Master's Dissertation

The main objective of the Master's Thesis (TFM) is to individually analyze, design, implement and validate a project related to Artificial Intelligence Technologies, and to emphasize some of the acquired competences. The project must include innovative components that go beyond the mere development of a standard application, service or line of business. The TFM must promote the student's contribution of added value in innovative projects, and its direct relationship with the labor market or with some cutting-edge aspect of research.

The contents of the subject include the analysis, design, implementation and validation of a project related to Artificial Intelligence Technologies.

The specific bibliography for each TFM will be specified in each of the different project proposals approved by the Master's Academic Committee.

The specific competencies to be developed during the TFM depend on the specific subject matter of each specific project. The competencies to be worked on in the TFM include (see master’s programme report):

· Basic: CB2, CB3 and CB4.

· General: CG1, CG2, CG3, CG4 and CG5.

· Transversal: CT1, CT2, CT3, CT4, CT6, CT7, CT8 and CT9.

· Specific: CE29 and CE30.

The student must present an agreement between themselves and their tutors to the Artificial Intelligence Master's Commission within the deadlines established for each call.

The Artificial Intelligence Master's Committee may accept or reject the agreement presented, or request modifications or ask for clarifications.

If the agreement is approved, the student will present a report and will have to make a public presentation of the work before a panel of examiners.

The assessment system includes continuous monitoring by the tutors who supervise the work and approval of the project report. The work will also be assessed by a committee made up of specialist lecturers in the area. The grading system will be in accordance with the university regulations.

The time to be devoted to this subject will be 300 hours, including personal work, face-to-face tutorials and assessment.

The time to be devoted to this subject will be 300 hours, including personal work, face-to-face tutorials and assessment.