Methodology
The Master's Degree in Artificial Intelligence is built on an active, applied and interdisciplinary methodology that blends academic rigor with hands-on experience. The teaching approach focuses on real-world problem solving through collaborative projects, simulations, case studies and technology labs.
Throughout the programme, students:
- Apply the knowledge acquired in real or simulated environments for the development of AI solutions.
- Work with real-world data, professional tools and cutting-edge development environments.
- Take part in cross-disciplinary projects that integrate the programme’s core areas: machine learning, computer vision, natural language processing, robotics and big data.
- Develop key skills in technical leadership, teamwork, results communication and data-driven decision making.
- Receive training in the ethics, regulation and transparency of intelligent systems, with a responsible approach focused on social impact.
The programme’s assessment combines individual work, practical assignments, oral presentations, active class participation and the completion of a Master’s Final Project, which synthesises learning outcomes and showcases the student’s ability to lead a project in the AI field.