The aim of this course unit is to be able to guarantee an advanced educational offer, capable of a fast response to any technological, professional or educational change. For this reason, it is composed of an open-ended block of optional subjects. These subjects are continually updated and annually reviewed, also taking into account parameters or criteria related to student demand in previous years.
The Academic Committee will put together the offer of subjects annually. For this reason, this course unit outlines the suggested contents but does not specify individual subjects. The Academic Committee will ensure that each of the proposed subjects covers the specific competences associated with the course unit.
In view of its special characteristics and the fact that it is composed of a very wide-ranging group of subjects in terms of subject matter and faculty, neither the teaching activities nor the assessment systems have been specified as they have for the other course units.
The contents of this course unit are outlined by areas, which should assure the attainment of the planned learning outcomes. The Academic Committee will guarantee that the educational offer is always broad enough to cover all these areas. Some possible contents are, for example, computer science for environmental simulation, web-based GIS development, home automation and intelligent buildings, remote-sensing project management, introduction to space technology, biomedical informatics, voice and speech processing.
This course unit addresses the compute-intensive requirements of many science and engineering processes.
On the one hand, it deals with the most significant techniques used to make these computations, which are illustrated using applications from different branches.
On the other, it examines the techniques associated with the practical implementation of such computations, the interpretation of computation results, as well as the high-performance systems designed to execute scientific and engineering computations from the viewpoint of both the special-purpose hardware and software on which they run. This covers everything from the programming tools to the operating systems and their management services.
This course unit also looks at other associated processes, such as data acquisition or visualization techniques to represent the information output by the computations.
The optional subjects associated with the course unit deal with especially significant knowledge and uses cases, such as fractals.
Dynamical systems and chaos theory provide simulation and data representation tools.
Data instrumentation and acquisition systems are very often the input points for sophisticated simulations.
Computational models for the environment are a typical application in high-performance computation.
Scientific visualization techniques are useful for extracting knowledge from the huge flow of outputs that a high-performance system can generate.
Additionally, this course unit also examines the administration of large scientific computation systems and will take a look at large corporate servers as an example of a less common application field, economics, which is gaining importance within simulation processes.
This course unit is composed of one compulsory and eight optional subjects, aimed at providing a broad-based coverage of the field of knowledge management systems.
The compulsory subject in this course unit is called knowledge management and aims to train students to apply methodologies, methods and techniques for building knowledge management systems, lending attention to knowledge acquisition and representation. A special focus will be the development of ontologies as artefacts for the formal representation of negotiated knowledge, and their application to create and manage corporate memories and for tagging semantic web and linked data web resources. Likewise, methodologies for managing knowledge-based innovation will be reviewed.
This course unit offers optional subjects divided into three major blocks:
Data Mining. Three complementary subjects are taught in this area. Data Mining Processes focuses on describing general-purpose processes commonly used in data mining-related consultancy projects, according to internationally accepted models like CRISP-DM. They cover everything from the understanding and preparation of data sources to the republication of the data output after the application of different techniques. Data Mining: Method and Techniques provides a systematic view of different supervised and unsupervised pattern recognition methods and techniques, illustrating several practical cases of application in different domains (informatics, biomedicine, bioinformatics and neuroscience). Finally, Knowledge Discovery in Databases provides an overview of knowledge discovery process and details some of the leading techniques: association rules, clustering, outlier detection, genetic algorithms and time series processing.
Data Management. Two subjects are taught in this area. Data Management Technologies focuses on aspects related to database administration and database management systems architecture and Data Warehouse: Methods and Techniques focuses on the creation of systems related to the field of business intelligence, covering different methods and techniques related to this area.
Other advanced knowledge representation formalisms and techniques. This block reviews different formalisms and techniques that are useful for building knowledge-based systems and services. It focuses on fuzzy logic as an extension of classical logic, useful for representing degrees of truth in statements and inferences rules; artificial neural networks, as bioinspired models that are a simplified approximation of the brain and are based on scientific knowledge about the structure and operation of the nervous system; and linguistic engineering, as a discipline used to manage knowledge expressed in natural language providing information retrieval techniques and useful for managing multiple languages in knowledge bases.
This course unit deals with the issues of both systems (computers, communications equipment and networks) and services (administrative, distributed and business) development, installation and operation globally and in individual fields.
The compulsory subject of this course unit, called New-Generation Communication Services, focuses on the following four major areas: business network design process analysis through a description of the global panorama of Spanish communications services and technologies used to design commercial services provider IP networks; the evolution and convergence of fixed and mobile networks, as well as the architecture that defines new-generation networks; the use of cryptographic techniques to protect networked communications in businesses and organizations; and the evolution of the Internet routing IP protocol in its transition from version 4 to version 6.
The course unit's optional subjects focus on large systems design issues and particularly on network and systems administration generally. This way, this set of optional subjects deal with both the development of distributed and business applications and the application of information in a corporate environment.
This course unit focuses on systems whose distinctive feature is their high degree of interactivity with users. This ranges from systems with multimedia contents and web systems to complex 3D and virtual reality environments.
From this viewpoint, the compulsory subject of this course unit provides a theoretical and practical view that will enable students to find out about techniques, methodologies and audiovisual and multimedia communication standards, develop 3D graphical models and animations and design and develop interaction mechanisms in 3D virtual environments.
For their part, the optional subjects in the course unit aim to complete the interactive systems and services picture. On the one hand, they cover basic concepts required by any specialist in this area, such as surface modelling and fractals, dynamic systems and chaos, used, for example, to generate 3D scenarios.
On the other hand, they detail the design and construction of systems that are heavily dependent on interaction, such as web systems, analysed from the viewpoint of accessibility; voice-mediated interaction systems, ranging from voice recognition to speech synthesis; and mobile devices, covering both mobile and wireless technology and mobile platforms.
An embedded system is a computer system that is physically part of a larger engineered system that it supervises or controls.
Embedded systems are built into a host of applications ranging from consumer electronics to the control of complex industrial processes.
They are present in almost all facets of society like mobile telephones, cars, traffic control, spacecraft, automated manufacturing processes, energy production, aircraft, etc.
Also, the upsurge of embedded system is on the increase, as more and more machines are manufactured with built-in computer-controlled systems.
A familiar example is the automobile industry, as a mid-range car today includes twenty-odd such gadgets (ABS, airbag, etc).
Another everyday example are new-generation household appliances that have built-in embedded controllers and timers. Nowadays embedded systems have many more applications than conventional or general-purpose computer systems.
This difference is set to grow steadily due mainly to the high growth rate of automation in almost all walks of life. This means that this subject is of primary importance in the training of an informatics engineer.
