Programming skills: - Programming - Systems Programming - Systems Architecture

The main objective of this course is to analize the concept of "intelligence" in information and communication systems and study the main techniques that allow to incorporate "intelligent" behaviours in them. At the end of the course, the students have to study the fundamentals of Artificial Intelligence, the impact of the incorporation of intelligent mechanisms in software and hardware systems and the areas where these technologies may bring the most significant advances. Competences or specific skills that the student must acquire include: - Knowledge of the main concepts and techniques of Artificial Intelligence. - Capacity to analyze the application and feasibility of different AI techniques to solve a specific problem, and evaluate the impact on real-world systems (analysis, abstraction, problem solving and capacity to apply theoretical concepts). In addition, the student will acquire general skills: - Ability to work in teams and share and distribute the work load to deal with complex problems. - The student must learn how to plan the development of a system with a certain degree of complexity. - The student must learn how to search for useful information in different sources for the design and implementation of a given engineering problem.

CB1: Students have demonstrated possession and understanding of knowledge in an area of study that builds on the foundation of general secondary education, and is usually at a level that, while relying on advanced textbooks, also includes some aspects that involve knowledge from the cutting edge of their field of study CB2: Students are able to apply their knowledge to their work or vocation in a professional manner and possess the competences usually demonstrated through the development and defence of arguments and problem solving within their field of study. CG3: Knowledge of basic and technological subject areas which enable acquisition of new methods and technologies, as well as endowing the technical engineer with the versatility necessary to adapt to any new situation. ETEGITT4: Ability to construct, develop and manage telecommunication networks, services, processes and applications, such as capture, transport, representation, processing, storage, and multimedia information presentation and management systems, from the point of view of telematics services. ETEGITT5: Capacity to apply techniques on which telematics networks, services and applications are based. These include systems for management, signaling and switching, routing, security (cryptographic protocols, tunneling, firewalls, payment authentication mechanisms, and content protection),traffic engineering(graph theory, queuing theory and tele-traffic), tarification and service reliability and quality, in fixed, mobile, personal, local or long distance environments, with different bandwidths, including by telephone and data. ETEGITT6: Ability to design network architectures and telematics services. RA1: Knowledge and understanding of the general fundamentals of engineering, scientific and mathematical principles, as well as those of their branch or specialty, including some knowledge at the forefront of their field. RA3: Design. Graduates will have the ability to make engineering designs according to their level of knowledge and understanding, working as a team. Design encompasses devices, processes, methods and objects, and specifications that are broader than strictly technical, including social awareness, health and safety, environmental and commercial considerations RA4: Research. Graduates will be able to use appropriate methods to carry out detailed research and studies of technical aspects, commensurate with their level of knowledge. The research involves bibliographic searches, design and execution of experiments, interpretation of data, selection of the best proposal and computer simulation. May require consultation of databases, standards and security procedures. RA5: Applications. Graduates will have the ability to apply their knowledge and understanding to solve problems, conduct research, and design engineering devices or processes. These skills include knowledge, use and limitations of materials, computer models, process engineering, equipment, practical work, technical literature and information sources. They must be aware  of all the implications of engineering practice: ethical, environmental, commercial and industrial.

1. Concepts and history of Artificial Intelligence 2. Problem solving and search strategies 2.1. Concepts 2.2. Uninformed search strategies 2.3. Heuristic search strategies 2.4. Game theory 3. Knowledge Based Systems (KBS) and expert systems 3.1. Knowledge representation 3.2. Fundamentals of formal logic, logic programming and inference systems 3.3. Management of uncertaintity 3.4. Agents 4. Machine learning 4.1. Concepts of machine learning, Data Science/Analytics/Mining 4.2. Techniques, tools and applications 4.3. Supervised learning 4.4. Unsupervised learning 4.5. Other 5. Linguistic Engineering (Natural Language Processing)

Learning activities include: - Theoretical lectures, individual and group tutoring sessions, student presentations, student personal work, including study, tests and exams; focused on the acquisition of the specific coginitive competences of the course - Practical lectures, lab sessions, individual and group tutoring sessions, including study, tests and exams; focused on the development of the specific instrumental competences and most of the general competences, such as analysis, abstraction, problem solving and capacity to apply theoretical concepts - Development and presentation in class of a group project, focused on any of the topics that are included in the course, whose objective is to check that the student is able to develop (design, implement and validate) a software system that includes one or several Artificial Intelligence components to solve a given engineering problem