Objectives:
The objective of this EU is to teach an approach/methodology to analyse data through fundamental steps such as: description, classification, modelling, prediction and validation for information extraction for solving industrial problems. The aim is to enable students to assimilate the challenges of data analysis through case studies. This objective will require the acquisition of the following skills:
-structure the information contained in multidimensional data
-master standard methods for performing analyses and producing complete reports
-understand the limitations of these approaches, and consider alternatives, extensions, etc.
-implement these methods in the context of case studies from the various engineering professions
Learning Outcomes:
-data mining method: Main Component Analysis, Correspondence Factor Analysis, Multiple Correspondence Analysis
-linear regression and logistic regression modelling methods (discrete variables)
-classification methods (fuzzy logic and neural networks)
-processing of missing and outliers data, error detection
-presentation and practical case study (applied to the different fields of the engineer's profession)
