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. 2023/2024 A.A. 2022/2023 A.A. 2021/2022 A.A. 2020/2021

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.

1° Year

ModulesCreditsTAFSSD
9
B
SECS-P/08
12
C
MAT/06
12
B
INF/01

2° Year  activated in the A.Y. 2021/2022

ModulesCreditsTAFSSD
9
B/C
IUS/01 ,M-FIL/03
Training
6
F
-
Final exam
22
E
-
activated in the A.Y. 2021/2022
ModulesCreditsTAFSSD
9
B/C
IUS/01 ,M-FIL/03
Training
6
F
-
Final exam
22
E
-
Modules Credits TAF SSD
Between the years: 1°- 2°
1 module among the following (1st year: Big Data epistemology and Social research; 2nd year: Cybercrime, Data protection in business organizations, Comparative and Transnational Law & Technology)
6
C
M-FIL/02
6
C
IUS/02
6
C
IUS/17
6
C
SPS/07
6
C
IUS/04
Between the years: 1°- 2°
2 courses among the following (1st year: Business analytics, Digital Marketing and market research; 2nd year: Logistics, Operations & Supply Chain, Digital transformation and IT change, Statistical methods for Business intelligence)
6
B
SECS-P/10
6
B
SECS-P/08
6
B
SECS-P/10
6
B
SECS-P/08
6
B
SECS-S/01
Between the years: 1°- 2°
2 courses among the following (1st year: Complex systems and social physics, Discrete Optimization and Decision Making, 2nd year: Statistical models for Data Science, Continuous Optimization for Data Science, Network science and econophysics, Marketing research for agrifood and natural resources)
6
C
FIS/02
6
C
MAT/09
6
C
AGR/01
6
C
MAT/06
6
C
MAT/08
6
C
FIS/02
Between the years: 1°- 2°
2 courses among the following (1st year: Data Visualisation, Data Security & Privacy, Statistical learning, Mining Massive Dataset, 2nd year: Machine Learning for Data Science)
6
B
INF/01
6
B
ING-INF/05
6
B
ING-INF/05
6
B
INF/01
6
B
INF/01
Between the years: 1°- 2°
8
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

Network science and econophysics   (2021/2022)

Teaching code

4S009155

Teacher

Fabrizio Illuminati

Credits

6

Language

English en

Scientific Disciplinary Sector (SSD)

FIS/02 - THEORETICAL PHYSICS, MATHEMATICAL MODELS AND METHODS

Period

Secondo semestre dal Mar 7, 2022 al Jun 10, 2022.

Lessons timetable MoodleMoodle Seminars 0

Learning outcomes

The aim of the course is to provide the student with the interdisciplinary physical-mathematical modeling skills for the study of networks of economic agents in interaction, with applications to the characterization of financial markets, business organization, and economic forecasting. Analysis schemes of interacting networks, with particular reference to the spread of agents and influences in the company organization, will in particular be developed.

At the end of the course the student has to show to have acquired the following skills:
● ability to develop analytical-quantitative models and numerical algorithms for the detection of trends in interacting social network systems and for the design of strategies for analyzing and optimizing the business management and dynamics.