The information published in this guide corresponds to face-to-face classes and can serve as a guide. Due to the health emergency caused by COVID-19 there may be changes in teaching, assessment and calendars for the academic year. These changes will be reported in the Moodle space of each subject.

GENERAL DESCRIPTION OF THE SUBJECT:Artificial neural networks and genetic algorithms constitute a wide and diverse set of models and techniques for data analysis, inspired by their biological equivalents: the nervous system and genetic evolution. In this course we will show the main models of neural and evolutionay computation, with emphasys on their capacity and use to solve problems of prediction, classification, optimization, clustering and visualization of multidimensional data.