Studying at the University of Verona

Here you can find information on the organisational aspects of the Programme, lecture timetables, learning activities and useful contact details for your time at the University, from enrolment to graduation.

This information is intended exclusively for students already enrolled in this course.
If you are a new student interested in enrolling, you can find information about the course of study on the course page:

Laurea magistrale in Ingegneria e scienze informatiche - Enrollment from 2025/2026

The Study Plan includes all modules, teaching and learning activities that each student will need to undertake during their time at the University.
Please select your Study Plan based on your enrollment year.

CURRICULUM TIPO:

2° Year   It will be activated in the A.Y. 2025/2026

ModulesCreditsTAFSSD
Final exam
24
E
-
It will be activated in the A.Y. 2025/2026
ModulesCreditsTAFSSD
Final exam
24
E
-
Modules Credits TAF SSD
Between the years: 1°- 2°
Between the years: 1°- 2°
Further activities
3
F
-
Between the years: 1°- 2°
English B2
3
F
-

Legend | Type of training activity (TTA)

TAF (Type of Educational Activity) All courses and activities are classified into different types of educational activities, indicated by a letter.




S Placements in companies, public or private institutions and professional associations

Teaching code

4S012349

Credits

6

Coordinator

Pietro Sala

Language

Italian

Scientific Disciplinary Sector (SSD)

INF/01 - INFORMATICS

Courses Single

Authorized

The teaching is organized as follows:

Teoria
The activity is given by Data Mining and Knowledge Discovery - Teoria of the course: Master's degree in Computer Science and Engineering

Credits

5

Period

Semester 1

Academic staff

Pietro Sala

Laboratorio
The activity is given by Data Mining and Knowledge Discovery - Laboratorio of the course: Master's degree in Computer Science and Engineering

Credits

1

Period

Semester 1

Academic staff

Pietro Sala

Learning objectives

The corse aims to provide the theoretical and practical foundations for integrating data from, possibly, heterogeneous sources and the subsequent phase of extraction of summary information/knowledge. By completing the course, the students will be able to tackle complex data mining problems by designing and implementing a full pipeline that allows its user to integrate the necessary data sources, select and apply the adequate data mining techniques for solving a specific data mining problem, and evaluate its performances. Given a data mining problem, coming from a real-world domain ranging from industry to healthcare, the course enables the students to design, apply and test original solutions or or modifications of existing ones, for solving it and evaluate the feasibility of the proposed solution in a real environment.