Checking date: 22/12/2023

Course: 2023/2024

Master Thesis
Master in Machine Learning for Health (Plan: 480 - Estudio: 359)

Coordinating teacher: GOMEZ VERDEJO, VANESSA

Department assigned to the subject: Signal and Communications Theory Department

Type: Master Final Project
ECTS Credits: 9.0 ECTS


Requirements (Subjects that are assumed to be known)
The public defense of the Master Thesis (TFM, Trabajo Fin de Máster) will occur when the student has passed all the subjects of the master, within the period established for this purpose in the current academic calendar for postgraduate studies and according to the regulations set by the University and the Master Program.
The objective of the TFM is that the student develops individually an original and rigorous work with innovative character, where the knowledge acquired throughout the master's degree in machine learning techniques and health is demonstrated, so it must be related to one or more of the courses of the degree.
Skills and learning outcomes
Description of contents: programme
This course is the culmination of the skills and abilities acquired in the master's degree with the aim of training scientists capable of combining the areas of bioengineering and machine learning. To this end, the student will be required to carry out a supervised work in which an appropriate orientation and follow-up are provided at the level of their scientific maturity.
Learning activities and methodology
AF5 Tutorials AF7 Student individual work AF8 Partial and final exams
Assessment System
  • % end-of-term-examination 100
  • % of continuous assessment (assigments, laboratory, practicals...) 0

Assessment Matrix
Detailed subject contents or complementary information about assessment system of B.T.
Additional information

The course syllabus may change due academic events or other reasons.