- Docente: Marco Berrettini
- Credits: 8
- SSD: SECS-S/01
- Language: Italian
- Teaching Mode: Traditional lectures
- Campus: Bologna
- Corso: Second cycle degree programme (LM) in Digital Innovation Policies and Governance (cod. 5889)
-
from Sep 16, 2024 to Nov 26, 2024
Learning outcomes
The course aims at providing the student the necessary tools to configure, analyze and interpret big data. At the end of the course the student will be able to understand the fundamental principles on which the systems for the management of Big Data are built; identify the peculiar features and functionalities offered by each of these systems; critically evaluate the sources from which the data is extracted; use the appropriate statistical tools for their analysis.
Course contents
- Review of probability
- Introduction to supervised statistical learning
- Multiple linear regression
- Dimension reduction and regularisation
- Classification
- Overview on unsupervised statistical learning
Readings/Bibliography
Suggested readings:
- James, G., Witten, D., Hastie, T., & Tibshirani, R. (2021). Introduzione all’apprendimento statistico con applicazioni in R. Piccin.
English version freely available online:
English version with applications in Python freely available online:
Teaching methods
Lectures and practical sessions.
Assessment methods
Written exam aimed at assessing the student's acquired knowledge and ability to analyze and interpret big data using appropriate statistical tools. For all students (regardless of the fact that they have attended lectures or not) the test consists of solving a problem with the aid of software. The final grade is out of thirty.
Teaching tools
- Slides
- Scripts
- Datasets
Office hours
See the website of Marco Berrettini