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, 2019 Jan 31, 2020
II semestre Mar 2, 2020 Jun 12, 2020
Exam sessions
Session From To
Sessione invernale d'esame Feb 3, 2020 Feb 28, 2020
Sessione estiva d'esame Jun 15, 2020 Jul 31, 2020
Sessione autunnale d'esame Sep 1, 2020 Sep 30, 2020
Degree sessions
Session From To
Sessione Estiva Jul 15, 2020 Jul 15, 2020
Sessione Autunnale Oct 16, 2020 Oct 16, 2020
Sessione Autunnale Dicembre Dec 11, 2020 Dec 11, 2020
Sessione Invernale Mar 17, 2021 Mar 17, 2021
Holidays
Period From To
Festa di Ognissanti Nov 1, 2019 Nov 1, 2019
Festa dell'Immacolata Dec 8, 2019 Dec 8, 2019
Vacanze di Natale Dec 23, 2019 Jan 6, 2020
Vacanze di Pasqua Apr 10, 2020 Apr 14, 2020
Festa della Liberazione Apr 25, 2020 Apr 25, 2020
Festa del lavoro May 1, 2020 May 1, 2020
Festa del Santo Patrono May 21, 2020 May 21, 2020
Festa della Repubblica Jun 2, 2020 Jun 2, 2020
Vacanze estive Aug 10, 2020 Aug 23, 2020

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 P Q S Z

Belussi Alberto

alberto.belussi@univr.it +39 045 802 7980

Bicego Manuele

manuele.bicego@univr.it +39 045 802 7072

Bombieri Nicola

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

Bontempi Pietro

pietro.bontempi@univr.it +39 045 802 7614

Boscaini Maurizio

maurizio.boscaini@univr.it

Boscolo Galazzo Ilaria

ilaria.boscologalazzo@univr.it +39 045 8127804

Burato Alberto

alberto.burato@univr.it

Calanca Andrea

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

Canevari Giacomo

giacomo.canevari@univr.it +39 045 8027979

Carra Damiano

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

Castellini Alberto

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

Centomo Stefano

stefano.centomo@univr.it 045 802(7048)

Combi Carlo

carlo.combi@univr.it 045 802 7985

Cozza Vittoria

vittoria.cozza@univr.it

Cristani Matteo

matteo.cristani@univr.it 045 802 7983

Cristani Marco

marco.cristani@univr.it +39 045 802 7841

Daffara Claudia

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

Dall'Alba Diego

diego.dallalba@univr.it +39 045 802 7074

Dalla Preda Mila

mila.dallapreda@univr.it

Demrozi Florenc

florenc.demrozi@univr.it +39 045 802 7048

Di Pierro Alessandra

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

Fiorini Paolo

paolo.fiorini@univr.it 045 802 7963

Fratea Caterina

caterina.fratea@univr.it 045 802 8858

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

Gregorio Enrico

Enrico.Gregorio@univr.it 045 802 7937

Laking Rosanna Davison

rosanna.laking@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)

Masini Andrea

andrea.masini@univr.it 045 802 7922

Mastroeni Isabella

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

Mazzi Giulio

giulio.mazzi@univr.it

Meli Daniele

daniele.meli@univr.it

Migliorini Sara

sara.migliorini@univr.it +39 045 802 7908

Muradore Riccardo

riccardo.muradore@univr.it +39 045 802 7835

Pravadelli Graziano

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

Quaglia Davide

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

Quintarelli Elisa

elisa.quintarelli@univr.it +39 045 802 7852

Sala Pietro

pietro.sala@univr.it 0458027850

Segala Roberto

roberto.segala@univr.it 045 802 7997

Spoto Nicola Fausto

fausto.spoto@univr.it +39 045 8027940

Storti Silvia Francesca

silviafrancesca.storti@univr.it +39 045 802 7908

Zivcovich Franco

franco.zivcovich@univr.it

Zorzi Margherita

margherita.zorzi@univr.it +39 045 802 7908

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
6
C
ING-INF/04
12
B
ING-INF/05
ModulesCreditsTAFSSD
12
B
ING-INF/05
1 module to be chosen among the following
6
C
INF/01
6
C
ING-INF/04
Tirocinio
6
F
-
Prova finale
6
E
-

2° Year

ModulesCreditsTAFSSD
12
B
INF/01
6
C
FIS/01
6
B
ING-INF/05
6
C
ING-INF/04
12
B
ING-INF/05

3° Year

ModulesCreditsTAFSSD
12
B
ING-INF/05
1 module to be chosen among the following
6
C
INF/01
6
C
ING-INF/04
Tirocinio
6
F
-
Prova finale
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

4S00037

Credits

12

Also offered in courses

Language

Italian

Scientific Disciplinary Sector (SSD)

ING-INF/05 - INFORMATION PROCESSING SYSTEMS

The teaching is organized as follows:

Teoria

Credits

6

Period

Primo semestre

Academic staff

Alberto Belussi

Laboratorio

Credits

3

Period

Secondo semestre

Academic staff

Sara Migliorini

Tecnologie per le basi di dati

Credits

3

Period

Secondo semestre

Academic staff

Sara Migliorini

Learning outcomes

The course aims to provide the necessary skills for: (i) the design of data according to the requirements with reference to different application contexts and within the production process of software systems; (ii) effective and efficient management and use of data; (iii) the use of a system for the management of relational databases in order to create, manage and query databases; (iv) the development of applications that interact with relational databases. At the end of the course the student must demonstrate knowledge and understanding of data models and query languages that characterize systems for data management and knowledge of the fundamental mechanisms to develop applications that interact with a database; have the ability to apply the acquired knowledge and understanding skills for the design of a data collection in an effective way compared to a set of application requirements, the ability to query and efficiently use the data managed by a system, the ability to design and implement an application that interacts with a data- base; know how to develop the skills necessary to continue the studies independently in the field of data management systems and software solutions development.

Program

The program is specified for each module as follows.

Module of Theory
--------------------------
- Introduction to database management systems (DBMS): architectures and functionalities of a DBMS. Physical and logical data independence. Data models. Concepts of model, schema and instance of a database. Languages for database systems. DBMS vs. file system.
- Conceptual database design: conceptual data models. The Entity-Relationship model (ER). Elements of the ER model: entities, attributes, relationships, ISA hierarchies and cardinality constraints.
- Logical database design: logical data models, the relational data model. Elements of the relational data models: relations and integrity constraints. Mapping between conceptual schemas in ER model and logical schema in the relational model.
- Interacting with a database system: languages for the definition, querying and update of a database. The relational algebra. Optimization of algebraic expressions. SQL: select-from-where statement.

Teaching methods: lecturing, practicing with the teacher, didactical material (slides) and further exercises available on the eLearning platform, individual meetings during office hours according to the timetable published on the teacher web page.

Module of Lab
---------------------
- Introduction to the relational database management system (RDBMS) PostgreSQL.
- Introduction to the use of SQL in PostgreSQL.
- Query Optimization.
- Introduction to the transaction.
- Introduction to Python Language.
- Database access from applications written in Java/Python.

Lecturing and practicing in computer laboratory, didactical material (slides) and further exercise texts are available on the eLearning platform, the teacher is available for individual meeting in office hours.

Module of Database technology
----------------------------------------------
- The internal architecture of a DBMS. Transactions. Transactions properties. The concurrency control: schedules, the two-phase locking. Access methods (indexes): primary and secondary indexes, B-+tree, hashing based access methods. Query execution and optimization.
- Techniques for the interaction between a DBMS and an application.
- XML, XML schema, UML for XML data design (hints).

Teaching methods: lecturing, practicing with the teacher, didactical material (slides) and further exercises available on the eLearning platform, individual meetings during office hours according to the timetable published on the teacher web page.

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

The exam is composed of two parts: theory and technologies+lab.

To pass the exam, the student must show that:
- they have understood the concepts related to the theory of relational databases and their design and implementation on database management systems
- they are able to describe the concepts in a clear and exhaustive way without digressions
- they are able to apply the acquired knowledge to solve application scenarios described by means of exercises, questions and projects.

Module of Theory
----------------------------------------------------------------
For the modules of "Teoria" and "Tecnologie per le basi di dati" the exam consists of a written test with a duration of 2.5 hours containing: (i) an exercise about the conceptual modeling (using the E-R model) and the logical modeling (using the relational model) of a database; (ii) some exercises about the specification of queries in relational algebra on a given database; (iii) some exercises on XML and XML-Schema and some questions on the theory. On the e-learning platform in the section "TEMI D'ESAME E ALTRI ESERCIZI RIEPILOGATIVI" some tests of the previous years are published.
During the year, it is also possible to undergo the mid-term tests: these tests are fixed by the teacher in agreement with the students and are managed on the eLearning platform. These are two tests: the first test regards the design of a relational database: conceptual design (E-R model) and logic design (relational model), and the specification of queries on a relational database in relational algebra, this test weighs 1/2 of the final grade; the second test regards the program of the module Databases Technologies, and it weighs 1/4 of the final grade.

Module of Lab
---------------------------------
For the "Laboratory" module there is a one-hour written test which includes questions and exercises on SQL queries and on writing code in Java or Python for accessing a relational database.
The laboratory test weighs 1/4 of the overall grade.

The total grade (theory+laboratory) is given by the following average: theory_grade*3/4 + lab_grade*1/4.

Type D and Type F activities

1° periodo di lezioni From 9/30/19 To 12/14/19
years Modules TAF Teacher
The fashion lab (1 ECTS) D Maria Caterina Baruffi (Coordinatore)
I semestre From 10/1/19 To 1/31/20
years Modules TAF Teacher
Control theory D Riccardo Muradore (Coordinatore)
Biomedical Data and Signal Processing D Silvia Francesca Storti (Coordinatore)
Python programming language D Maurizio Boscaini (Coordinatore)
II semestre From 3/2/20 To 6/12/20
years Modules TAF Teacher
CyberPhysical Laboratory D Andrea Calanca (Coordinatore)
C++ Programming Language D Federico Busato (Coordinatore)
LaTeX Language D Enrico Gregorio (Coordinatore)
Matlab-Simulink programming D Bogdan Mihai Maris (Coordinatore)
List of courses with unassigned period
years Modules TAF Teacher
Corso Europrogettazione D Not yet assigned
The course provides an introduction to blockchain technology. It focuses on the technology behind Bitcoin, Ethereum, Tendermint and Hotmoka. D Matteo Cristani

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.

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.


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

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