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

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

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

ModulesCreditsTAFSSD
Final exam
30
E
-
ModulesCreditsTAFSSD
It will be activated in the A.Y. 2027/2028
ModulesCreditsTAFSSD
Final exam
30
E
-
Modules Credits TAF SSD
Between the years: 1°- 2°
2 modules among the following: area algebra and geometry + analysis
- A.A. 2026/2027 Applied algebra not delivered
6
B
MATH-02/A ,MATH-02/B
6
B
MATH-02/A
6
B
MATH-03/A
Between the years: 1°- 2°
Further activities
6
F
-
Between the years: 1°- 2°

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

4S008268

Coordinator

Luca Di Persio

Credits

6

Also offered in courses:

Language

English en

Scientific Disciplinary Sector (SSD)

MATH-03/B - Probability and Mathematical Statistics

Period

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

Courses Single

Authorized

Learning objectives

This course will provide an introduction to the theory of Stochastic Differential Equations (SDEs), mainly based on the Brownian motion type of noise. The purpose of this course is to introduce and analyse probability models that capture the stochastic features of the system under study to predict the short and long term effects that this randomness will have on the systems under consideration. The study of probability models for continuous-time stochastic processes involves a broad range of mathematical and computational tools. This course will strike a balance between the mathematics and the applications. The main applications will be mathematical finance, biology and populations evolution, also with respect to their descriptions in terms of the associated SDEs. Topics include: construction of Brownian motion; martingales in continuous time; stochastic integral; Ito calculus; stochastic differential equations; Girsanov theorem; martingale representation; the Feynman-Kac formula and Lévy processes.