Methods and Languages for Data Processing
A.Y. 2025/2026
Learning objectives
The course aims to introduce methods and techniques for describing, summarizing, and finding a structure in a dataset, with particular attention to data collected in the field of cultural heritage. Traditional statistical methods and artificial intelligence methods will be briefly mentioned.
Expected learning outcomes
Students will be able to perform exploratory analysis of a dataset, conduct basic inferences, and run the main hypothesis tests using a data analysis environment. They will also be familiar with the main techniques of machine learning, for both regression and classification purposes, and the main topics related to machine learning.
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
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