University Master's Degree in Computer Vision

Several changes have been made to the study plan of this master's degree. Please check the information on the latest version here: Computer Vision

Content Official Master's Degree in Computer Vision

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Ideal student profile

This master's degree is for students interested in computer vision technology, for a variety of purposes:
  • students who have graduated in any branch of Engineering, Mathematics or Physics, or have an equivalent qualification, and are looking to specialise in order to begin a technology-related career;
  • students who are already working in this field and wish to refresh their knowledge;
  • students wanting to undertake a PhD thesis in this field.
Students' expected academic profile
  • Knowledge of mathematics equivalent at least to that of engineering students (Algebra, Signal Theory, Basic Image Processing, Probability and Statistics)
  • Knowledge of programming in prototyping languages like Matlab or Python.
  • A minimum English level of B1 of the Council of Europe's Common European Framework of Reference for Languages, in comprehension, writing and speaking.
Students' expected personal profile
  • Motivation to deal with complex problems.
  • Time management skills.
  • Empathy, to be able to work well in teams.
  • Strong commitment.
  • Flexibility and creativity dealing with results.

Basic skills

  • Use acquired knowledge as a basis for originality in the application of ideas, often in a research context.
  • Solve problems in new or little-known situations within broader (or multidisciplinary) contexts related to the field of study.
  • Integrate knowledge and use it to make judgements in complex situations, with incomplete information, while keeping in mind social and ethical responsibilities.
  • Communicate and justify conclusions clearly and unambiguously to both specialised and non-specialised audiences.
  • Continue the learning process, to a large extent autonomousl.

Specific skills

  • Identify concepts and apply the most appropriate fundamental techniques for solving basic problems in computer vision.
  • Conceptualise alternatives to complex solutions for vision problems and create prototypes to show the validity of the system proposed.
  • Choose the most suitable software tools and training sets for developing solutions to problems in computer vision.
  • Plan, develop, evaluate and manage solutions for projects in the different areas of computer vision.
  • Define and apply in detail the process of technology transfer for innovation in the field of computer vision.
  • Apply the research methodology, choose the techniques and information sources and organise the specific resources for research in the field of computer vision.

Cross-curricular skills

  • Recognise the human, economic, legal and ethical dimension of the profession and show a clear commitment to quality in the objectives.
  • Understand, analyse and synthesise advanced knowledge in the area, and put forward innovative ideas.
  • Accept responsibilities for information and knowledge management.
  • Work in multidisciplinary teams.