Studying at the University of Verona

A.A. 2020/2021

Academic calendar

Il calendario accademico riporta le scadenze, gli adempimenti e i periodi rilevanti per la componente studentesca, personale docente e personale dell'Università. Sono inoltre indicate le festività e le chiusure ufficiali dell'Ateneo.
L’anno accademico inizia il 1° ottobre e termina il 30 settembre dell'anno successivo.

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 di laurea estiva Jul 22, 2021 Jul 22, 2021
Sessione di laurea autunnale Oct 14, 2021 Oct 14, 2021
Sessione di laurea invernale Mar 16, 2022 Mar 16, 2022
Holidays
Period From To
Festa dell'Immacolata Dec 8, 2020 Dec 8, 2020
Vacanze Natalizie Dec 24, 2020 Jan 3, 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
Vacanze estive Aug 9, 2021 Aug 15, 2021

Exam calendar

The exam roll calls are centrally administered by the operational unit   Science and Engineering Teaching and Student Services Unit
Exam Session Calendar and Roll call enrolment   sistema ESSE3 . If you forget your password to the online services, please contact the technical office in your Faculty or to the service credential recovery .

Exam calendar

Per dubbi o domande Read the answers to the more serious and frequent questions - F.A.Q. Examination enrolment

Academic staff

A B C D F G L M O R S

Albi Giacomo

giacomo.albi@univr.it +39 045 802 7913

Baldo Sisto

sisto.baldo@univr.it 045 802 7935

Bos Leonard Peter

leonardpeter.bos@univr.it +39 045 802 7987

Caliari Marco

marco.caliari@univr.it +39 045 802 7904

Castellini Alberto

alberto.castellini@univr.it +39 045 802 7908

Cubico Serena

serena.cubico@univr.it 045 802 8132

Dai Pra Paolo

paolo.daipra@univr.it +39 0458027093

Daldosso Nicola

nicola.daldosso@univr.it +39 045 8027076 - 7828 (laboratorio)

Delledonne Massimo

massimo.delledonne@univr.it 045 802 7962; Lab: 045 802 7058

Dipasquale Federico Luigi

federicoluigi.dipasquale@univr.it

Di Persio Luca

luca.dipersio@univr.it +39 045 802 7968

Favretto Giuseppe

giuseppe.favretto@univr.it +39 045 802 8749 - 8748

Gregorio Enrico

Enrico.Gregorio@univr.it 045 802 7937

Mantese Francesca

francesca.mantese@univr.it +39 045 802 7978

Marigonda Antonio

antonio.marigonda@univr.it +39 045 802 7809

Mattiolo Davide

davide.mattiolo@univr.it

Mazzuoccolo Giuseppe

giuseppe.mazzuoccolo@univr.it +39 0458027838

Monti Francesca

francesca.monti@univr.it 045 802 7910

Orlandi Giandomenico

giandomenico.orlandi at univr.it 045 802 7986

Rapa Alessandro

alessandro.rapa@univr.it

Rizzi Romeo

romeo.rizzi@univr.it +39 045 8027088

Rubio Y Degrassi Lleonard

lleonard.rubioydegrassi@univr.it

Sala Pietro

pietro.sala@univr.it 0458027850

Sansonetto Nicola

nicola.sansonetto@univr.it 049-8027932

Schiavi Simona

simona.schiavi@univr.it +39 045 802 7803

Schuster Peter Michael

peter.schuster@univr.it +39 045 802 7029

Segala Roberto

roberto.segala@univr.it 045 802 7997

Solitro Ugo

ugo.solitro@univr.it +39 045 802 7977

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.

CURRICULUM TIPO:
TeachingsCreditsTAFSSD
TeachingsCreditsTAFSSD
6
B
(MAT/05)
Final exam
32
E
-

1° Anno

TeachingsCreditsTAFSSD

2° Anno

TeachingsCreditsTAFSSD
6
B
(MAT/05)
Final exam
32
E
-
Teachings Credits TAF SSD
Between the years: 1°- 2°1 module between the following
Between the years: 1°- 2°1 module between the following
Between the years: 1°- 2°
Between the years: 1°- 2°
Other activities
4
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.




SPlacements in companies, public or private institutions and professional associations

Teaching code

4S008279

Credits

6

Coordinatore

Paolo Dai Pra

The teaching is organized as follows:

Part i

Credits

3

Period

I semestre

Academic staff

Paolo Dai Pra

Part ii

Credits

3

Period

I semestre

Academic staff

Alberto Castellini

Learning outcomes

The objective is to introduce students to statistical modelling and exploratory data analysis. The mathematical foundations of Statistical Learning (supervised and unsupervised learning, deep learning) are developed with emphasis on the underlying abstract mathematical framework, aiming to provide a rigorous, self-contained derivation and theoretical analysis of the main models currently used in applications. Complimentary laboratory sessions will illustrate the use of both the key algorithms and relevant case studies, mainly by using standard software environments such as R or Python.

Program

The entire course will be available online. In addition, a number of the lessons/all the lessons (see the course
schedule) will be held in-class.

The objective is to introduce students to statistical modelling and exploratory data analysis. The mathematical foundations of Statistical Learning (supervised and unsupervised learning, deep learning) are developed with emphasis on the underlying abstract mathematical framework, aiming to provide a rigorous, self-contained derivation and theoretical analysis of the main models currently used in applications. Complimentary laboratory sessions will illustrate the use of both the key algorithms and relevant case studies, mainly by using standard software environments such as R or Python.

Examination Methods

See the assessment methods for Part I and Part II.

The assessment methods could change according to the academic rules

Bibliografia

Reference texts
Author Title Publishing house Year ISBN Notes
T. Hastie, R. Tibshirani, J. Friedman. The elements of statistical learning. Data mining, inference, and prediction. (Edizione 2) Springer 2009

Tipologia di Attività formativa D e F

Course not yet included

Career prospects


Avvisi degli insegnamenti e del corso di studio

Per la comunità studentesca

Se sei già iscritta/o a un corso di studio, puoi consultare tutti gli avvisi relativi al tuo corso di studi nella tua area riservata MyUnivr.
In questo portale potrai visualizzare informazioni, risorse e servizi utili che riguardano la tua carriera universitaria (libretto online, gestione della carriera Esse3, corsi e-learning, email istituzionale, modulistica di segreteria, procedure amministrative, ecc.).
Entra in MyUnivr con le tue credenziali GIA.

Attività didattiche alternative

Allegati

Title Info File
pdf Courses replacement 113 KB, 22/07/21 
pdf Learning Agreement UNITN - UNIVR 44 KB, 22/07/21 

Double degree

The University of Verona, through a network of agreements with foreign universities, offers international courses that enable students to gain a Double/Joint degree at the time of graduation. Indeed, students enrolled in a Double/Joint degree programme will be able to obtain both the degree of the University of Verona and the degree issued by the Partner University abroad - where they are expected to attend part of the programme -, in the time it normally takes to gain a common Master’s degree. The institutions concerned shall ensure that both degrees are recognised in the two countries.

Places on these programmes are limited, and admissions and any applicable grants are subject to applicants being selected in a specific Call for applications.

The latest Call for applications for Double/Joint Degrees at the University of Verona is available now!


Gestione carriere


Modalità di frequenza

Come riportato al punto 25 del Regolamento Didattico per l'A.A. 2021/2022, la frequenza è in generale non obbligatoria, con la sola eccezione di alcune attività laboratoriali. Per queste sarà chiaramente indicato nella scheda del corrispondente insegnamento l'ammontare di ore per cui è richiesta la frequenza obbligatoria.

Graduation

Allegati

List of theses and work experience proposals

theses proposals Research area
Controllo di sistemi multiagente Calculus of variations and optimal control; optimization - Hamilton-Jacobi theories, including dynamic programming
Controllo di sistemi multiagente Calculus of variations and optimal control; optimization - Manifolds
Controllo di sistemi multiagente Calculus of variations and optimal control; optimization - Optimality conditions
Formule di rappresentazione per gradienti generalizzati Mathematics - Analysis
Formule di rappresentazione per gradienti generalizzati Mathematics - Mathematics
Mathematics Bachelor and Master thesis titles Various topics
Stage Research area
Internship proposals for students in mathematics Various topics

Further services

I servizi e le attività di orientamento sono pensati per fornire alle future matricole gli strumenti e le informazioni che consentano loro di compiere una scelta consapevole del corso di studi universitario.