Master’s Degree in Health Data Science
|
Module |
Subject area |
Type |
Subject |
ECTS |
Semester |
|
Advanced statistics and programming for health research |
Advanced statistics |
Compulsory |
Longitudinal Data and Analysis of Survival Applied To Health Sciences |
5 |
1 |
|
Compulsory |
Bayesian Statistics Applied to Health Sciences |
5 |
1 |
||
|
Bioinformatics |
Compulsory |
Bioinformatics |
6 |
1 |
|
|
Data mining in healthcare databases |
Compulsory |
Data Mining in Healthcare Databases |
4 |
1 |
|
|
Compulsory |
Deep Learning Applied to Health Sciences |
5 |
2 |
||
|
Compulsory |
Big Data Environments and Unstructured Healthcare Databases |
5 |
2 |
||
|
Epidemiology, public health and management |
Epidemiology I |
Compulsory |
Epidemiology |
5 |
1 |
|
Healthcare management |
Compulsory |
Monitoring and Databases in Health Sciences |
5 |
1 |
|
|
Compulsory |
Management and Decision-Making in Health Sciences |
4 |
2 |
||
|
Epidemiology II |
Compulsory |
Causal Inference |
5 |
2 |
|
|
(TFM) (FMP) |
Final Master's Degree Project |
(TFM) (FMP) |
(TFM) (FMP) |
8 |
2 |
|
Work placements in companies |
External practicums |
PE |
PE |
3 |
2 |
|
TYPE
|
CREDITS |
|
Compulsory |
49 (490 hrs) |
|
Options |
- |
|
External work placements |
3 (75 hrs) |
|
Final Degree Projects (Postgraduate and Master’s) |
8 |
|
TOTAL CREDITS |
60 |

