Educational guide 2023_24
Escola Superior de Enxeñaría Informática
Máster universitario en Inteligencia artificial
 Training and Learning Results


Choose A Code Training and Learning Results
  A1 CB6 - Possess and understand knowledge that provides a basis or opportunity to be original in the development and/or application of ideas, often in a research context
  A2 CB7 - Students should be able to apply their acquired knowledge and problem-solving skills in new or unfamiliar environments within broader (or multidisciplinary) contexts related to their area of study.
  A3 CB8 - the complexity of making judgments based on information that, while incomplete or limited, includes reflections on the social and ethical responsibilities linked to the application of their knowledge and judgments.
  A4 CB9 - Students should be able to communicate their conclusions and the ultimate knowledge and rationale behind them to specialized and non-specialized audiences in a clear and unambiguous manner.
  A5 CB10 - That students possess the learning skills that will enable them to continue studying in a manner that will be largely self-directed or autonomous.
Choose B Code Knowledge
  B1 Maintain and extend sound theoretical approaches to enable the introduction and exploitation of new and advanced technologies in the field of Artificial Intelligence.
  B2 Successfully address all stages of an Artificial Intelligence project.
  B3 Search and select useful information needed to solve complex problems, handling with fluency the bibliographic sources of the field.
  B4 Elaborate adequately and with certain originality written compositions or motivated arguments, write plans, work projects, scientific articles and formulate reasonable hypotheses in the field.
  B5 Work in teams, especially multidisciplinary teams, and be skilled in time management, people management and decision making.
Choose C Code Skill
  C1 Understanding and mastering techniques for text processing in natural language
  C2 Understanding and mastery of the fundamentals and techniques of semantic processing of linked, structured, and unstructured documents, and of the representation of their content.
  C3 Understanding and knowledge of the techniques of representation and processing of knowledge through ontologies, graphs, and RDF, as well as the tools associated with them.
  C4 To know the fundamentals and basic techniques of artificial intelligence and its practical application
  C5 Ability to design and develop intelligent systems through the application of inference algorithms, knowledge representation and automatic planning
  C6 Ability to recognize those problems that need a distributed architecture that is not prefixed during the system design, which will be suitable for the implementation of intelligent multi-agent systems.
  C7 Ability to understand the implications of the development of an explainable and interpretable intelligent system.
  C8 Ability to design and develop secure intelligent systems, in terms of integrity, confidentiality and robustness.
  C9 Ability to have a deep knowledge of the fundamental principles and models of quantum computing and know how to apply them to interpret, select, evaluate, assess, model, and create new concepts, theories, uses, and technological developments related to artificial intelligence
  C10 Ability to build, validate and apply a stochastic model of a real system from observed data and the critical analysis of the results obtained
  C11 Understanding and mastery of the main data analysis techniques and tools, both from a statistical and machine learning point of view, including those dedicated to the processing of large volumes of data, and the ability to select the most appropriate ones for problem solving.
  C12 Ability to plan, formulate and resolve all stages of a data project, including understanding and mastery of basic fundamentals and techniques for searching and filtering information in large data collections.
  C13 Knowledge of computer tools in the field of data analysis and statistical modeling, and ability to select the most appropriate for problem solving.
  C14 Understanding and mastery of the main machine learning techniques, including those dedicated to the processing of large volumes of data. Understanding and mastery of basic fundamentals and techniques for searching and filtering information in large data collections.
  C15 Knowledge of computer tools in the field of machine learning, and ability to select the most appropriate for solving a problem.
  C16 Knowledge of the process and tools for data processing and preparation from data acquisition or extraction, cleaning, transformation, loading, organization and access.
  C17 Understand and assimilate the capabilities and limitations of current intelligent robotic systems, as well as the technologies that support them.
  C18 Develop the ability to choose, design and implement strategies based on artificial intelligence to provide robotic systems, both individual and collective, with the necessary capabilities to perform their tasks properly according to the objectives and constraints that arise.
  C19 Knowledge of different application areas of AI-based technologies and their capacity to offer a differentiating added value.
  C20 Ability to combine and adapt different techniques, extrapolating knowledge between different fields of application.
  C21 Knowledge of techniques that facilitate the organization and management of AI projects in real environments, resource management and task planning in an efficient way, taking into account concepts of knowledge dissemination and open science.
  C22 Knowledge of techniques that facilitate the security of data, applications and communications and their implications in different AI application areas.
  C23 Understanding and mastering the basic concepts and techniques of digital image processing.
  C24 Ability to apply different techniques to computer vision problems.
  C25 Knowledge and skills to design systems for detection, classification and tracking of objects in images and video.
  C26 Understanding and mastery of the forms of representation of signals and images according to their data, as well as their fundamental characteristics and their forms of representation.
  C27 Understanding of the importance of the entrepreneurial culture and knowledge of the means available to entrepreneurs.
  C28 Adequate knowledge of the concept of business, its organization and management, and the different business sectors with the aim of providing solutions from Artificial Intelligence.
  C29 To be able to apply knowledge, skills and attitudes to business and professional reality, planning, managing and evaluating projects in the field of artificial intelligence.
  C30 Be able to pose, model and solve problems requiring the application of artificial intelligence methods, techniques and technologies.
Choose D Code Competences
  D1 Express themselves correctly, both orally and in writing, in the official languages of the autonomous community.
  D2 Master the oral and written expression and comprehension of a foreign language.
  D3 Utilizar las herramientas básicas de las tecnologías de la información y las comunicaciones (TIC) necesarias para el ejercicio de su profesión y para el aprendizaje a lo largo de su vida.
  D4 To develop for the exercise of a citizenship respectful of democratic culture, human rights and gender perspective.
  D5 To understand the importance of the entrepreneurial culture and to know the means available to entrepreneurs.
  D6 Acquire life skills and healthy habits, routines and lifestyles.
  D7 Develop the ability to work in interdisciplinary or transdisciplinary teams to offer proposals that contribute to sustainable environmental, economic, political and social development.
  D8 Value the importance of research, innovation and technological development in the socioeconomic and cultural progress of society.
  D9 Have the ability to manage time and resources: develop plans, prioritize activities, identify critical ones, set deadlines and meet them.
Universidade de Vigo            | Reitoría | Campus Universitario | C.P. 36.310 Vigo (Pontevedra) | Spain | Tlf: +34 986 812 000