. w30957). National Bureau of Economic Research. https://www.nber.org/papers/w30957
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Microcontrollers
OA1 study of microcontroller architecture;
OA2 development and programming of systems with microcontroller with application in automation;
OA3 develop automations based on microcontroller.
CP1:Typical architecture and internal units of a microcontroller,
CP2: Memory types and organization.
CP3: Analog and Digital Signal Interface.
CP4: Timing/counting, Interrupts
CP5:Serial communications (UART,SPI, I2C).
CP6Program development using C and dedicated libraries
CP7Planning and realization of a microcontroller based project.
Written test (40%)
Laboratory Work (30%)
Final mini-project (30%)
Minimum grade 8
Title: ·, Simon Monk, Programming Arduino, 2016, ·, ·
·, Microcontroladores - Guia de Laboratório, 2023, ·, ·
·
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Title: Tero Karvinen, Kimmo Karvinen, V. Valtokari / MalerMedia, Sebastopol, Make Sensors, 2015, ·, ·
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Robotics and Advanced Automation
After the completion of this course, students should
(OA1) Know the different industrial robotic platforms as well as the main control architectures of robotic systems.
(OA2) Identify the requirements of the systems and/or models to be implemented;
(OA3) Choose the technological approaches best suited to the requirements of the problems.
(OA4) Understand and know how to use the approaches presented in the UC for the development of robotic systems.
CP1: Robotics Fundamentals
CP2: Robot Technology
CP3: Robot Applications in Industry
CP4: Kinematics
CP5: Robot Languages and Programming
CP6: Robot Control Systems
CP7: Block Programming
CP8: Redundancy
The evaluation is based on a project (50%) and a final exam (50%).
The project has two evaluation phases, mid-term delivery and a final oral examination.
Final grade is the average from the project and the exam grades
Title: Saeed B. Niku, "Introdução a Robótica: Análise, Controle, Aplicações , 2ªedição LTC Editora
J. Norberto Pires, "Robótica Insdustrial Industria 4.0" ,Lidel, Lisboa, 2018.
Norberto J. Pires , "Automação e Controlo Industrial",Lidel, Lisboa, 2019
P. Oliveira, ?Curso de Automação Industrial?, ETEP, LIDEL, 2008
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Title: --
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Quality Control and Artificial Vision
After completing this course, the student should:
OA1: Know the fundamentals of quality control;
OA2: Know the fundamentals of applying artificial vision to quality control;
OA3: Know the fundamentals of applying artificial intelligence to quality control;
OA4: Understand the fundamentals of designing human-machine interfaces for quality control.
P1. Quality Control (QC), quality metrics and non-destructive inspection.
P2. Integration of QC in automation systems and interconnection to the process.
P3. Fundamentals of artificial vision and artificial intelligence essential to QC.
P4. Selection and calibration of sensors, lenses, filters, and lighting for QC based on artificial vision.
P5. Passive and active collection of sensory data, its filtering, processing, and analysis for QC.
P6. Automatic learning of models and their use in detecting and predicting failures/deviations.
P7. Human-machine interfaces in the context of QC.
Periodic Assessment: Group project (60%) + Individual written test (40%).
Assessment by Exam: Individual written exam (100%).
Title: Szeliski, R. (2021). Computer Vision: Algorithms and Applications (2nd ed). Springer.
Dawson-Howe, K. (2014). A Practical Introduction to Computer Vision with OpenCV (1st. ed.). Wiley.
Anand, S., & Priya, L. (2019). A Guide for Machine Vision in Quality Control (1st ed.). CRC Press.
Authors:
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Entrepreneurship and Innovation I
At the end of the learning unit, the student must be able to: LG.1. Understand entrepreneurship; LG.2. Create new innovative ideas, using ideation techniques and design thinking; LG.3. Create value propositions, business models, and business plans; LG.5. Develop, test and demonstrate technology-based products, processes and services; LG.6. Analyse business scalability; LG.7. Prepare internationalization and commercialization plans; LG.8. Search and analyse funding sources
I. Introduction to Entrepreneurship;
II. Generation and discussion of business ideas;
III. Value Proposition Design;
IV. Business Ideas Communication;
V. Business Models Creation;
VI. Business Plans Generation;
VII. Minimum viable product (products, processes and services) test and evaluation;
VIII. Scalability analysis;
IX. Internationalization and commercialization;
X. Funding sources
Periodic grading system: - Group project: first presentation: 30%; second presentation: 30%; final report: 40%.
Title: A. Osterwalder, Y. Pigneur / John Wiley & Sons, Value Proposition Design: How to Create Products and Services Customers Want, 2014, ·, ·
A. Osterwalder, Y. Pigneur / John Wiley & Sons, Business Model Generation: A Handbook for Visionaries, Game Changers, and Challengers., 2010, ·, ·
P. Burns / Palgrave Macmillan, Entrepreneurship and Small Business, 2016, ·, ·
S. Mariotti, C. Glackin / Global Edition. Pearson; Dorf. R., Byers, T. Nelson, A. (2014). Technology Ventures: From Idea to Enterprise. McGraw-Hill Education, Entrepreneurship: Starting and Operating A Small Business, 2015, ·, ·
Authors:
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Manufacturing Management and Information Systems
At the end of this course, students should be able to:
OA1. Understand digital technologies and their impact on the strategy of industrial manufacturing companies, when producing tangible goods and providing services;
OA2.: Characterize organizations, model business processes and understand the role of technological systems in companies;
OA3: Understand the characteristics of ERP systems and their use in the management of organizational processes in companies. Know how to use an ERP, WMS or TMS system.
OA4.: Use a strategic management planning approach to understand the link between the organization's strategy and the supporting technological systems;
OA5.: Consolidate the concepts studied by creating a plan for the development of an innovative business (start-up), articulating organizational aspects and technological systems suited to the company's strategic objectives.
CP1. Characteristics of the industrial manufacturing company
a. The Digital Transformation and Industry 4.0
b. Operation and organizational structure of the company
CP2. Operations and business process management
a. Operations and logistics management.
b. Organizational architecture and industrial processes
c. Business Process Management (BPM)
d. Visual process modeling (with BPMN)
CP3. Information systems in manufacturing
a. Management and information systems
b. IS requirements
c. Automation of production and logistics processes (ERP, WMS, TMS)
CP4. applied project
Evaluation throughout the semester
Group assignment (report + presentation + final discussion) 40%
Individual report (thematic or field visit) 20%
Individual final test 40%
In order to get approval, students must score, at least, 8 points (over 20) in every evaluation component with a weight over 30%.
Final exam
Final exam 100%
Title: Object Management Group, Business Process Model and Notation, http://www.bpmn.org/."
Dumas, M.; La Rosa, M.; Mendling, J.; Reijers, H.A. (2018), Fundamentals of Business Process Management, 2nd edition, Springer (www. http://fundamentals-of-bpm.org/)
Laudon, K., Laudon, J., 2016, Management Information Systems - Managing the Digital Firm, 14th Edition, Global Edition.
Documentação de apoio ao software utilizado (ERP Primavera ou outro, Bizagi, etc.)
Slack, N. e Brandon-Jones, A. (2019) Operations Management, 9ª Edição, Pearson
"Slides, handouts
Authors:
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Title: --
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Programming Fundamentals
By the end of this course unit, the student should be able to:
LO1: Apply fundamental programming concepts.
LO2: Create procedures and functions with parameters.
LO3: Understanding the syntax of the Python programming language.
LO4: Develop programming solutions for problems of intermediate complexity.
LO5: Explain, execute and debug code fragments developed in Python.
LO6: Interpret the results obtained from executing code developed in Python.
LO7: Develop programming projects.
PC1. Integrated development environments. Introduction to programming: Logical sequence and instructions, Data input and output.
PC2. Constants, variables and data types. Logical, arithmetic and relational operations.
PC3. Control structures.
PC4. Lists and Lists of Lists
PC5. Procedures and functions. References and parameters.
PC6. Objects and object classes.
PC7. File Manipulation.
PC8: Graphical Interface.
The course follows a project-based continuous assessment model throughout the semester due to its highly practical nature, and does not include a final exam.
The student is evaluated according to the following parameters:
A1 (30% of the final grade): Learning Tasks validated by teachers, with a minimum grade of 8 points on the average of the tasks. There are 10 learning tasks and the 8 best grades count.
A2 (70% of the final grade): Mandatory Group Project (maximum 3 members) with theoretical-practical discussion (Delivery: 30%, Practical-oral: 40% with a minimum grade of 8). Component A2 has a minimum score of 9.5 points.
Students who do not achieve the minimum grade will have the opportunity to complete a 100% Practical Project with an oral discussion.
Minimum attendance of no less than 2/3 of classes is required.
Title: Portela, Filipe, Tiago Pereira, Introdução à Algoritmia e Programção com Python, FCA, 2023, ISBN: 9789727229314
Sónia Rolland Sobral, Introdução à Programação Usando Python, 2a ed., Edições Sílabo, 2024, ISBN: 9789895613878
Nilo Ney Coutinho Menezes, Introdução à Programação com Python: Algoritmos e Lógica de Programação Para Iniciantes. Novatec Editora, 2019. ISBN: 978-8575227183
John Zelle, Python Programming: An Introduction to Computer Science, Franklin, Beedle & Associates Inc, 2016, ISBN-13 : 978-1590282755
Ernesto Costa, Programação em Python: Fundamentos e Resolução de Problemas, 2015, ISBN 978-972-722-816-4,
Authors:
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Title: João P. Martins, Programação em Python: Introdução à programação com múltiplos paradigmas, IST Press, 2015, ISBN: 9789898481474
David Beazley, Brian Jones, Python Cookbook: Recipes for Mastering Python 3, O'Reilly Media, 2013, ISBN-13 ? : ? 978-1449340377
Kenneth Reitz, Tanya Schlusser, The Hitchhiker's Guide to Python: Best Practices for Development, 1st Edition, 2016, ISBN-13: 978-1491933176, https://docs.python-guide.org/
Eric Matthes, Python Crash Course, 2Nd Edition: A Hands-On, Project-Based Introduction To Programming, No Starch Press,US, 2019, ISBN-13 : 978-1593279288
Authors:
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Sensors Actuators and Signal Processing
After successful attendance of the course, students should be able to:
OA1. Identify the main features and components of sensors and actuators and select for applications
OA2. Carry out the design and implementation of specific conditioning circuits for sensors and actuators.
OA3. Design systems based on sensors and actuators for specific applications: industrial, processional agriculture, environmental monitoring.
OA4. Understand, design and implement digital signal processing algorithms.
OA5 Design and implement real-time digital systems characterized by sensors, actuators and specific digital signal processing algorithms.
CP1 Classification sensors; analog and digital sensors, operation, applications.
CP2: Actuators: classification, operation and applications
CP3: Signal conditioning: amplification, analog signal processing -analog filtering, specific control circuits for actuators:
CP4 Elements about analogue and analogue digital conversion..
CP5 Digital signal processing: time-domain and frequency-domain signal analysis; digital filtering algorithms.
CP6 Implementation of digital processing algorithms on real-time computing platforms
CP7 Systems design with sensors and actuators and signal processing modules and applications::industrial, cities and smart homes, transport, precision agriculture.
Laboratory (40%) + Written exam (60%)
Minimum grade in the laboratory: 8
Minimum exam grade: 8
The possibility of taking the written exam in the normal or special season is subject to:
- Presence in laboratory classes (100%) *,
- Presence in theoretical classes at least (50%),
- Presence in theoretical-practical classes at least (50%).
*If for objective reasons absences are registered in the laboratory, a way to recover the missing laboratory will be agreed with the professor.
Title: Clarence W. de Silva, Sensors and Actuators, Engineering System Instrumentation, Second Edition, CRC press 2015.
Octavian Postolache,Eletronica Programada e Processamento digital de SinaisI: Guia de laboratórios, ISCTE-IUL, 2021;
Allen B. Downey,Think DSP: Digital Signal Processing in Python, O'Reilly Media; 1st edition, 2016
Clarence W. de Silva,Sensors and Actuators: Engineering System Instrumentation, Second Edition, CRC Press 2015
Authors:
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Title: William Bolton, Instrumentation and Control Systems, Newnes; 3rd edition, 2021
NJATC NJATC Fundamentals of Instrumentation 2nd Edition
John G. Webster, Halit Eren Measurement, Instrumentation, and Sensors Handbook, CRC press 2014
Authors:
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Entrepreneurship and Innovation II
At the end of this UC, the student should be able to:
LG.1. Present the image of the product/service in a website
OA.2. Present the image of the product/service in social networks
OA.3. Describe functionalities of the product/service
OA.4. Describe phases of the development plan
OA.5. Develop a prototype
OA.6. Test the prototype in laboratory
OA.7. Correct the product/service according to tests
OA.8. Optimize the product/service considering economic, social, and environmental aspects
OA.9. Adjust the business plan after development and tests, including commercialization and image
OA.10. Define product/service management and maintenance plan
I. Development of the product/service image
II. Functionalities of the product/service
III. Development plan
IV. Development of the product/service (web/mobile or other)
V. Revision of the business plan
VI. Management and maintenance of the product/service
VII. Certification plan
VIII. Intellectual property, patents, and support documentation
IX. Main aspects for the creation of a startup - juridical, account, registry, contracts, social capital, obligations, taxes
Periodic grading system:
- Group project: first presentation: 30%; second presentation: 30%; final report: 40%. The presentations, demonstrations and Defence are in group.
Title: ·
A. Osterwalder, Y. Pigneur / John Wiley & Sons, Value Proposition Design: How to Create Products and Services Customers Want, 2014, ·, ·
A. Osterwalder, Y. Pigneur / John Wiley & Sons, Business Model Generation: A Handbook for Visionaries, Game Changers, and Challengers, 2010, ·, ·
P. Burns / Palgrave Macmillan, Entrepreneurship and Small Business, 2016, ·, ·
R. Dorf, T. Byers, A. Nelson / McGraw-Hill Education, Technology Ventures: From Idea to Enterprise., 2014, ·, ·
S. Mariotti, C. Glackin / Global Edition. Pearson, Entrepreneurship: Starting and Operating A Small Business, 2015, ·, ·
Authors:
Reference: null
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Instrumentation and Industrial Control
After attending the course, students should be able to:
OA1. Identify the main elements of a control loop, physical characteristics and metrology elements associated with industrial instruments and controllers.
OA2. Know the main instruments associated with the control of industrial processes.
OA3 Characterize, test and calibrate industrial instrumentation modules
OA4. Understand and implement process controllers considering the main control modes
OA5. Design and implement industrial instrumentation systems based on the use of PLCs and real-time processing platforms.
OA6 Understand and use industrial communication protocols.
CP1: General Concepts on measurement and measuring instruments and on the control of industrial processes,
CP2: Industrial instrument for measuring process quantities: pressure, force, level, flow, temperature, heat, humidity, density, viscosity and pH.
CP3: Signal conditioning for industrial instruments: amplifiers, measuring bridges.
CP4: Valves and Actuators and Motor Control - Applications
CP5:Control modes and digital controllers.
CP6: Programmable Logic Circuits and Applications
CP7: Communication protocols with application in industrial instrumentation and control systems.
Laboratory (40%) + Written exam (60%), Continuous Evaluation
Minimum grade in the lab: 8
Minimum exam grade: 8
The possibility of taking the written exam in the normal or special season is subject to:
- Presence in laboratory classes (100%) *,
- Presence in theoretical classes at least (50%),
- Presence in theoretical-practical classes at least (50%).
*If for objective reasons absences are registered in the laboratory, a way to recover the missing laboratory will be agreed upon with the professor.
Title: William Dunn, Fundamentals of Industrial Instrumentation and Process Control, Second Edition, Mc Graw Hill Education 2018.
Octavian Postolache, Instrumentação e Controlo Industrial : Guia de laboratórios, ISCTE-IUL, 2021;
William Bolton, Instrumentation and Control Systems, Newnes; 3rd edition, 2021
Authors:
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Title: Wiliam Bolton Instrumentation and Control 2nd edition, Elsevier, 2015
NJATC NJATC Fundamentals of Instrumentation 2nd Edition
John G. Webster, Halit Eren Measurement, Instrumentation, and Sensors Handbook, CRC press 2014
Authors:
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Fundamentals of Automation
LO1 - automaton architect and programming methods
LO2 - Automation system structure using programmable logic controllers
LO3 - solve sequential control tasks in an automation system by writing the corresponding programmable logic controller programs
LO4 - control automatic drive systems
CP1: Introduction
CP2: Combinational Logic
CP3: Sequential Logic
CP4: Programming Languages
CP5: Algorithms
CP6: Finite Automation
CP7: Programmable Industrial Automation
Compulsory attendance of the student in 90% of Curricular Unit activities. Completion and presentation in laboratory of group project. Assessment weights:
- 5% - Attendance and participation in class.
- 70% - 4 group project work assignments.
- 25% - Mini-test with multiple answers.
The student waives the exam with 10 marks. In case of failure in the regular season the student has access to the exam of the resource season.
Title: J. N. Pires, ?Automação Industrial?, 3a Edição. Lidel, 2007.
J. R. C. Pinto, ?Técnicas de Automação?, Lidel, Lisboa, 2004.
A. Francisco, ?Autómatos Programáveis (Programação, GRAFCET, Aplicações)?, 4a Edição, Lidel, 2007
Authors:
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Title: Mandado Pérez et al, Autómatas Programables, entorno y aplicaciones, Thomson, ed. Siemens, 2005;
W. Bolton , Programmable Logic Controllers - 6th Edition, Elsevier
Authors:
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Applied Project in Automation II
LO1: Correct the user and/or organization problem identified in the Applied Project I course of the 1st semester, developing, in an iterative way, an integrated project with all its components, including requirements gathering, solution prototyping (lo-fi, hi-fi, MVP), and evaluation and field deployment of the innovative solution, regarding product, process or service (PPS).
LO2: Produce design documentation of the PPS innovation solution, including, where applicable, architecture, hardware and software configuration, installation, operation and usage manuals.
LO3: Produce solutions with the potential to be triple sustainable in the field, taking into account the applicable legal framework.
LO4: Produce audiovisual content on the achieved results, to be exploited in several communication channels: social networks, landing page web, presentation to relevant stakeholders, demonstration workshop.
S1 Solution space: ideation of the best technological solution relative to the project, development of user requirements, storyboarding, user/costumer journey, iterative prototyping cycles (low fidelity - lo-fi, high fidelity - hi-fi, minimum viable product - MVP), heuristic evaluation of the solution with experts and evaluation with end users.
S2 Production of solution design documentation, including, where applicable, architecture, technical specifications, hardware and software configuration, installation, operation and use manuals.
S3. Experimental deployment of the solution with the potential to be triple sustainable (with economic, social and environmental value creation), safeguarding the applicable legal framework.
S4. Audiovisual communication on the Web and social networks. Communication in public and its structure. Presentation to relevant actors.
S5. Demonstration in workshop with relevant actors
UC in periodic assessment, not contemplating final exam, given the adoption of the project-based teaching method applied to real situations. Presentations, demonstrations and discussion are carried out in groups.
Evaluation weights:
R1 Solution Ideation Report, with Storyboard, User Journey, User Requirements, Technical Specifications and its audiovisual presentation: 20%.
R2 Solution Prototyping: Lo-fi and Hi-fi Prototypes and Minimum Viable Prototype - MVP (on GitHub), its Demonstration and Evaluation Report: 40%
R3 Solution Design Report with the following elements (if applicable): Architecture (UML Package Diagram, UML Component Diagram), Hardware and Software Configuration, Installation Manual (UML Deployment Diagram, Configuration Tutorial), Operation Manual, User Manual: 20%
R4 Audio-visual presentation of the solution and its demonstration in a Workshop: 20%.
Title: ·
HarperCollins, 2009, ISBN-13: 978-0062856623, Change by Design: How Design Thinking Transforms Organizations and Inspires Innovation, 2009, ·, ·
Lewrick, M, Link, P., Leifer, L. / Wiley, ISBN 9781119629191, The Design Thinking Toolbox, 2020, ·, ·
Knapp, J., Zeratsky, J., & Kowitz, B. / Bantam Press, Sprint: How to Solve Big Problems and Test New Ideas in Just Five Days., 2016, ·, ·
Authors:
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Title: ·
Ries, E. / capítulos 3 e 4, Penguin Group, The Lean Startup: How Today's Entrepreneurs Use Continuous Innovation to Create Radically Successful Businesses, 2017, ·, ·
·, Scrum Institute, The Kanban Framework 3rd Edition, 2020, ·, www.scrum-institute.org/contents/The_Kanban_Framework_by_International_Scrum_Institute.pdf acedido em 02/2023
Darrell Rigby, Sarah Elk, Steve Berez / Scrum Institute (2020), The Scrum Framework 3rd Edition, Doing Agile Right: Transformation Without Chaos Hardcover Scrum Institute (2020), The Scrum Framework 3rd Edition, 2020, ·, www.scrum-institute.org/contents/The_Scrum_Framework_by_International_Scrum_Institute.pdf
Jeff Sutherland, J.J. Sutherland, Scrum: The Art of Doing Twice the Work in Half the Time, 2014, ·, ·
Project Management Institute / 6th ed. Newton Square, PA: Project Management Institute, A guide to the project management body of knowledge (PMBOK guide), 2017, ·, ·
Gwaldis M., How to conduct a successful pilot: Fail fast, safe, and smart, 2019, ·, https://blog.shi.com/melissa-gwaldis/ acedido em 02/2023
Authors:
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Year:
Unsupervised Machine Learning
LO1. Understand the main methods of non-supervised learning.
LO2: Evaluate, validate, and interpret the results of non-supervised models.
LO3: Develop knowledge discovery projects from data using non-supervised learning models.
LO4: Acknowledge, through the approach of various problem contexts (e.g., customer segmentation) in which unsupervised learning can effectively provide solutions relevant to these problems.
LO5. Understand the theoretical and practical foundations of reinforced learning.
LO6. Implement and test reinforced learning algorithms in simulated environments to understand the dynamics between actions and consequent rewards.
LO7. Evaluate and optimize the performance of reinforced learning models using appropriate metrics.
LO8. Learn and apply unsupervised and reinforced algorithms in practical case studies.
SY1: Introduction to unsupervised learning: fundamental concepts, types of algorithms and practical applications.
SY2: Dimensionality reduction and data visualization: Principal Component Analysis (PCA), t-SNE and UMAP for dimensionality reduction and visual interpretation.
SY3: Clustering and segmentation techniques: exploration of algorithms such as K-Means, DBSCAN, Expectation-Maximization (EM), hierarchical clustering.
SY4: Outlier analysis and detection using unsupervised techniques: KNN, LOF, iForest.
SY5: Association rules and the Apriori algorithm.
SY6: Self-Organizing Maps (SOMs): application of self-organizing maps for visualization and analysis of complex patterns in large volumes of data.
SY7: Reinforcement learning techniques: Q-Learning, SARSA. Introduction to concepts and practical implementation.
SY8: Exploration vs. exploitation in reinforcement learning: strategies for balancing decision-making.
As this course is of a very practical and applied nature, it follows the 100% project-based assessment model throughout the semester, which is why this course does not include a final exam. The assessment consists of 3 assessment blocks (AB), and each AB consists of one or more assessment moments. It is organized as follows:
- AB1: 1st tutorial + 1st mini-test [20% for the 1st tutorial + 10% for the 1st mini-test = 30%]
- AB2: 2nd tutorial + 2nd mini-test [20% for the 2nd tutorial + 10% for the 2nd mini-test = 30%]
- AB3: 1 final project [40%]
All periodic assessment blocks (AB1, AB2 and AB3) have a minimum mark of 8.5. In any AB, it may be necessary to hold an individual oral discussion to assess knowledge.
The tutorials consist of individual oral discussions to assess the students' performance in the projects proposed for the tutorial.
Mini-tests are used to assess the theoretical knowledge applied to each of the projects also assessed during tutorials.
The final project consists of the development of a practical piece of work that brings together the knowledge and skills acquired throughout the semester, in which external organizations / companies may participate in the proposed challenge.
The 1st Season and 2nd Season can be used for assessment.
Attendance at classes is not compulsory.
Title: Berry, M. W., Mohamed, A., & Yap, B. W. (Eds.). (2019). Supervised and unsupervised learning for data science. Springer Nature.
Vidal, R., Ma, Y., & Sastry, S. S. (2016). Generalized principal component analysis (Vol. 5). New York: Springer.
Reddy, C. K. (2018). Data Clustering: Algorithms and Applications. Chapman and Hall/CRC.
Szepesvari, C. (2010). Algorithms for reinforcement learning (R. Brachman & T. Dietterich, Eds.; 1.a ed.). Morgan & Claypool.
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Title: Kassambara, A. (2017). Practical guide to cluster analysis in R: Unsupervised machine learning (Vol. 1). Sthda.
Verdhan, V. (2020). Models and Algorithms for Unlabelled Data. Springer.
Contreras, P., & Murtagh, F. (2015). Hierarchical clustering. In Handbook of cluster analysis (pp. 124-145). Chapman and Hall/CRC.
Sutton, R. S., & Barto, A. G. (2018). Reinforcement Learning, second edition: An Introduction (2.a ed.). MIT Press.
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Human-Machine Interaction and Simulation
After completing this course, the student should:
? OA1: Know the fundamentals of user-centered design of interactive systems;
? OA2: Know the fundamentals of designing and implementing human-robot interfaces;
? OA3: Know the fundamentals of robotic systems simulation;
? OA4: Understand the fundamentals of testing and validating human-robot systems.
? P1. Human factors, user models, user experience, and usability.
? P2. User-centred design, prototyping, and evaluation of interactive systems.
? P3. Basics of visualization and interaction.
? Q4. Fundamentals of human-robot interaction and social robotics.
? Q5. Graphical, natural, and multimodal interfaces in robotics.
? P6. Interfaces based on virtual reality and mixed reality in robotics.
? P7. Simulation of human-robot systems.
? P8. Testing and validation of human-robot systems.
- Periodic Assessment: Group project (60%) + Individual written test (40%).
- Assessment by Exam: Individual written exam (100%).
Title: ? Bartneck, C., Belpaeme, T., Eyssel, F., Kanda, T., Keijsers, M., & ?abanovi?, S. (2020). Human-robot interaction: An introduction. Cambridge University Press.
? Alan Dix, Janet E. Finlay, Gregory D. Abowd, and Russell Beale. 2003. Human-Computer Interaction (3rd Edition). Prentice-Hall, Inc., USA.
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Technology, Economy and Society
After completing this UC, the student will be able to:
LO1. Identify the main themes and debates relating to the impact of digital technologies on contemporary societies;
LO2. Describe, explain and analyze these themes and debates in a reasoned manner;
LO3. Identify the implications of digital technological change in economic, social, cultural, environmental and scientific terms;
LO4. Predict some of the consequences and impacts on the social fabric resulting from the implementation of a digital technological solution;
LO5. Explore the boundaries between technological knowledge and knowledge of the social sciences;
LO6. Develop forms of interdisciplinary learning and critical thinking, debating with interlocutors from different scientific and social areas.
S1. The digital transformation as a new civilizational paradigm.
S2. The impact of digital technologies on the economy.
S3. The impacts of digital technologies on work.
S4. The impact of digital technologies on inequalities.
S5. The impacts of digital technologies on democracy.
S6. The impacts of digital technologies on art.
S7. The impacts of digital technologies on individual rights.
S8. The impacts of digital technologies on human relations.
S9. The impacts of digital technologies on the future of humanity.
S10. Responsible Artificial Intelligence.
S11. The impact of quantum computing on future technologies.
S12. The impact of digital technologies on geopolitics.
The assessment process includes the following elements:
A) Ongoing assessment throughout the semester
A1. Group debates on issues and problems related to each of the program contents. Each group will participate in three debates throughout the semester. The performance evaluation of each group per debate will account for 15% of each student's final grade within the group, resulting in a total of 3 x 15% = 45% of each student's final grade.
A2. Participation assessment accounting for 5% of each student's final grade.
A3. Final test covering part of the content from the group debates and part from the lectures given by the instructor, representing 50% of each student's final grade.
A minimum score of 9.5 out of 20 is required in each assessment and attendance at a minimum of 3/4 of the classes is mandatory.
B) Final exam assessment Individual written exam, representing 100% of the final grade.
Title: Chalmers, D. (2022). Adventures in technophilosophy In Reality+ - Virtual Worlds and the problems of Philosophy (pp. xi-xviii). W. W. Norton & Company.
Chin, J., Lin, L. (2022). Dystopia on the Doorstep In Deep Utopia – Surveillence State – Inside China’s quest to launch a new era of social control (pp. 5–11). St. Martin’s Press.
Dignum, V. (2019). The ART of AI: Accountability, Responsibility, Transparency In Responsible Artificial Intelligence - How to Develop and Use AI in a Responsible Way (pp. 52–62). Springer.
Howard, P. N. (2020). The Science and Technology of Lie Machines In Lie Machines - How to Save Democracy from Troll Armies, Deceitful Robots, Junk News Operations, and Political Operatives (pp. 1-4; 6-7; 10-18). Yale University Press.
Kearns, M., Roth, A. (2020). Introduction to the Science of Ethical Algorithm Design In The Ethical Algorithm - The Science of Socially Aware Algorithm Design (pp. 1-4; 6-8; 18-21). Oxford University Press.
Authors:
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Title: (Principal - continuação)
Kissinger, H. A., Schmidt, E., Huttenlocher, D (2021). Security and World Order In The Age of AI - And Our Human Future (pp. 157–167, 173-177). John Murray Publishers.
Parijs, P. V., Vanderborght, Y. (2017). Ethically Justifiable? Free Riding Versus Fair Shares In Basic Income - A Radical Proposal for a Free Society and a Sane Economy (pp. 99–103). Harvard University Press.
Pentland, A. (2014). From Ideas to Actions In Social Physics – How good ideas spread – The lessons from a new science (pp. 4–10). The Penguin Press.
Zuboff, S. (2021). O que é capitalismo de vigilância? In A Era do Capitalismo de Vigilância - A luta por um futuro humano na nova fronteira de poder (pp. 21–25). Intrínseca.
***
(Complementar)
Acemoglu, D.; Johnson, S. (2023). What Is Progress? In Power and progress: our thousand-year struggle over technology and prosperity (pp. 1 - 7). PublicAffairs.
Bostrom, N. (2024). The purpose problem revisited In Deep Utopia – Life and meaning in a solved world (pp. 121–124). Ideapress Publishing.
Castro, P. (2023). O Humanismo Digital do século XXI e a nova Filosofia da Inteligência Artificial In 88 Vozes sobre Inteligência Artificial - O que fica para o homem e o que fica para a máquina? (pp. 563 – 572). Oficina do Livro/ISCTE Executive Education.
Gunkel, D. J. (2012). Introduction to the Machine Question In The Machine Question - Critical Perspectives on AI, Robots, and Ethics (pp. 1-5). The MIT Press.
Innerarity, D. (2023). O sonho da máquina criativa. In Inteligência Artificial e Cultura – Do medo à descoberta (pp. 15 – 26). Colecção Ciência Aberta, Gradiva.
Jonas, H. (1985). Preface to the English version of the Imperative of Responsibility In The Imperative of Responsibility: In Search of an Ethics for the Technological Age. (pp. ix - xii). University of Chicago Press.
Nakazawa, H. (2019). Manifesto of Artificial Intelligence Art and Aesthetics In Artificial Intelligence Art and Aesthetics Exhibition - Archive Collection (p. 25). Artificial Intelligence Art and Aesthetics Research Group (AIAARG).
Patel, N. J. (2022, february 4). Reality or Fiction - Sexual Harassment in VR, The Proteus Effect and the phenomenology of Darth Vader — and other stories. Kabuni. https://medium.com/kabuni/fiction-vs-non-fiction-98aa0098f3b0
Pause Giant AI Experiments: An Open Letter. (22 March, 2023). Future of Life Institute. Obtido 26 de agosto de 2024, de https://futureoflife.org/open-letter/pause-giant-ai-experiments/
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Industrial Networks and Supervision
After attending the course, students should be able to:
OA1. Understand the flow of information in office networks with an internet connection;
OA2. Understand the information flow in an industrial automation process, from the sensor to the internet;
OA3. Understand the operation, set up, configure and maintain office computer networks;
OA4. Understand the operation, set up, configure and maintain communication networks for industrial automation;
OA5. Use the OPC (Open Platform Communications) platform to share data at supervisory level and above;
OA6. Build supervision software to support HMI, including synoptics, alarm management and historical data archive.
CP1. Introduction to communication networks based on the OSI (Open Systems Interconnection) model. Architecture of office and industrial automation networks.
CP2. Computer networks (Ethernet, IP, UDP, TCP, sockets).
CP3. Industrial communication networks (Modbus, Profibus).
CP4. Industrial Ethernet (Modbus TCP, Profinet).
CP5. Data sharing and logging using the OPC (Open Platform Communications) platform.
CP6. Supervisory systems (SCADA).
Continuous evaluation consists of interim tests, laboratory projects and/or bibliographic research works.
In case of reproval, the continuous assessment will be replaced by a final written exam.
Title: 4) "Automation, production systems, and computer integrated manufacturing, 5th ed.", Mikell Groover, Pearson, 2019
3) "Fieldbus and Networking in Process Automation", Sunit Kumar Sen, CRC Press, 2014, ISBN 978-1-4665-8677-2
2) "TCP/IP Teoria e Prática", Fernando Boavida e MArio Bernardes, FCA Editora de Informática
1) "Computer Networks", Andrew Tanenbaum, Prentice Hall
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Applied Project in Automation I
At the end of the course, the student should be able to:
LO1: Apply co-creation methodologies in the development of innovative triple sustainable projects (with economic, social and environmental value) in organizations.
LO2: Create empathy with the user and his organization (define needs, obstacles, goals, opportunities, current and desired tasks), define the problem and raise the issues addressed by the project.
LO3: Conduct a systematic literature review and competitive landscape analysis (if applicable), related to the identified problem and the issues raised.
LO4: Identify the digital (including data collection), computational and other resources needed to address the problem.
LO5: Apply already consolidated knowledge of project planning, agile management and project development, within the framework of group work.
LO6: Participate in collaborative and co-creation dynamics and make written and oral presentations, in the context of group work.
S1 Co-creation methodologies based on Design Thinking and Design Sprint
C2 Sustainable Development Goals (SDGs) of the United Nations. Creation of value propositions
S3 Presentation of case studies and digital technologies project topics (product, service or process)
S4 Selecting the project topic and framing it in the organization
S5 Problem space: creating empathy with the user and his organization, defining the problem and its related issues, considering business requirements, customer and user needs, and technology challenges
S6 Application of a systematic literature review methodology and its critical analysis. Competition analysis (if applicable)
S7 Identification of digital resources (including data collection), computational, and other resources required for project development
S8 Application of agile project management methodologies, appropriate to the group work to be developed by the students. Communication of results
Course in periodic assessment, not contemplating final exam, given the adoption of the project-based teaching-learning method applied to real situations. Presentations, demonstrations and discussion will be carried out in groups.
Assessment weights:
R1 Report: Project Topic Definition: 5%
R2 Report: Empathy with the User and the Organization and Definition of the Problem. Its presentation and group discussion: 40%
R3 Report: Systematic Literature Review and Project Development Planning. Its presentation and group discussion: 55%
Title: ·
Brown, T. / HarperCollins, 2009, ISBN-13: 978-0062856623, Change by Design: How Design Thinking Transforms Organizations and Inspires Innovation, 2009, ·, ·
Osterwalder, A., Pigneur, Y., Papadakos, P., Bernarda, G., Papadakos, T., & Smith, A., Value proposition design / John Wiley & Sons., 2014, ·, ·
Knapp, J., Zeratsky, J., & Kowitz, B. / Bantam Press, Sprint: How to Solve Big Problems and Test New Ideas in Just Five Days, 2016, ·, ·
Lewrick, M, Link, P., Leifer, L. / Wiley, ISBN 9781119629191, The Design Thinking Toolbox, 2020, ·, ·
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Title: ·
Ries, E. / capítulos 3 e 4, Penguin Group, Ries, E. (2017), The Lean Startup: How Today's Entrepreneurs Use Continuous Innovation to Create Radically Successful Businesses, 2017, ·, ·
·, Scrum Institute (2020), The Kanban Framework 3rd Edition, 2020, ·, www.scrum-institute.org/contents/The_Kanban_Framework_by_International_Scrum_Institute.pdf acedido em 02/2023
Darrell Rigby, Sarah Elk, Steve Berez / The Scrum Framework 3rd Edition, Doing Agile Right: Transformation Without Chaos HardcoverScrum Institute, 2020, ·, www.scrum-institute.org/contents/The_Scrum_Framework_by_International_Scrum_Institute.pdf acedido em 02/2023
Jeff Sutherland, J.J. Sutherland, Scrum: The Art of Doing Twice the Work in Half the Time, 2014, ·, ·
Project Management Institute / 6th ed. Newton Square, PA: Project Management Institute, A guide to the project management body of knowledge (PMBOK guide), 2017, ·, ·
Gwaldis M., How to conduct a successful pilot: Fail fast, safe, and smart, 2019, ·, https://blog.shi.com/melissa-gwaldis/ acedido em 02/2023
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Accreditations