The students are expected to have basic knowledge of - Calculus - Programming skills - Statistics

- Know the basic techniques of text pre-processing. - Use software tools for pre-processing text. - Know the techniques of topic modeling. - Use topic modeling software tools in corpus of documents. - Use topic models for information retrieval in corpus of documents. - Learn how to train models of semantic representation in a vector space. - Learn to train language models using recursive neural networks. - Know basic translation structures based on recursive neural networks. - Use optimization tools to build language models with recursive neural networks.

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. RA1: To acquire the knowledge and understanding of the general basic fundamentals of engineering, as well as, in particular, of multimedia communications networks and services, audio and video signal processing, room acoustic control, distributed multimedia systems and interactive multimedia applications specific to Sound and Image Engineering within the telecommunications family. RA5: Be competent to apply the knowledge acquired to solve problems and design audiovisual networks and services, to configure their devices, as well as to deploy adaptive, personal audiovisual applications and services on them, bringing network intelligence to the value for the user, maximising the potential of multimedia networks and services in the different social and economic spheres, knowing the environmental, commercial and industrial implications of the practice of engineering in accordance with professional ethics.

- Document preprocessing techniques - Automatic summarization. Clustering techniques - Text embeddings - Topic Modeling - Neural Networks and Recurrent Neural Networks - Text processing with neural networks

All sessions will be theoretical / practical, in which each session introduces a theoretical aspect and is developed using specific software libraries. It is important to highlight that these classes will require initiative and personal and group work on the part of the student (there will be concepts that they will have to study personally based on some indications, particular cases they will have to develop, etc.) These practices, on the one hand, allow the student apply the theoretical knowledge acquired to try practical solutions, so that they can consolidate and critically analyze such knowledge. ECTS credits include in all cases the corresponding part of personal or team work by the student.