Official Code: | L224 |
Acronym: | L.EIC |
2018 | 2019 | 2020 | 2021 | 2022 |
---|---|---|---|---|
- | - | - | 172,5 | 173,8 |
Scheme | Phase | Vacancies |
---|---|---|
General Admissions | 1 | 284 |
This course has two main objectives: the promotion of logical reasoning and methods of analysis and the introduction and theoretical development of a set of concepts that will be fundamental to support the study of other disciplines along this course of studies.
This course aims to acquaint students with the differential and integral calculus, in order to make them able to apply basic tools of mathematical analysis in problem solving related with subjects of Informatics and Computing Engineering. This course also aims to expand students’ knowledge, so that they can address new methodologies applied to engineering problems. At the end of the course, the learning outcomes are: 1. To solve derivatives of functions, draw graphics and study functions in general; 2. To solve integrals and use them in various engineering applications; 3. To use different integration techniques and differential equations; 4. To use and understand approximation concepts based on series and polynomials.
BACKGROUND
Fluency in the process of software development is an essential prerequisite to the work of Informatics Engineers. To use computers to solve problems effectively, students must be competent at reading and writing programs using high-level programming languages.
SPECIFIC AIMS
The global aim of this Unit is to give the student the ability to create algorithms and use a programming language to implement, test, and debug algorithms for solving simple problems. The student will understand and use the fundamental programming constructs, and the functional approach to programming, specifically effect-free programming where function calls have no side-effects and variables are immutable, and contrast it with the Imperative approach.
PERCENT DISTRIBUTION
Scientific component: 40%
Technological component: 60%
The course introduces the general principles of operation design of modern computing systems. Analysis of computer implementation technology (logic circuits and memory) and basic principles of digital information representation enable students to recognize and describe the principles of computer operation, programming languages, and software development.
Background
Logic is the fondament of any scientific reasoning and that is the main reason for its inclusion in the first year of the program. Furthermore, in the case of a Computer Science program, Logic has direct operational relevance in multiple professional aspects.
Specific aims
The goals are the development of skills of rigorous reasoning and in the techniques of discrete mathematics required in several areas of computer science like problem solving, algorithm design and analysis, theory of computing, knowledge representation and security.
Percentual distribution
Scientific component: 100%
Technological component: 0%.
1- BACKGROUND The main aim is to introduce fundamental mathematical concepts by developing the ability to analyze problems and results and also to acquire mathematical precision. These aspects form an educational background for other subjects in the curricula.
2- SPECIFIC AIMS Enhance the students reasoning capacity and knowledge of essential mathematical concepts. The students should acquire solid theoretical and practical training on the main concepts and results of differential and integral calculus of several variables, including the basic theorems of calculus.
3- PREVIOUS KNOWLEDGE Functions and graphs. Differential and integral calculus in R1. Vector algebra. Lines and planes in R3.
4- LEARNING OUTCOMES Knowledge and understanding: Partial and directional derivatives for real-valued and vector-valued functions; gradient vector. The chain rule for real-valued and vector-valued functions including implicit functions. Apply parametric curves and surfaces in R3 to calculate line and surface integrals. Establishment of the relationship between the line integral and the surface integral based on the Green’s, Stokes and Gauss Theorems.
BACKGROUND
The architecture of a computer reflects the current technological advancement, but also sets the limits of its capabilities and performance. Variants of the ARM instruction set are used in the vast majority of current mobile platforms (tablets, cell phones). Both the system architecture and the instruction set have a profound impact on the daily practice of computer engineers.engineers.
SPECIFIC AIMS
The curricular unit "Computer Architecture" aims to develop, combine and apply in an integrated way concepts from the areas of Computer Architecture and Programming Languages. Thus, the curricular unit explores the relationship between the instruction set and low-level programming (assembly language). Mechanisms to support efficient program execution, such as instruction pipelining and jump prediction, will also be addressed. Recognizing that computer architecture goes far beyond the CPU architecture, the curricular unit will also address memory, storage and peripheral subsystems. Upon successful completion of this curricular unit, the student will have acquired the ability to identify and describe the architecture of computing platforms currently in use, as well as the ability to apply assembly programming techniques in the implementation of algorithms.
PERCENT DISTRIBUTION
Allow students to acquire the fundamental knowledge about imperative and object oriented programming in C/C++.
To prepare students about computing theory topics with a special emphasis on formal language topics.
Students will learn about regular languages, regular expressions, non-regular languages, deterministic and nondeterministic finite automata, context-free languages and grammars, deterministic and non-deterministic pushdown automata, and Turing machines, and how to apply these topics to problems.
Students will be able to express computing problems by using formal languages, automata, and Turing machines.
In addition, students will learn how to formally specify computing problems related to formal languages and prove related statements.
At the end of the course, students should be able to:
BACKGROUND
Information Systems (IS) is a key topic in informatics engineering. Databases are data repositories required in any IS. The database course is a key course in the area of IS. The main objective of this course unit is to prepare students to design and develop database systems that meet the users' needs according to the organizational management goals.
SPECIFIC AIMS
This is an introductory course on databases. It is focused on the relational paradigm. It covers the design (UML model and relational normalization), construction (SQL data definition language), querying (SQL data manipulation language) and management (physical organization and query optimization) of relational databases.
PERCENT DISTRIBUTION
Scientific component: 50%
Technological component:50%
Nowadays information processing, storage and transmission are done using electromagnetic phenomena. Therefore, the background knowledge for a computer engineer must include the study of electricity, magnetism and electric circuits.
This course aims to provide the students with basic knowledge on electromagnetism and signal processing. An experimental approach is used with simple on-hands experiments that the students may conduct during the practical sessions, in order to strengthen the subjects covered in the lectures and to gain experience with the use of measuring devices. The Computer Algebra System (CAS) used in Physics 1 is also used in this course to help solve problems and to visualize electric and magnetic fields.
In this training in transversal skills, students are expected to acquire skills in the use of Spreadsheets, in particular MS Excel, for solving management problems and analyzing large volumes of data, namely using data series available in Pordata, INE and others.
This curricular unit is intended for students to develop application design skills using the object-oriented paradigm. Students who pass the course should be able to:
This curricular unit (UC) has as its main objective the acquisition of skills on the fundamental aspects of the connection between Engineering and Sustainability and respective challenges. To that end, this UC addresses fundamental concepts about sustainability in its environmental, economic, and social aspects.
Be able to:
1 – Understand the climatic changes and the need to change the paradigm regarding the exploitation of renewable sources, namely the ones that involve electricity generation and mobility.
2- Understand the different types of available primary energy systems and the ways to convert them into electricity (from large units to microgeneration). Thermal power plants, hydro, wind a solar PV plants.
3- Changes of paradigm in the electric power system involving distributed generation, microgeneration and microgrids.
4 - Smart Grids, concepts and architectures.
5- understand the main components of the electric power system and basic concepts about the structure of the electric power system;
6 - Understand the main regulatory solutions adopted for electric power systems
7 – Understand the main models of electricity markets and their management (energy and ancillary services markets).
The main objectives of this curricular unit are to provide the fundamental knowledge on:
O1- the structure and the operation of a generic operating system;
O2- the use of the Application Programming Interface (API) of a real operating system.
This course on Design of Algorithms (DA) aims at complementing and further develop the implementation skills regarding the analysis and synthesis of computer algorithms, previously explored (in an introductory fashion) in the algorithms and data structures (AED course. This DA class introduces various algorithmic techniques of wide applicability, such as brute-force, backtracking, divide-and-conquer, greedy and dynamic programming, ubiquitous in real life algorithmic implementation solutions. We will also introduce the complexity classes of P and NP and the concept of polynomial-time reduction. As a practical application, we will also introduce the notion of approximation algorithms. Lastly, we will also cover the algorithmic techniques used in optimization problems via linear (real and integer) programming.
This course aims to acquaint students with the engineering and management methods necessary for the cost-effective development and maintenance of high-quality complex software systems.
1- Introduction
I/O devices are an integral part of a computer, without which the usefulness or the ease of use of a computer would be significantly lower. The importance of I/O devices in computer-based systems has increased since the first generation of computers, and it continues up to these days with the ever increasing use of computers in embedded systems. However, programming of I/O devices using their programatic interface requires specific knowledge and techniques.
2- Specific Objectives
This course unit aims to endow students with the knowledge and the skills required to:
3- Percentual Distribution
Scientific: 30%
Tecnological: 70%
The goal is providing the students with skills in the most significant languages and Web technologies in the current technological context or that were breakthroughs in the Web's evolutionary process.
This course unit aims to provide students with an integrated vision of the basic concepts and techniques of Statistics.
The main goals sought for the students are for them to get contact, practice and experience with the following topics:
In this training in transversal skills, students are expected to acquire skills in the use of Spreadsheets, in particular MS Excel, for solving management problems and analyzing large volumes of data, namely using data series available in Pordata, INE and others.
The LBAW curricular unit aims to consolidate the subjects exposed in the curricular units of databases and web languages and technologies. This curricular unit offers a practical perspective on two central areas of computer engineering.
This course unit is intended to provide students with the ability to design and develop information systems accessible through the web and supported by database management systems.
This curricular unit (UC) has as its main objective the acquisition of skills on the fundamental aspects of the connection between Engineering and Sustainability and respective challenges. To that end, this UC addresses fundamental concepts about sustainability in its environmental, economic, and social aspects.
Be able to:
1 – Understand the climatic changes and the need to change the paradigm regarding the exploitation of renewable sources, namely the ones that involve electricity generation and mobility.
2- Understand the different types of available primary energy systems and the ways to convert them into electricity (from large units to microgeneration). Thermal power plants, hydro, wind a solar PV plants.
3- Changes of paradigm in the electric power system involving distributed generation, microgeneration and microgrids.
4 - Smart Grids, concepts and architectures.
5- understand the main components of the electric power system and basic concepts about the structure of the electric power system;
6 - Understand the main regulatory solutions adopted for electric power systems
7 – Understand the main models of electricity markets and their management (energy and ancillary services markets).
The Functional Programming and Logic Programming paradigms present declarative approaches to programming, based on formal reasoning processes, which are more appropriate to the resolution of some types of problems.
Objectives: become familiar with the Functional Programming and Logic Programming paradigms. Develop skills in abstract reasoning and declarative problem representation.
Provide the students with basic training in Computer Networks - knowledge of the essential architectural concepts and principles, the more used technologies and solutions and also the main standards. Furthermore, the student must be capable of analyzing and evaluating the performance of different types of systems and communication networks.
Provide concepts that allow to:
BACKGROUND Computer graphics has been stated and is today a very important component in the whole human-computer interaction ambience. However, its applicability goes far beyond, having nowadays a prominent position in major industries such as the cinema and electronic games. Also, in technology and science it plays an irreplaceable role allowing the visualization of phenomena, often linked to simulation and virtual reality techniques. In this course, the approach to computer graphics is made under a Top-Down philosophy, starting with the subjects most related to 3D (image synthesis, modelling) and ending with a visit to several most basic algorithms in 2D. The 3D components of the programme are accompanied, in practical lessons, with exercises based on the usual technologies, like OpenGL and WebGL.
SPECIFIC AIMS -Transmit knowledge of concepts, techniques, algorithms, computer graphics technologies and architectures. -Strengthen the theoretical knowledge with practical application, through the implementation, testing and evaluation of algorithms discussed in theory.
PERCENTAGE DISTRIBUTION
-Scientific Component: 50%
-Technological Component: 50%
This course provides a set of subjects (topics) that are the core of the Artificial Intelligence and Intelligent System area. The main objectives are:
1. Understand the fundamentals of Artificial Intelligence and Intelligent Systems, what characterizes and distinguishes them and their applicability.
2. Being able to design and implement Agents and Multi-Agent Systems to solve different problems.
3. To learn heuristic and systematic methods of problem solving, with and without adversaries and optimization algorithms.
4. To learn methods of acquisition, representation and reasoning with uncertain knowledge using different formalisms.
5. To understand the basis of natural language processing and its applications.
6. Know and be able to apply learning algorithms with different paradigms (supervised, unsupervised, reinforcement, evolutionary, deep learning) and algorithms (decision trees, neural networks, SVMs).
7. To understand advanced topics in Artificial Intelligence and be able to formulate a vision into the future of AI.
8. To develop simple but complete projects using AI techniques.
Percentual Distribution: Scientific component: 50%; Technological component: 50%