Master's Degree in Master's degree in Intelligent Systems
- New student profile and admission criteria
- Academic and professional goals
- Access to other study programmes and career opportunities
- Structure of the study programme
- Final Exam
- Evaluation criteria and exams
- Study programme leadership
- Credit Recognition and Transfer Committee for MUSI
This master's degree is aimed especially at graduates in Computer Engineering, in Automation and Industrial Electronic Engineering or in Mathematics. Graduates in degrees with related competences, such as Telematics Engineering or Physics, may also be admitted. The recommended admission profile for each specialty are:
- Applied artificial intelligence: Graduates in Computer Engineering, in Mathematics, or in Automation and Industrial Electronic Engineering.
- Data science: Graduates in Computer Engineering or Mathematics.
- Computer vision: Graduates in Computer Engineering, in Mathematics, or in Automation and Industrial Electronic Engineering.
- Mobile Robotics: Graduates in Automation and Industrial Electronic Engineeringor in Computer Engineering.
- Internet of things: Graduates in Computer Engineering, or in Automation and Industrial Electronic Engineering.
In any case, the academic committee of the master's degree will evaluate the curriculum of each student to establish their suitability for each particular specialty.
Regarding admission criteria, as a general criterion, it will be checked whether the degree of access of the student is from the preferred admission profile, or a degree with similar competences. Additionally, the following criteria will also be considered to evaluate the applicants to the master's degree:
- Average mark of the academic record of the student, giving preference to the recommended degrees.
- Years of professional experience in the field of the technologies of the master's degree. You get the maximum score with two years of experience.
For its correct assessment, the candidate must present the required documentation in accordance with the provisions established by the admission regulations.
Applications will be assessed as follows:
- Average grade of the academic record, 85% of the total assessment.
- Years of professional experience in the field, 15% of the total assessment.
The pre-registration date for the master's degree will be taken into account if there is a tie between the candidates.
The goals of this master's degree are focused on the acquisition by the student of a set of basic, general and specific competences. Among the basic competences, we can highlight:
- To acquire and understand knowledge that provides a basis or opportunity of being original in the development and/or application of ideas, often in a research context.
- To know how to apply the acquired knowledge and ability to solve problems in new or unfamiliar environments in broader (or multidisciplinary) contexts related to their area of ??study.
- To be able to integrate knowledge and train themselves in the complexity of formulating judgments based on information that, being incomplete or limited, includes reflections on the social and ethical responsibilities linked to the application of their knowledge and judgements
- To know how to communicate one’s conclusions and the underlying reasons that support them to specialized and non-specialized audiences in a clear and unambiguous way.
- To have the learning abilities that allow oneself to continue studying in a way that often will be self-directed or autonomous.
Among the general competencies, we can emphasize:
- Integration of knowledge from different disciplines, as well as the management of complexity.
- Capacity for technical management and for leadership in research, development and innovation projects, in companies and technological centers.
- Wide understanding of the techniques and methods applicable in a specific specialization, as well as its limits.
- Ability to work in an international context.
- To understand the steps, value and limits of the scientific method, being able to design and guide analytical, modeling and experimental research, as well as evaluate critically data and draw conclusions.
Among the specific competences, we can emphasize:
- Ability to analyze the information needs that are posed in an environment in the context of intelligent systems
- Ability to carry out the process of designing an automatic system for the acquisition of information in the field of intelligent systems
- Ability to model, simulate and interpret results in the field of intelligent systems
- Ability to apply mathematical and statistical methods to design and develop applications and services in the field of intelligent systems.
- Ability to assess the importance of documentary sources, manage and search the information for the development of any research work.
- Ability to read and understand publications in one’s field of study/research, as well as their scientific value.
- Ability to understand the financing mechanisms of research and technology transfer, and the current legislation on protection of results.
- Capacity for the realization, presentation and public defense of an integral project of a professional or research nature.
This Master’s degree gives direct access to the PhD program of Information Technology and Communications offered by the Department of Mathematics and Computer Science of the University of the Balearic Islands. It also guarantees proper training for any PhD program in the field of Computer Science.
The labor exits include especially those fields in which advanced knowledge in intelligent systems are necessary:
- Smart applications on the web and in the video game industry.
- Data analysis.
- Design and implementation of cognitive agents for the elderly.
- Computer vision.
- Internet of things.
This Master’s degree lasts one academic year, that is, 60 ECTS credits. Credits are distributed in required subjects (6 credits), in six-month optional subjects (36 credits) and a Master's Thesis (18 credits).
Required subjects include the necessary foundations for all those students who want to start their path in the field of research or innovation.
Next, depending on the specializations chosen by the student, the following specializations are proposed: Applied Artificial Intelligence (18 credits), Data Science (18 credits), Computer Vision (18 credits), Mobile Robotics (18 credits) and Internet of Things (18 credits). Of these 5 specializations of 18 credits each one, the student must pass completely one of them and the remaining 18 credits may be taken from any subjects of the other specializations. Some of the subjects are recommended according to the profile of the student.
To obtain the title it is necessary to elaborate and defend the Master's Thesis.
The elements of evaluation are detailed in the academic guide of each subject. (Website section "Subjects").
Following the recommendations of the European Higher Education Area, all subjects of this Master's Degree will be evaluated following a continuous assessment process. At the beginning of the course, the evaluation criteria for each subject will be available to the students at the syllabus of each subject in the Subjects section of this webpage.