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.

Study Plan

A.A. 2026/2027 A.A. 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:

1° Year 

ModulesCreditsTAFSSD
12
B
IINF-05/A
12
B
IINF-05/A
Four modules among the following
6
B
IINF-05/A
6
B
IINF-05/A
6
B
IINF-05/A
6
B
IINF-05/A
6
B
IINF-05/A
6
B
IINF-05/A

2° Year   It will be activated in the A.Y. 2027/2028

ModulesCreditsTAFSSD
Final exam
24
E
-
It will be activated in the A.Y. 2027/2028
ModulesCreditsTAFSSD
Final exam
24
E
-
Modules Credits TAF SSD
Between the years: 1°- 2°
Two modules among the following
6
B
INFO-01/A
6
B
INFO-01/A
6
B
INFO-01/A
6
B
INFO-01/A
6
B
INFO-01/A
6
B
INFO-01/A
6
B
INFO-01/A
6
B
INFO-01/A
6
B
INFO-01/A
6
B
INFO-01/A
6
B
INFO-01/A
6
B
INFO-01/A
6
B
INFO-01/A
6
B
INFO-01/A
6
B
INFO-01/A
6
B
INFO-01/A
6
B
INFO-01/A
6
B
INFO-01/A
6
B
INFO-01/A
6
B
INFO-01/A
Between the years: 1°- 2°
Three modules among the following
- A.A. 2026/2027 Automated software verification not delivered
6
C
INFO-01/A
6
C
INFO-01/A
6
C
INFO-01/A
6
C
INFO-01/A
6
C
INFO-01/A
6
C
INFO-01/A
6
C
INFO-01/A
6
C
INFO-01/A
6
C
INFO-01/A
6
C
INFO-01/A
6
C
INFO-01/A
6
C
INFO-01/A
6
C
INFO-01/A
6
C
INFO-01/A
6
C
INFO-01/A
6
C
INFO-01/A
6
C
ECON-08/A
6
C
INFO-01/A
6
C
INFO-01/A
6
C
INFO-01/A
6
C
INFO-01/A
Between the years: 1°- 2°
Further language skills (students who didn't take B2 ENG exam during bachelor's degree have to take it during master's degree. Who did take it during bachelor's can take: ENG (C1, C2), SPA (B1, B2, C1, C2), FRA (B1, B2, C1, C2), TED (B1, B2, C1, C2)
3
F
-
Between the years: 1°- 2°
Further activities
3
F
-
Between the years: 1°- 2°
12
D
-

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.

A Basic activities
B Characterizing activities
C Related or complementary activities
D Activities to be chosen by the student
E Final examination
F Other training activities
S Placements in companies, public or private institutions and professional associations

Business intelligence  (2026/2027)

Teaching code

4S011697

Teacher

Elisa Quintarelli

Coordinator

Elisa Quintarelli

Credits

6

Also offered in courses:

Language

Italian

Scientific Disciplinary Sector (SSD)

INFO-01/A - Informatics

Period

II semestre dal Mar 1, 2027 al Jun 11, 2027.

Courses Single

Authorized

Lessons timetable Seminars 0

Learning objectives

The main aim of the course is providing students with theoretical foundations of decision support system design, data integration and data analysis techniques. In particular, techniques for decision support system design, data integration techniques and visualization and analysis of data will be described. At the end of the course the student will be able to master knowledge and skills about designing and management of a Business Intelligence System, and to understand system requirements and communicate appropriately with stakeholders. In particular, the student will be able to design and manage a decision support system, to apply data integration techniques, and analyse multidimensional data. She will also be able to autonomously continue studies in the Information Systems field.

Prerequisites and basic notions

Fundamental concepts of databases.

Program

- Data Integration.
- Data Analytics.
-- Classification.
--- Decision Trees.
--- Bayesian classification.
--- Association rules classification.
--- Classification accuracy.
--- Spatial Data Classification.
-- Clustering.
--- Spatial Data Classification.
--- K-means clustering and k-nn clustering.
--- Hierarchical clustering.
--- Density-based Clustering.
--- Grid-based clustering.
--- Clustering accuracy.
-- Data Mining vs. Machine Learning.

Didactic methods

In-person classes.

Learning assessment procedures

Written test with exercises and questions.

Students with disabilities or specific learning disorders (SLD), who intend to request the adaptation of the exam, must follow the instructions given HERE

Evaluation criteria

To pass the exam, the students must show that:
- they have understood the concepts related to decision support systems, and data analytics;
- they are able to describe the concepts in a clear and exhaustive way;
- they are able to apply the acquired knowledge to solve application problems described by means of questions and exercises.

Criteria for the composition of the final grade

Criteria for exam evaluation:
- Mastery of content and depth of knowledge.
- Propriety of language with respect to topics.
- Ability to solve application problems.

Exam language

Italiano