- Area Economico-Statistica
- Corso di Laurea Magistrale
- Scienze Statistiche ed Economiche [F8204B]
- Insegnamenti
- A.A. 2024-2025
- 2° anno
- Data Science M
- Introduzione
Syllabus del corso
Obiettivi formativi
Data Science M è composto da due moduli:
Data Mining M
Il corso si pone come obiettivo l'approfondimento di tecniche per l'analisi dei dati e di data mining e il perfezionamento delle abilità di modellizzazione con finalità previsiva, con relative implementazioni nell’ambiente di programmazione R.
Per maggiorni informazioni: https://elearning.unimib.it/course/info.php?id=55081
Statistical Learning M
Il corso si pone come obiettivo l'acquisizione delle principali tecniche di statistical learning (SL) e la loro implementazione nell’ambiente di programmazione R. Durante il corso verrà data particolare enfasi alla algorithmic modeling culture, prestando anche attenzione alla stima dell'incertezza nelle previsioni.
Per maggiori informazioni : https://elearning.unimib.it/course/info.php?id=55091
Entrambi i corsi contribuiscono al raggiungimento degli obiettivi formativi nell’area di apprendimento del CdS: “Statistica”.
Contenuti sintetici
Data Mining M
A-B-C: modelli lineari ed aspetti computazionali
Compromesso distorsione e varianza, ottimismo
Selezione del modello e metodi penalizzati per modelli lineari (regressione ridge, lasso, elastic-net)
Regressione nonparametrica (regressione lineare locale, splines di regressione e di lisciamento)
Modelli additivi (GAM and MARS)
https://elearning.unimib.it/course/info.php?id=55081
Statistical Learning M
Metodi basati sugli alberi e aspetti computazioni.
Deep Learning per dati non strutturati.
Stima dell'incertezza.
https://elearning.unimib.it/course/info.php?id=55091
Programma esteso
Data Mining M
https://elearning.unimib.it/course/info.php?id=55081
Statistical Learning M
https://elearning.unimib.it/course/info.php?id=55091
Prerequisiti
Data Mining M
https://elearning.unimib.it/course/info.php?id=55081
Statistical Learning M
https://elearning.unimib.it/course/info.php?id=55091
Metodi didattici
Data Mining M
https://elearning.unimib.it/course/info.php?id=55081
Statistical Learning M
https://elearning.unimib.it/course/info.php?id=55091
Modalità di verifica dell'apprendimento
Data Mining M
https://elearning.unimib.it/course/info.php?id=55081
Statistical Learning M
https://elearning.unimib.it/course/info.php?id=55091
Testi di riferimento
Data Mining M
https://elearning.unimib.it/course/info.php?id=55081
Statistical Learning M
https://elearning.unimib.it/course/info.php?id=55091
Periodo di erogazione dell'insegnamento
Data Mining M
https://elearning.unimib.it/course/info.php?id=55081
Statistical Learning M
https://elearning.unimib.it/course/info.php?id=55091
Lingua di insegnamento
Data Mining M
https://elearning.unimib.it/course/info.php?id=55081
Statistical Learning M
https://elearning.unimib.it/course/info.php?id=55091
Sustainable Development Goals
Learning objectives
Data Science M is composed by two modules
Data Mining M
The course aims to provide data analysis and data mining tecniques and to improve predictive modelling skills by using the R software environment for statistical computing.
For more details, please see: https://elearning.unimib.it/course/info.php?id=55081
Statistical Learning M
The course aims to acquire the main techniques of statistical learning (SL) and their implementation in the R programming environment. During the course, emphasis will be placed on the algorithmic modelling culture, while also paying attention to the estimation of uncertainty in predictions.
For more details, please see : https://elearning.unimib.it/course/info.php?id=55091
Both courses contribute to the achievement of the learning objectives in the subject area of the MSc: "Statistics".
Contents
Data Mining M
https://elearning.unimib.it/course/info.php?id=55081
Statistical Learning M
https://elearning.unimib.it/course/info.php?id=55091
Detailed program
Data Mining M
https://elearning.unimib.it/course/info.php?id=55081
Statistical Learning M
https://elearning.unimib.it/course/info.php?id=55091
Prerequisites
Data Mining M
https://elearning.unimib.it/course/info.php?id=55081
Statistical Learning M
https://elearning.unimib.it/course/info.php?id=55091
Teaching methods
Data Mining M
https://elearning.unimib.it/course/info.php?id=55081
Statistical Learning M
https://elearning.unimib.it/course/info.php?id=55091
Assessment methods
Data Mining M
https://elearning.unimib.it/course/info.php?id=55081
Statistical Learning M
https://elearning.unimib.it/course/info.php?id=55091
Textbooks and Reading Materials
Data Mining M
https://elearning.unimib.it/course/info.php?id=55081
Statistical Learning M
https://elearning.unimib.it/course/info.php?id=55091
Semester
Data Mining M
https://elearning.unimib.it/course/info.php?id=55081
Statistical Learning M
https://elearning.unimib.it/course/info.php?id=55091
Teaching language
Data Mining M
https://elearning.unimib.it/course/info.php?id=55081
Statistical Learning M
https://elearning.unimib.it/course/info.php?id=55091