Methods and Languages for Data Management
A.Y. 2024/2025
Learning objectives
The aim of the course is the introduction to methods and techniques for describing, summarizing and finding a structure in a data set, with particular attention to cultural heritage datasets. Both classical statistical methods and artificial intelligence methods will be considered.
Expected learning outcomes
Students will know how to perform explorative analysis, some basic inferences and the most common statistical tests using a statistical analysis software. Moreover, they will know the main techniques of machine learning both for regression and classification problems, and will be aware of the main machine learning issues.
Lesson period: Second semester
Assessment methods: Esame
Assessment result: voto verbalizzato in trentesimi
Single course
This course can be attended as a single course.
Course syllabus and organization
Single session
Responsible
Lesson period
Second semester
INF/01 - INFORMATICS - University credits: 6
Laboratories: 32 hours
Lessons: 32 hours
Lessons: 32 hours
Professor:
Zanaboni Anna Maria
Professor(s)
Reception:
Wednesday 10:30-12:30 -- by appointment
via Celoria 18, 5th floor