LG1 Understand the concept of vector space, apply properties and determine a basis.
LG2 Classify sets of vectors with respect to linearity.
LG3 Represent points and vectors and calculate distances.
LG4 Operate with vectors and identify the relative position of planes and lines.
LG5 Determine equations of the line and plane.
LG6 Calculate and interpret inner and outer products.
LG7 Parametrize curves and calculate the normal and tangent vectors.
LG8 Operate with matrices, solve systems of linear equations by matrix calculation and interpret geometrically.
LG9 Calculate inverse matrix and determinant.
LG10 Understand the linear transformation between finite dimensional vector spaces.
LG11 Understand the necessity of complex numbers and the algebraic and polar forms.
LG12 Operate with complex numbers and apply Moivre's formulas and Euler's identity.
LG13 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. Measures.
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 regular 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:
- Periodic assessment: 1 midterm test (14%) + 11 weekly mini-tests (11x2%) + weekly autonomous work (AW) activities (12%) + construction of a glossary in group work (12%) + final test (40%); a minimum score of 7 values (scale 1-20) is required in each of the midterm and final tests
- Assessment by Exam (100%), in any of the exam periods, with individual written test.

After successfully attending the curricular unit, students should be able to:
OA1: Components and laws
OA2: Analysis of electrical circuits
OA3: 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

Periodic assessment:
Laboratory and Reports (40%) + Written test (60%) (1st exam period)
Minimum grade in the laboratory and report: 8
Minimum test score: 8
for a final average greater than or equal to 9.5 values

Assessment by exam (100% written test) in the 1st, 2nd and special exam period.
The written test will include, in addition to theoretical content, theoretical and practical content related to the laboratory work carried out.

The possibility of carrying out periodic assessment is subject to:
- Attendance in laboratory classes (100%) *,
- Attendance in theoretical classes at least (50%),
- Attendance in theoretical and practical classes at least (50%).
*If, for objective reasons, absences are recorded in the laboratory, a way to recover the missing laboratory will be agreed with the teacher.

Students will acquire the following knowledge:
LO1 - Develop a solid understanding of the essential concepts of one-dimensional and two-dimensional motions, enabling students to analyze causes, apply these principles in practical contexts, and prepare them for future studies.
LO2 - Understand and apply Newton's laws to predict and explain the motion of a body, applying this knowledge to the study of gravitational forces.
LO3 - Comprehend the concepts of electricity and magnetism, analyze practical problems, and understand how energy is conserved and transferred in an electrical system.

CP 1. Models, unities and calculus
CP 2. Unidimensional movement
CP 3. Bidimensional movement
CP 4. Newton's laws
CP 5. Gravitation
CP 6. Electrical quantities and Conservation of energy
CP 7. Faraday's law of induction

Two written tests with a weight of 60% in the final grade.
Autonomous student work with a weight of 10% in the final grade and the submission of reports with a weight of 30% in the final grade.
Minimum grade of 9.5 points in the sum of all evaluation components.

After successfully attending the curricular unit, students should be able to:

OA1. Know the different data formats.
OA2. Know the complete data 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 for a given problem.

CP1. Introduction to Data Analysis
CP2. Introduction to R and RStudio
CP3. Knowledge of problems in data analysis with examples
CP4. The complete cycle of data analysis
CP5. Data and data format
CP6. Data preparation
CP7. Odds; Descriptive Statistics and Exploratory Analysis
CP8. Data visualization
CP9. Modeling and different types of machine learning problems
CP10. Model evaluation methods
CP11. Reporting and publishing results

PERIODIC assessment results from: online exercises, without a minimum grade, after each class (20%); two individual tests - a mid-term test and another at the end of the semester (30%); and a group work (maximum of 3 students) in R with preparation of a report and oral presentation (50%).

Students who obtain a final grade above 9.5 are approved.

LO1: Know the main theories, concepts and problematics 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 of the digital transition;
LO4: Explore cases, strategies and application methods to understand the real impacts of the digital transition on professions, companies and organizations.

S1. Is work different today than in the past? S2. How has theory looked at technology?
S3. What technologies for the future?
S4. What future for work?
S5. How intelligent is artificial intelligence?
S6. Where does precarity begin?
S7. Do platform workers need employment contracts?
S8. Who is to blame when the machine goes wrong?
S9. Are digital technologies changing the relationship between unions and companies?
S10. Does teleworking make people happier?
S11. Portugal and the digital transformation?

"Periodic evaluation:
Making of an Inverted class class. Each Inverted Class represents 20% of the final mark, with a minimum mark of 8. Weekly question and answer which represents 10% of the final mark, with a minimum mark of 8. An individual assignment, spread over 3 assessment periods, with a minimum mark of 8 in each, representing 35% of the final grade. A group assignment, representing a total of 35% (10% group presentation and 25% written assignment), with a minimum mark of 8. The average grade must be equal to or greater than 9.5.

Assessment by exam (First season 1 if the student chooses, Second Season and Special Season): In-person exam (100% of the final grade)."

LG1 Understand the concept of function and the associated properties.
LG2 Calculate limits, solve indeterminate forms and interpret graphs.
LG3 Calculate derivatives and interpret results in context of problems.
LG4 Determine linear and higher order Taylor's approximations and apply numerical methods.
LG5 Apply the derivative of composite and inverse functions.
LG6 Know the graph of elementary functions and apply transformations to the graph.
LG7 Understand the concepts of succession and numerical series for Riemann sums approach.
LG8 Calculate limits of sequences and, relative to series, find out the existence of sum.
LG9 Understand the definition of integral as the limit of Riemann sums.
LG10 Calculate antiderivative and apply them to calculate integrals.
LG11 Apply integrals to calculate areas, lengths and mean values.
LG12 Articulate different approaches to a given content: graphical, numerical and algebraic.

PC1 Concepts of real variable functions. Polynomial, rational, trigonometric and exponential functions.
PC2 Limits and indeterminate forms. Asymptotic line. Continuity at a point.
PC3 Average and instantaneous rates of change. Derivative at a point and tangent line. Differential. Rules of derivative calculus.
PC4 Monotonicity and concavity intervals.
PC5 Composite function and chain rule. Inverse function and derivative.
PC6 Logarithm and inverse trigonometric functions.
PC7 Taylor linear and higher order approximations. Lagrange rest.
PC8 Sequences. Monotonicity and convergence. Minorants and majorants.
PC9 Numerical series, partial sums and sum. Error and convergence criteria.
PC10 Riemann definite integral. Fundamental theorem of calculus and antiderivatives.
PC11 Integration by parts and change of variables. Decomposition into simple fractions.
PC12 Applications of the integral (area, length).
PC13 Improper integral and convergence.

Approval with classification not less than 10 points (1-20 scale) in one of the following modalities:
- Periodic assessment: 2 mini-tests (MT) on classes (15% each) + Test on the first examination period (40%) + weekly tasks (10%) + work done in groups of 2-3 students (20%).
The average of the classifications of mini-tests ( (MT1+MT2)/2 ) must be greater or equal to 7 points.
The classification in the final test must be greater or equal to 7 points.
There is the possibility of oral assessment.

or
- Assessment by Examination (100%), in any of the examination periods.

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.

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%).

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.

Learning Outcomes:
LO1. Develop oral communication skills
LO2. Improve body expression
LO3. Master the art of using the vocal apparatus
LO4. Learn performance techniques

Compatibility with the Teaching Method:
The course combines theory and practice, providing students with an immersive experience in the world of public performances with theatrical techniques. The teaching method is interactive and participatory, encouraging students to put into practice the concepts learned through individual and group exercises.

The knowledge acquired involves both theatrical theory and specific oral communication techniques. Participants will learn about the fundamentals of vocal expression, character interpretation and improvisation, adapting these skills to the context of public presentations

S1 - Preparation for presentation (3 hours)
S2 - Non verbal communication (3 hours)
S3 - Introduction to using the vocal apparatus (3 hours)
S4 - Introduction to the term Performance (3 hours)

Modality of continuous assessment:
Practical Presentations (50%): Participants will be assessed based on their public presentations during the course. Criteria such as clarity of communication, vocal and body expression, use of theatrical techniques and performance will be considered. Presentations may be individual or group presentations, depending on the activities proposed.

Exercises and Written Assignments (50%): In addition to the practical presentations, participants may be asked to complete exercises and written assignments related to the content covered in each module. These may include reflections on learned techniques, analysis of case studies, answers to theoretical questions or even the creation of presentation scripts. These activities will help to assess participants' conceptual understanding.

To conclude the curricular unit in the modality of continuous assessment the student must be present in 75% of the classes.
Although not recommended, students may opt for final assessment by written and oral examination (100%).

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)

Modality of continuous assessment:
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, 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, quality of the solutions and collaboration among group members.

To conclude the curricular unit in the modality of continuous assessment the student must be present in 75% of the classes.
Although not recommended, students may opt for final assessment by written and oral examination (100%).

"LO1. Knowledge about the structure, language, ethical and normative procedures for the elaboration of academic texts.
LO2. Skills to use generative algorithms to assist the elaboration of academic work.
LO3. Skills in analysing and scrutinising the independence, relevance and reliability of AI generated data.
LO4. Overall abilities to recognise the ethical and civic implications underlying the access, sharing and use of AI tools in an academic context."

"S1. Introduction to Academic Writing and generative algorithms (3h)
S2. Procedures for planning and constructing argumentative texts with the aid of AI (3h)
S3. Critical analysis of texts produced: identification and referencing of data sources and analysis of their relevance in the ligth of the objectives of the academic work (3h)
S4. Opportunities and risks of AI use: good practice guide for accessing, sharing and using AI tools in an academic context (3h)"

"Modality of continuous assessment:
Class participation: Class participation: assesses students' attendance, involvement and individual contributions to class discussions and activities (20%).
Group work will require students to form groups to revise and edit academic texts between themselves, using generative algorithms. Assessment will be based on the quality of the revisions, edits and feedback provided (40%).
Individual report: with an in-depth reflection on the civic and ethical questions posed by the use of AI tools as an aid to academic writing (40%).
There is a required minimum of 7 values in each component that is graded.

To conclude the curricular unit in the modality of continuous assessment the student must be present in, at least, 75% of the classes.
Although not recommended, students may opt for final assessment by written and oral examination (100%).

In addition to the practical presentations, students will be asked to carry out exercises and written tasks related to the content covered. These may include: reflecting on techniques learnt, analysing case studies, answering theoretical questions or even creating presentation scripts. These activities will help to assess conceptual understanding of the content taught.

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%.

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.

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: Understand the syntax of the Python programming language.
LO4: Develop programming solutions for problems of simple complexity.
LO5: Explain, execute, and debug code fragments developed in Python.
LO6: Interpret the results obtained from the execution of code developed in Python.
LO7: Develop programming projects.

S1. Introduction to Programming: Logical sequence and instructions, Input and output of data, Constants, variables, and data types, Logical, arithmetic, and relational operations, Control structures
S2. Procedures and Functions
S3. References and Parameters
S4. Integrated Development Environments
S5. Syntax of the programming language
S6. Objects and object classes
S7. Lists and Lists of Lists
S8. File Manipulation

The course unit follows a project-based assessment model due to its highly practical nature and does not include a final exam.
Students are evaluated based on the following parameters:
A1: Programming tasks validated by the instructors (10%), with a minimum grade of 9.5 out of 20 in the average of the tasks.
A2: Individual Project with theoretical-practical discussion (40%), with a minimum grade of 8.5 out of 20.
A3: Group Project with theoretical-practical discussion (50%), with a minimum grade of 8.5 out of 20.

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.

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.

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%).

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.

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%

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

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

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.

Being a course with a very practical and applied nature, it follows the 100% project-based assessment model, where there is no final exam. Assessment takes place throughout the semester and consists of 3 assessment blocks (AB), each consisting of one or more assessment moments. The distribution is as follows:

- AB1: 1st tutorial + 1st mini-test [20% 1st tutorial + 10% 1st mini-test = 30%]
- AB2: 2nd tutorial + 2nd mini-test [20% 2nd tutorial + 10% 2nd mini-test = 30%]
- AB3: 1 final project [40%]

The tutorials consist of individual oral discussions to assess the students' performance in the projects proposed for the tutorial.

The mini-tests evaluate the theoretical knowledge applied to each of the projects also assessed during the tutorial.

The final project consists of developing 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 Epoch and 2nd Epoch can be used for all the assessments.
Attendance at classes is not mandatory.

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%).

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%

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%.

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.

The student who successfully completes this UC will be able to:
OA1. Identify the main contemporary issues and debates;
OA2. Analyze current issues and debates in a reasoned manner;
OA3. Identify the implications of technological change and digitalization in economic, social, cultural and environmental terms;
OA4. Understand the role and the importance of technology in the challenges of contemporary societies;
OA5. Explore the boundaries between technological knowledge and social science knowledge;
OA6. Develop forms of interdisciplinary learning and critical thinking.

S1. Debates XXI: technological change and contemporary societal challenges.
S2. Digital transition: meaning and implications.
S3. Technology, social change and inequalities.
S4. Environment and transition towards to sustainability.
S5. Globalization, financialisation and development.
S6. Capitalism and democracy.
S7. Migrations and multiculturality.

The periodic assessment process comprises the following elements:
1. Preparation and presentation (class) of a group work on technological change and society (40%).
2. Test (60%).
The final assessment corresponds to 1st and 2nd phase exams (100% of the grade).