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Délia Boino
Submitted by dboino on 30 March 2021
Intended learning outcomes

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.


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