Objectives and competences

This master's degree provides a solid foundation and advanced knowledge of artificial intelligence, which is one of the most important and promising fields in information technology. The aim is to train highly qualified professionals who have the knowledge and values required to solve complex problems, hold positions of responsibility in companies, and carry out theoretical and practical research in artificial intelligence.
This interuniversity master's degree provides a comprehensive, innovative perspective of this field and its application to real situations. The contents are focused on knowledge, representation and reasoning, automatic learning, natural language processing, autonomous agents, robotics and artificial vision and visualization. It focuses on functional techniques to design and construct intelligent systems, so that graduates of this course can apply their skills in a wide range of areas.

The course is aimed at anyone with a background in engineering (computer, electronic, etc.), cognitive sciences, mathematics, physics, linguistics or philosophy.

Basic information

Type Master's degree
Faculty or school Faculty of Mathematics and Computer Science
Branch of knowledge Computer and systems engineering
Mode of delivery Presencial
Credits 90
Number of places available 50
Length of course 2 academic years
Language(s) of instruction English 
Coordination MAITE LOPEZ SANCHEZ
Course details Indicators
Lead to doctoral studies Yes
Admission for applicants not holding a degree qualification No
Main university information Master's degree course homepage
Interuniversity Yes
Main university Universitat Politècnica de Catalunya
Universities
  • Universitat Politècnica de Catalunya
  • Universitat Barcelona
  • Universitat Rovira i Virgili
Bridging courses No

Objectives and competences

Objectives

Competences

Access and admission

Applicant profile and access requirements

Recommended applicant profile

Access requirements and conditions

General requirements
In accordance with Article 16 of Royal Decree 1393/2007, of 29 October, students wishing to be admitted to a university master's degree must hold one of the following qualifications:

  • Official Spanish university degree.

  • A degree issued by a higher education institution within the European Higher Education Area framework that authorizes the holder to access university master's degree courses in the country of issue.

  • A qualification issued by an institution outside the framework of the European Higher Education Area. In this case, applicants must request homologation of the degree to its equivalent official Spanish university qualification or obtain express approval from the University of Barcelona, which will conduct a study of equivalence to ensure that the degree is of a comparable level to an official Spanish university qualification and that it grants access to university master's degree study in the country of issue. Admission shall not, in any case, imply that prior qualifications have been recognized as equivalent to a Spanish master's degree and does not confer recognition for any purposes other than that of admission to the master's degree course.

Pre-enrolment

Calendar

La preinscripció es realitza a la universitat coordinadora del màster.


Més informació

Required documentation

Selection criteria

Notification

Enrolment

As a general rule, at the UB you will be required to enrol online. Remember that you can lose your place if you do not enrol on the day you have been assigned

Course curriculum

Subjects and course plans

Distribution of credits

Type ECTS
Compulsory 33
Optional 39
Compulsory placements 0
Compulsory final project 18
TOTAL 90

List of subjects

Subject Type Language Credits
Specialization: Artificial Intelligence
Advanced Human Language Technologies Optional 5
Advanced Machine Learning Techniques Optional 5
Advanced Natural Language Processing Optional 5
Advanced Topics in Computational Intelligence Optional 4
Artificial Intelligence in Health Care Optional 3
Artificial Intelligence Seminar Optional 3
Artificial Vision and Pattern Recognition Compulsory 4.5
Assistive and Health-Care Technologies Optional 4.5
Big Data Analytics Optional 4.5
Cognitive Interaction with Robots Optional 4.5
Cognitive Robotics Optional 4.5
Complex Networks Optional 5
Computational Vision Compulsory 5
Constraint Processing and Programming Optional 4.5
Deep Learning for Medical Image Analysis Optional 3
Deep Learning Optional 4.5
Final Project Compulsory 18
Human Language Engineering Optional 4.5
Human-Computer Interfaces Optional 4.5
Intelligent Data Analysis Applications in Business Optional 2
Intelligent Decision Support Systems Optional 4.5
Intelligent System Project Optional 3
Introduction to Human Language Technology Compulsory 5
Introduction to Machine Learning Compulsory 5
Introduction to Multi-Agent Systems Compulsory 5
Knowledge Representation and Engineering Optional 6
Logic and Artificial Intelligence Optional 6
Machine Learning in Computer Graphics Optional 3
Minds, Brains and Machines Optional 4
Multi-Agent Systems Design Optional 4
Multi-Agent Systems Optional 4
Multi-Criteria Decision Support Systems Optional 4.5
Multi-Robot Systems Optional 4.5
New Trends in Robotics Optional 3
Normative and Dynamic Virtual Worlds Optional 4.5
Object Recognition Optional 4
Personalized Multicriteria Decision-Support Systems Optional 4.5
Planning and Approximate Reasoning Optional 5
Probabilistic Graphical Models Optional 4.5
Professional Practice in Artificial Intelligence Optional 3
Self-Organizing Agent Systems Optional 4.5
Smart Data Analysis and Data Mining Optional 4.5
Supervised and Experimental Learning Optional 4.5
Unsupervised and Reinforcement Learning Optional 4.5

Previous years

Placements

Placements in a company or another type of organization are an integral part of university studies, providing first-hand experience of working methodologies in students' chosen professional fields. They offer invaluable practical experience for the transition into work after graduation.



Placements are supervised by tutors and subject to assessment. They are therefore included in the academic record.  There is also an option to complete non-curricular placements of up to 500 hours, which can be extended to 900 hours. For both curricular and non-curricular placements, an educational cooperation agreement is signed between the UB and the company, institution or other organization at which the placement will be carried out.



Institutional information


Career opportunities

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