Competencies and objectives

 

Course context for academic year 2025-26

This subject represents the students' first contact with the field of Artificial Intelligence (AI). AI is one of the fastest-growing areas in computer science and is becoming increasingly critical in the professional sphere. For future graduates in Computer Engineering, a deep understanding and the ability to apply AI concepts and techniques in solving complex problems are core competencies.

The knowledge acquired in this subject is fundamental for students to successfully tackle a significant portion of the technological and innovation projects they will be involved in during their professional careers. The ability to design, develop, and implement AI-based solutions has become a key differentiator in the job market and a driver of progress in virtually all sectors. This subject lays the groundwork for understanding intelligent systems and information-based decision-making.

 

 

Course competencies (verified by ANECA in official undergraduate and Master’s degrees) for academic year 2025-26

Specific Competences (CE)

  • CE15 : Understand and apply the basic principles and techniques of intelligent systems and their practical application.

 

 

 

Learning outcomes (Training objectives)

No data

 

 

Specific objectives stated by the academic staff for academic year 2025-26

  1. Reflect on the context of Artificial Intelligence and Intelligent Systems by analyzing their problems, techniques, and research lines.
  2. Become familiar with general and specific Artificial Intelligence literature.
  3. Master and use the terminology employed in Artificial Intelligence.
  4. Identify programming languages and development tools specific to Artificial Intelligence.
  5. Understand, know, analyze, and apply advanced search methods for problem-solving.
  6. Understand the methods commonly used in the design of two-player computer games.
  7. Learn about different ways to represent knowledge.
  8. Be familiar with the areas of Artificial Intelligence: Computer Vision and Machine Learning.
  9. Be able to implement Computer Vision and Machine Learning algorithms.
  10. Ability to integrate the knowledge, methods, algorithms, and practical skills of Artificial Intelligence Systems.
  11. Be able to demonstrate the validity of their work through examples and results.
  12. Develop maturity in creating reports and useful documentation for the implemented algorithms.
  13. Develop the ability to autonomously apply and relate interdisciplinary Artificial Intelligence.

 

 

General

Code: 34024
Lecturer responsible:
Aznar Gregori, Fidel
Credits ECTS: 6,00
Theoretical credits: 1,20
Practical credits: 1,20
Distance-base hours: 3,60

Departments involved

  • Dept: SCIENCE OF COMPUTING AND ARTIFICIAL INTELLIGENCE
    Area: CIENCIA DE LA COMPUTACIO, INTEL·LIGENCIA ARTIFICIA
    Theoretical credits: 1,2
    Practical credits: 1,2
    This Dept. is responsible for the course.
    This Dept. is responsible for the final mark record.

Study programmes where this course is taught