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.

A.A. 2017/2018

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 sem. Oct 2, 2017 Jan 31, 2018
II sem. Mar 1, 2018 Jun 15, 2018
Exam sessions
Session From To
Sessione invernale d'esame Feb 1, 2018 Feb 28, 2018
Sessione estiva d'esame Jun 18, 2018 Jul 31, 2018
Sessione autunnale d'esame Sep 3, 2018 Sep 28, 2018
Degree sessions
Session From To
Sessione di laurea estiva Jul 18, 2018 Jul 18, 2018
Sessione di laurea autunnale Nov 22, 2018 Nov 22, 2018
Sessione di laurea invernale Mar 20, 2019 Mar 20, 2019
Holidays
Period From To
Christmas break Dec 22, 2017 Jan 7, 2018
Easter break Mar 30, 2018 Apr 3, 2018
Patron Saint Day May 21, 2018 May 21, 2018
Vacanze estive Aug 6, 2018 Aug 19, 2018

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

B C D F G L M O P Q S T U

Belussi Alberto

alberto.belussi@univr.it +39 045 802 7980
Foto,  February 9, 2017

Bloisi Domenico Daniele

domenico.bloisi@univr.it

Bombieri Nicola

nicola.bombieri@univr.it +39 045 802 7094

Bonacina Maria Paola

mariapaola.bonacina@univr.it +39 045 802 7046

Boscaini Maurizio

maurizio.boscaini@univr.it

Busato Federico

federico.busato@univr.it

Calanca Andrea

andrea.calanca@univr.it +39 045 802 7847

Carra Damiano

damiano.carra@univr.it +39 045 802 7059

Combi Carlo

carlo.combi@univr.it 045 802 7985

Daffara Claudia

claudia.daffara@univr.it +39 045 802 7942

Dalla Preda Mila

mila.dallapreda@univr.it

Di Pierro Alessandra

alessandra.dipierro@univr.it +39 045 802 7971

Fiorini Paolo

paolo.fiorini@univr.it 045 802 7963

Fummi Franco

franco.fummi@univr.it 045 802 7994

Geretti Luca

luca.geretti@univr.it +39 045 802 7850

Giachetti Andrea

andrea.giachetti@univr.it +39 045 8027998

Giacobazzi Roberto

roberto.giacobazzi@univr.it +39 045 802 7995

Gobbi Bruno

bruno.gobbi@univr.it

Gregorio Enrico

Enrico.Gregorio@univr.it 045 802 7937

Lora Michele

michele.lora@univr.it

Maris Bogdan Mihai

bogdan.maris@univr.it +39 045 802 7074

Marzola Pasquina

pasquina.marzola@univr.it 045 802 7816 (ufficio); 045 802 7614 (laboratorio)

Mastroeni Isabella

isabella.mastroeni@univr.it +39 045 802 7089

Menegaz Gloria

gloria.menegaz@univr.it +39 045 802 7024

Mogavero Fabio

fabio.mogavero@univr.it

Oliboni Barbara

barbara.oliboni@univr.it +39 045 802 7077

Posenato Roberto

roberto.posenato@univr.it +39 045 802 7967

Pravadelli Graziano

graziano.pravadelli@univr.it +39 045 802 7081

Quaglia Davide

davide.quaglia@univr.it +39 045 802 7811

Segala Roberto

roberto.segala@univr.it 045 802 7997

Setti Francesco

francesco.setti@univr.it +39 045 802 7804

Spoto Nicola Fausto

fausto.spoto@univr.it +39 045 8027940

Tomazzoli Claudio

claudio.tomazzoli@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
B
(INF/01)
6
C
(FIS/01)
6
B
(ING-INF/05)
12
B
(ING-INF/05)
6
B
(INF/01)
ModulesCreditsTAFSSD
12
B
(ING-INF/05)
One course to be chosen among the following
6
B
(INF/01)
Training
6
F
-
Final exam
6
E
-

2° Year

ModulesCreditsTAFSSD
12
B
(INF/01)
6
C
(FIS/01)
6
B
(ING-INF/05)
12
B
(ING-INF/05)
6
B
(INF/01)

3° Year

ModulesCreditsTAFSSD
12
B
(ING-INF/05)
One course to be chosen among the following
6
B
(INF/01)
Training
6
F
-
Final exam
6
E
-

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

4S00030

Coordinatore

Enrico Gregorio

Credits

6

Scientific Disciplinary Sector (SSD)

MAT/05 - MATHEMATICAL ANALYSIS

Language

Italian

Period

I sem. dal Oct 2, 2017 al Jan 31, 2018.

Learning outcomes

The course will treat the fundamental concepts of mathematical analysis: the aim is to provide a better consciousness of the analytic methods in view of applications of analysis.

At the end of the course, the students shall prove of being able to: apply mathematical analysis techniques to the solution of problems about functions, derivatives, integrals and series also in different contexts even not strictly mathematical; to apply mathematical analysis techniques to solution of problems; to choose among the various techniques the one better suited to the problem at hand; to describe the solution of a problem employing correct terminology; to widen their knowledge starting from what they learned.

Program

Curves and tangents
Continuity
Limits
Differentiable functions
Study of functions
Integrals
Series

Bibliografia

Reference texts
Author Title Publishing house Year ISBN Notes
Serge Lang A first course in calculus (Edizione 5) Springer 1986 0-387-96201-8

Examination Methods

The written exam consists in discussing a topic from a theoretical point of view and in solving some exercises on the topics of the course.

The complete solution of the exercises leads to a grade not higher than 21/30.

Evaluation criteria:

• Knowledge and understanding: comprehension of the text of the problems and mastering of the theory behind them.

• Applying knowledge and understanding: ability to apply the general techniques to a specific problem

• Making judgements: ability to express the learned theoretical concepts in varied situations

• Communication skills: language clarity and appropriateness

• Learning skills: ability to structure a proof different from those presented during the course

Type D and Type F activities

Modules not yet included

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

List of theses and work experience proposals

theses proposals Research area
Analisi e percezione dei segnali biometrici per l'interazione con robot AI, Robotics & Automatic Control - AI, Robotics & Automatic Control
Integrazione del simulatore del robot Nao con Oculus Rift AI, Robotics & Automatic Control - AI, Robotics & Automatic Control
Domain Adaptation Computer Science and Informatics: Informatics and information systems, computer science, scientific computing, intelligent systems - Computer graphics, computer vision, multi media, computer games
Domain Adaptation Computer Science and Informatics: Informatics and information systems, computer science, scientific computing, intelligent systems - Machine learning, statistical data processing and applications using signal processing (e.g. speech, image, video)
BS or MS theses in automated reasoning Computing Methodologies - ARTIFICIAL INTELLIGENCE
Domain Adaptation Computing Methodologies - IMAGE PROCESSING AND COMPUTER VISION
Domain Adaptation Computing methodologies - Machine learning
Dati geografici Information Systems - INFORMATION SYSTEMS APPLICATIONS
Analisi e percezione dei segnali biometrici per l'interazione con robot Robotics - Robotics
Integrazione del simulatore del robot Nao con Oculus Rift Robotics - Robotics
BS or MS theses in automated reasoning Theory of computation - Logic
BS or MS theses in automated reasoning Theory of computation - Semantics and reasoning
Proposte di tesi/collaborazione/stage in Intelligenza Artificiale Applicata Various topics
Proposte di Tesi/Stage/Progetto nell'ambito delle basi di dati/sistemi informativi Various topics

Gestione carriere


Area riservata studenti


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.

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.