Content Official Master's Degree in Computer Vision
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.