This CU introduces statistical data mining algorithms and methodologies. It ́s interdisciplinary nature combines topics of statistics, databases and computer science. The intended outcomes are:

1. To describe the several stages of a Data Science project. To know the concepts and statistical techniques of machine learning (ML), exemplifying its applications and functionalities;
2. To identify the several types of input data and to know the methodologies for its preparation and preprocessing, as well as the main techniques for transformation and reduction of data dimensionality;
3. To know the mathematical theoretical foundations associated to the ML methods, to know how to handle them, as well as to identify and interpret the several forms and types of results;
4. To evaluate the results obtained with the ML techniques, using and interpreting the performance measures;
5. Use appropriate softwares for solving several challenges;
6. To complete a Data Science project using appropriate methodologies.

Curricular Unit Form