K3: Determine the best way to represent knowledge, using logic-based formalisms, applying the fundamentals of data management and processing, including storage and processing, metadata management, efficient management of continuous flows and governance of complex data systems, ensuring privacy, security and integrity of data in accordance with the rules and regulations in force, with high ethical rigour, social responsibility and taking into account its feasibility in problems involving any kind of processing of large volumes of data. K6: Determine the fundamental principles and models of computation, the theoretical foundations of programming languages and associated lexical, syntactic and semantic processing techniques, algorithmic strategies and the paradigms and techniques of intelligent systems and computational learning necessary for the resolution of problems in any field of application, such as computation, perception and performance in intelligent environments, acquisition, formalisation and representation of human knowledge, interactive and complex information presentation systems, human-computer interaction, computational learning environments and automatic extraction of information or knowledge from large volumes of data.. K-OPT1: Relate concepts and fundamentals of specific application environments to artificial intelligence technologies for problem-solving in organisations according to their usual processes and standards C3: Assess which data mining and machine learning methods are best suited to extract valuable information for organisations that takes into account potential data quality issues, algorithmic bias or data bias.

- Introduction to Neurophysiology - Neural Modelling - Brain Imaging - Brain Networks - Brain-Computer Interfaces - Brain-Machine Interfaces - Managing Injuries of the Nervous System

A1: MASTER CLASS. Lecture of a theoretical nature given by the teacher in the regular classroom. He/she can use different technologies to support his/her expository activity such as presentations, videos, etc. and carry out formative activities of analysis, reflection, debates on the information provided, etc. 100% de presencialidad / A2: PROBLEM SOLVING AND CASE STUDIES IN THE CLASSROOM. Practical activity (guided problems, tutorials or group work) in the regular classroom. It can use different support technologies in its expository activity such as presentations, videos, etc. and perform training activities of analysis, reflection, discussions of the information provided, etc. but does not require a specific infrastructure. 100% de presencialidad / A2bis: PROBLEM SOLVING IN A COMPUTER ENVIRONMENT: Activity similar in nature to A2 but performed in a computer environment with specific hardware and software. 100% de presencialidad / A3: STUDENT'S INDIVIDUAL WORK: This is the student's individual work outside the ¿classroom¿ and consists of self-study, solving exercises and problems, individual work, etc. 0% de presencialidad / A4: LABORATORY SESSIONS. Practical activities that students carry out in a laboratory environment, using the necessary specific resources and under the supervision and control of the professor. In these sessions the maximum number of students per group is 20 students. 100% de presencialidad / A5: FINAL EXAM Consists of an objective test whose purpose is to verify the acquisition of the knowledge, skills and abilities of the course. 100% de presencialidad M1: SEMINARS AND LECTURES SUPPORTED BY COMPUTER AND AUDIOVISUAL AIDS. / M2: PRACTICAL LEARNING BASED ON CASES AND PROBLEMS, AND EXERCISE RESOLUTION. / M3: INDIVIDUAL AND GROUP OR COOPERATIVE WORK WITH THE OPTION OF ORAL OR WRITTEN PRESENTATION. / M4: INDIVIDUAL AND GROUP TUTORIALS TO RESOLVE DOUBTS AND QUERIES ABOUT THE SUBJECT.