Bachelor’s Degree in Artificial Intelligence

General Data

ECTS Credits: 240
Fields of study: 06 Information and Communication Technologies (ICTs)
Professional Practices: Yes
Available for Mobility Students: Yes

Coordination

Lourdes Borrajo Diz
(+34) 988387028
lborrajo@uvigo.gal

Presentation

The Bachelor’s Degree in Artificial Intelligence (Grado en Intelixencia Artificial) addresses the growing global demand for specialists in intelligent computing systems.

Students study foundational and advanced topics in:

  • Artificial intelligence methods such as machine learning, reasoning, and knowledge representation
  • Intelligent information systems and their practical implementation
  • Data handling and processing, including big data techniques
  • Human‑computer interaction, perception, and real‑time intelligent systems
    The curriculum is interuniversitary in Galicia, with the first two years of courses common across the region’s universities and the latter years specialized at UVigo with a focus on Intelligent Information Systems (Sistemas de Información Inteligentes).

Graduates are prepared for careers in areas such as:

  • AI and machine learning engineering
  • Data science and analytics
  • Intelligent system design and deployment
  • Software development for AI applications
  • Automation, robotics, and human‑computer interfaces
    Their training equips them to work in both industry and research contexts where intelligent technologies are developed or applied.

Main Objective

The programme provides broad, deep, and multidisciplinary training to prepare professionals capable of designing, developing, and applying intelligent systems and services that are increasingly impacting diverse areas of society and technology — from automation and data analysis to decision‑making and human‑machine interaction.

Competencies

Technical and AI-Specific Competencies

  • Design, implement, and evaluate intelligent systems including machine learning, knowledge representation, reasoning, and problem-solving algorithms.
  • Develop and apply data-driven models for prediction, classification, and decision-making.
  • Design, implement, and maintain intelligent information systems and software applications.
  • Apply robotics, natural language processing, and computer vision techniques where relevant.

Analytical and Problem-Solving Competencies

  • Apply mathematical, statistical, and computational methods to solve complex AI problems.
  • Analyze large datasets and extract meaningful patterns and insights.
  • Evaluate and optimize performance, reliability, and scalability of intelligent systems.

Project Management and Professional Competencies

  • Plan, manage, and execute AI projects in industrial, research, or service contexts.
  • Work effectively in multidisciplinary teams, collaborating with engineers, data scientists, and domain experts.
  • Communicate technical concepts and results clearly to both specialists and non-specialists.
  • Apply ethical and legal principles in the design and deployment of AI systems, including data privacy and algorithmic fairness.

Research and Innovation Competencies

  • Conduct applied and theoretical research in artificial intelligence and related computing fields.
  • Integrate emerging technologies and innovative approaches in intelligent system design.
  • Critically assess AI methods and tools to select the most appropriate solutions for given problems.

Transversal and Digital Competencies

  • Use modern software development tools, programming languages, and AI frameworks effectively.
  • Engage in lifelong learning to stay updated with rapid technological advances.
  • Apply communication, teamwork, and project management skills across diverse professional contexts.

Structure and Distribution of Credits

  • Basic Training Subjects: 60 ECTS
    Foundational courses in mathematics, programming, physics, and introductory computing concepts.
  • Compulsory/Core Subjects: 138 ECTS
    Includes subjects in artificial intelligence methods, machine learning, data analysis, algorithms, intelligent information systems, robotics, computer vision, and human-computer interaction.
  • Elective Subjects: 24 ECTS
    Allows students to specialize in areas such as deep learning, natural language processing, or intelligent systems applications.
  • Final Degree Project (TFG): 18 ECTS
    An individual project integrating theoretical knowledge and practical AI application skills.
Type of CreditsECTS Credits
Basic Training Subjects60
Compulsory/Core Subjects138
Elective Subjects24
Final Degree Project (TFG)18
Total240 ECTS

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