Risk Management

Recommended Prerequisites

NA

Teaching Methods

The methodology includes lectures, using audiovisual means. It seeks to promote an active and participatory learning, focusing on the interaction, privileging the interaction and the discussion in the classroom, in order to better understand the contents addressed.
The goal of this final project is to provide with an opportunity to perform an in-depth investigation into risk measurement, letting students to “learn by doing” on concrete case studies.

Learning Outcomes

Present data analytic models aimed at measuring health risks: correlation models, network models, cluster analysis (unsupervised); regression models, tree models, neural network models (supervised).
Provide students with R software code to implement models on real data, by means of specific use cases.

Work Placement(s)

No

Syllabus

Correlation models, network models
Grouping and cluster analysis
Regression models
Tree models
Neural network models
Application of the R software on real data

Assessment Methods

Assessment
Other: 50.0%
Exam: 50.0%

Bibliography

Giudici, P. Applied data mining, Wiley, 2003
The R studio software: https://www.r-project.org
Trabalhos publicados recentemente em revistas científicas de revisão por pares, relacionados com os temas discutidos.