FONDAMENTI DI ANALISI DATI E LABORATORIO

Academic Year 2019/2020 - 1° Year - Curriculum Data Science

Teaching Staff

Credit Value: 9
Taught classes: 36 hours
Exercise: 24 hours
Laboratories: 12 hours
Term / Semester: 1°

Learning Objectives

FONDAMENTI DI ANALISI DATI
Basic introduction to state of the art data analysis and automated classification.
Laboratorio
The objective of the course is the acquisition of knowledge of:
- Practical tools for the management and analysis of data;
- Tools for data visualization and exploration;
- Help the understanding of theoretical concepts and models through the implementation of algorithms and/or the analysis of existing implementations;
- Practical methodologies to train and use machine learning and data analysis algorithms to build automated systems for decision support;
- Tools to produce reports detailing a data analysis process.

FONDAMENTI DI ANALISI DATI
- Fundamental of Data Analysis
  Data visualization, descriptive statistics
  
  regression and correlation. Logistic regression.
  
  Bayes approach to learning. MAP.
  
  TS, CS, trainign and generalization error. Confuson matrix. ROC.
  
  LDA, SVM.
  
  Kernel trick: non linear SVM
  
  PCA, non linear techniques for dimension reduction
  
  K-nn
  
  CART.
  
  Clustering: k-means and hierarchical clustering.
  
  Ensblem techniques. Boosting
Laboratorio
The objective of the course is the acquisition of knowledge of:
- Practical tools for the management and analysis of data;
- Tools for data visualization and exploration;
- Help the understanding of theoretical concepts and models through the implementation of algorithms and/or the analysis of existing implementations;
- Practical methodologies to train and use machine learning and data analysis algorithms to build automated systems for decision support;
- Tools to produce reports detailing a data analysis process.