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.

Academic calendar

The academic calendar shows the deadlines and scheduled events that are relevant to students, teaching and technical-administrative staff of the University. Public holidays and University closures are also indicated. The academic year normally begins on 1 October each year and ends on 30 September of the following year.

Academic calendar

Course calendar

The Academic Calendar sets out the degree programme lecture and exam timetables, as well as the relevant university closure dates..

Definition of lesson periods
Period From To
I semestre Oct 1, 2020 Jan 29, 2021
II semestre Mar 1, 2021 Jun 11, 2021
Exam sessions
Session From To
Sessione invernale d'esame Feb 1, 2021 Feb 26, 2021
Sessione estiva d'esame Jun 14, 2021 Jul 30, 2021
Sessione autunnale d'esame Sep 1, 2021 Sep 30, 2021
Degree sessions
Session From To
Sessione Estiva Jul 19, 2021 Jul 19, 2021
Sessione Autunnale Oct 19, 2021 Oct 19, 2021
Sessione Autunnale Dicembre Dec 7, 2021 Dec 7, 2021
Sessione Invernale Mar 17, 2022 Mar 17, 2022
Holidays
Period From To
Festa dell'Immacolata Dec 8, 2020 Dec 8, 2020
Vacanze Natalizie Dec 24, 2020 Jan 3, 2021
Epifania Jan 6, 2021 Jan 6, 2021
Vacanze Pasquali Apr 2, 2021 Apr 5, 2021
Festa del Santo Patrono May 21, 2021 May 21, 2021
Festa della Repubblica Jun 2, 2021 Jun 2, 2021

Exam calendar

Exam dates and rounds are managed by the relevant Science and Engineering Teaching and Student Services Unit.
To view all the exam sessions available, please use the Exam dashboard on ESSE3.
If you forgot your login details or have problems logging in, please contact the relevant IT HelpDesk, or check the login details recovery web page.

Exam calendar

Should you have any doubts or questions, please check the Enrolment FAQs

Academic staff

A B C D F G L M N O P Q S T V Z

Angeleri Lidia

symbol email lidia.angeleri@univr.it symbol phone-number 045 802 7911

Ballottari Matteo

symbol email matteo.ballottari@univr.it symbol phone-number 045 802 7098

Betterle Nico

symbol email nico.betterle@univr.it symbol phone-number +39 045 8027807

Bicego Manuele

symbol email manuele.bicego@univr.it symbol phone-number +39 045 802 7072

Boscaini Maurizio

symbol email maurizio.boscaini@univr.it

Canevari Giacomo

symbol email giacomo.canevari@univr.it symbol phone-number +39 045 8027979

Capaldi Stefano

symbol email stefano.capaldi@univr.it symbol phone-number +39 045 802 7907

Cicalese Ferdinando

symbol email ferdinando.cicalese@univr.it symbol phone-number +39 045 802 7969

Combi Carlo

symbol email carlo.combi@univr.it symbol phone-number 045 802 7985

Daducci Alessandro

symbol email alessandro.daducci@univr.it symbol phone-number +39 045 8027025

Della Libera Chiara

symbol email chiara.dellalibera@univr.it symbol phone-number +39 0458027219

Delledonne Massimo

symbol email massimo.delledonne@univr.it symbol phone-number 045 802 7962; Lab: 045 802 7058

Dell'Orco Daniele

symbol email daniele.dellorco@univr.it symbol phone-number +39 045 802 7637

Dominici Paola

symbol email paola.dominici@univr.it symbol phone-number 045 802 7966; Lab: 045 802 7956-7086

D'Onofrio Mariapina

symbol email mariapina.donofrio@univr.it symbol phone-number 045 802 7801

Drago Nicola

symbol email nicola.drago@univr.it symbol phone-number 045 802 7081

Fiorini Paolo

symbol email paolo.fiorini@univr.it symbol phone-number 045 802 7963

Fratea Caterina

symbol email caterina.fratea@univr.it symbol phone-number 045 802 8858

Fummi Franco

symbol email franco.fummi@univr.it symbol phone-number 045 802 7994

Giachetti Andrea

symbol email andrea.giachetti@univr.it symbol phone-number +39 045 8027998

Giacobazzi Roberto

symbol email roberto.giacobazzi@univr.it symbol phone-number +39 045 802 7995

Giorgetti Alejandro

symbol email alejandro.giorgetti@univr.it symbol phone-number 045 802 7982

Gregorio Enrico

symbol email Enrico.Gregorio@univr.it symbol phone-number 045 802 7937

Maris Bogdan Mihai

symbol email bogdan.maris@univr.it symbol phone-number +39 045 802 7074

Mazzi Giulio

symbol email giulio.mazzi@univr.it

Menegaz Gloria

symbol email gloria.menegaz@univr.it symbol phone-number +39 045 802 7024

Migliorini Sara

symbol email sara.migliorini@univr.it symbol phone-number +39 045 802 7908

Monti Francesca

symbol email francesca.monti@univr.it symbol phone-number 045 802 7910

Nardon Chiara

symbol email chiara.nardon@univr.it

Oliboni Barbara

symbol email barbara.oliboni@univr.it symbol phone-number +39 045 802 7077

Posenato Roberto

symbol email roberto.posenato@univr.it symbol phone-number +39 045 802 7967

Quaglia Davide

symbol email davide.quaglia@univr.it symbol phone-number +39 045 802 7811

Sala Pietro

symbol email pietro.sala@univr.it symbol phone-number 0458027850

Spoto Nicola Fausto

symbol email fausto.spoto@univr.it symbol phone-number +39 045 8027940

Storti Silvia Francesca

symbol email silviafrancesca.storti@univr.it symbol phone-number +39 045 802 7908

Trabetti Elisabetta

symbol email elisabetta.trabetti@univr.it symbol phone-number 045/8027209

Valenti Maria Teresa

symbol email mariateresa.valenti@univr.it symbol phone-number +39 045 812 8450

Villa Tiziano

symbol email tiziano.villa@univr.it symbol phone-number +39 045 802 7034

Zivcovich Franco

symbol email franco.zivcovich@univr.it

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 enrolment year.

ModulesCreditsTAFSSD
12
C
CHIM/03 ,CHIM/06
6
A
FIS/01
English B1 level
6
E
-
Modules Credits TAF SSD
Between the years: 2°- 3°
Between the years: 2°- 3°
Other activities
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

4S00021

Credits

6

Language

Italian

Scientific Disciplinary Sector (SSD)

MAT/06 - PROBABILITY AND STATISTICS

The teaching is organized as follows:

Teoria
The activity is given by Probability and Statistics - Teoria of the course Bachelor's degree in Computer Science

Credits

4

Period

Secondo semestre

Academic staff

Silvia Francesca Storti

Laboratorio
The activity is given by Probability and Statistics - Laboratorio of the course Bachelor's degree in Computer Science

Credits

2

Period

Secondo semestre

Academic staff

Silvia Francesca Storti

Learning outcomes

The course aims at providing the fundamental concepts of descriptive statistics and probability, with the task of modeling real problems by means of probability methods and applying to real problems statistic techniques. At the end of the course the student will have to demonstrate to understand the main statistical techniques for describing problems; to be able to interpret results of statistical analyses; to be able to develop know-how necessary to continue the study autonomously in the context of statistical analysis.

Program

------------------------
MM: Teoria
------------------------
(1) Descriptive Statistics. Describing data sets (frequency tables and graphs). Summarizing data sets (sample mean, median, and mode, sample variance and standard deviation, percentiles and box plots). Normal data sets. Sample correlation coefficient. (2) Probability theory. Elements of probability: sample space and events, Venn diagrams and the algebra of events, axioms of probability, sample spaces having equally likely outcomes, conditional probability, Bayes’ formula, independent events. Random variables and expectation: types of random variables, expected value and properties, variance, covariance and variance of sums of random variables. Moment generating functions. Weak law of large numbers. Special random variables: special random variables and distributions arising from the normal (chi-square, t, F). (3) Statistical inference. Distributions of sampling statistics. Parameter estimation (maximum likelihood estimators, interval estimates). Hypothesis testing and significance levels. (4) Regression. Least squares estimators of the regression parameters. Distribution of the estimators. Statistical inferences about the regression parameters. The coefficient of determination and the sample correlation coefficient. Analysis of residuals: assessing the model. Transforming to linearity. Weighted least squares.
------------------------
MM: Laboratorio
------------------------
The course includes a series of laboratories in the computer lab with exercises in MATLAB environment. After an introduction to MATLAB and to the main functions and tools useful for statistics, some exercises will be proposed on descriptive statistics and probability; for computing the probability density function (pdf) and cumulative distribution function (cdf) of special random variables, for generating random data and estimating parameters; on hypothesis testing for distributions and linear regression. The laboratories complement lectures by consolidating learning and developing problem-solving and hands-on practical skills. Teaching methods. Regular lectures with power point presentation and blackboard and laboratory exercises. Educational material will be available to students enrolled in the course on the Moodle platform. This material includes lecture presentations in PDF format and material related to laboratory activities. For further details and supplementary materials, please refer to the reference books.

Bibliography

Visualizza la bibliografia con Leganto, strumento che il Sistema Bibliotecario mette a disposizione per recuperare i testi in programma d'esame in modo semplice e innovativo.

Examination Methods

Written exam consisting of theoretical questions (test with multiple choice), problems, and laboratory questions (open questions). To pass the exam, the students must show that: - they have understood the basic concepts of probability theory and statistics; - they are able to use the knowledge acquired during the course to solve the assigned problem; - they are able to program in MATLAB environment in the statistical and probabilistic context.

Type D and Type F activities

Le attività formative in ambito D o F comprendono gli insegnamenti impartiti presso l'Università di Verona o periodi di stage/tirocinio professionale.
Nella scelta delle attività di tipo D, gli studenti dovranno tener presente che in sede di approvazione si terrà conto della coerenza delle loro scelte con il progetto formativo del loro piano di studio e dell'adeguatezza delle motivazioni eventualmente fornite.

 

I semestre From 10/1/20 To 1/29/21
years Modules TAF Teacher
Matlab-Simulink programming D Bogdan Mihai Maris (Coordinatore)
II semestre From 3/1/21 To 6/11/21
years Modules TAF Teacher
Introduction to 3D printing D Franco Fummi (Coordinatore)
Python programming language D Vittoria Cozza (Coordinatore)
HW components design on FPGA D Franco Fummi (Coordinatore)
Rapid prototyping on Arduino D Franco Fummi (Coordinatore)
Protection of intangible assets (SW and invention)between industrial law and copyright D Roberto Giacobazzi (Coordinatore)
List of courses with unassigned period
years Modules TAF Teacher
Subject requirements: mathematics D Rossana Capuani
The fashion lab (1 ECTS) D Maria Caterina Baruffi (Coordinatore)
LaTeX Language D Enrico Gregorio (Coordinatore)

Career prospects


Module/Programme news

News for students

There you will find information, resources and services useful during your time at the University (Student’s exam record, your study plan on ESSE3, Distance Learning courses, university email account, office forms, administrative procedures, etc.). You can log into MyUnivr with your GIA login details.

Graduation

For schedules, administrative requirements and notices on graduation sessions, please refer to the Graduation Sessions - Science and Engineering service.

List of theses and work experience proposals

Stage Research area
Correlated mutations Various topics

Attendance

As stated in point 25 of the Teaching Regulations for the A.Y. 2021/2022, attendance at the course of study is not mandatory.
Please refer to the Crisis Unit's latest updates for the mode of teaching.

Career management


Area riservata studenti