Studying at the University of Verona

A.A. 2016/2017

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 sem. Oct 3, 2016 Jan 31, 2017
II sem. Mar 1, 2017 Jun 9, 2017
Exam sessions
Session From To
Sessione invernale Appelli d'esame Feb 1, 2017 Feb 28, 2017
Sessione estiva Appelli d'esame Jun 12, 2017 Jul 31, 2017
Sessione autunnale Appelli d'esame Sep 1, 2017 Sep 29, 2017
Degree sessions
Session From To
Sessione estiva Appelli di Laurea Jul 18, 2017 Jul 18, 2017
Sessione autunnale Appelli di laurea Nov 22, 2017 Nov 22, 2017
Sessione invernale Appelli di laurea Mar 20, 2018 Mar 20, 2018
Holidays
Period From To
Festa di Ognissanti Nov 1, 2016 Nov 1, 2016
Festa dell'Immacolata Concezione Dec 8, 2016 Dec 8, 2016
Vacanze di Natale Dec 23, 2016 Jan 8, 2017
Vacanze di Pasqua Apr 14, 2017 Apr 18, 2017
Anniversario della Liberazione Apr 25, 2017 Apr 25, 2017
Festa del Lavoro May 1, 2017 May 1, 2017
Festa della Repubblica Jun 2, 2017 Jun 2, 2017
Vacanze estive Aug 8, 2017 Aug 20, 2017

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

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

Belussi Alberto

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

Bombieri Nicola

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

Bonacina Maria Paola

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

Bonnici Vincenzo

vincenzo.bonnici@univr.it +39 045 802 7045

Boscaini Maurizio

maurizio.boscaini@univr.it

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

Drago Nicola

nicola.drago@univr.it 045 802 7081

Fiorini Paolo

paolo.fiorini@univr.it 045 802 7963

Fummi Franco

franco.fummi@univr.it 045 802 7994

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

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

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

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.

TeachingsCreditsTAFSSD
6
A
(MAT/02)
12
A
(ING-INF/05)
6
A
(FIS/01)
6
A
(INF/01)
12
A
(INF/01)
English language competence-complete b1 level
6
E
-
TeachingsCreditsTAFSSD
12
B
(INF/01)
6
C
(FIS/01)
6
B
(ING-INF/05)
12
B
(ING-INF/05)
One course to be chosen among the following
TeachingsCreditsTAFSSD
12
B
(ING-INF/05)
One course to be chosen among the following
6
B
(INF/01)
6
B
(INF/01)
6
F
(-)
Prova finale
6
E
(-)

1° Anno

TeachingsCreditsTAFSSD
6
A
(MAT/02)
12
A
(ING-INF/05)
6
A
(FIS/01)
6
A
(INF/01)
12
A
(INF/01)
English language competence-complete b1 level
6
E
-

2° Anno

TeachingsCreditsTAFSSD
12
B
(INF/01)
6
C
(FIS/01)
6
B
(ING-INF/05)
12
B
(ING-INF/05)
One course to be chosen among the following

3° Anno

TeachingsCreditsTAFSSD
12
B
(ING-INF/05)
One course to be chosen among the following
6
B
(INF/01)
6
B
(INF/01)
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

Coordinatore

Alberto Belussi

Scientific Disciplinary Sector (SSD)

ING-INF/05 - INFORMATION PROCESSING SYSTEMS

Language of instruction

Italian

The teaching is organized as follows:

Teoria

Credits

6

Period

I sem.

Academic staff

Alberto Belussi

Laboratorio

Credits

3

Period

II sem.

Academic staff

Roberto Posenato

Tecnologie per le basi di dati

Credits

3

Period

II sem.

Academic staff

Alberto Belussi

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Learning outcomes

The learning targets are presented for each module of the course.

Module of Theory
--------------------------
The first part of the course, called “Databases Theory”, has the aim to provide the student with the necessary concepts and methods for the design of a database and its applications. In particular, it will be focused on the methodologies for the conceptual and logical design of a database and for the successive database implementation on database systems. Moreover, the fundamental characteristics of some query languages will be illustrated: in particular SQL (in Lab) and of the relational algebra .

Module of Lab
------------------------
The aim of this module is to provide the student with the necessary concepts and methods for operating with a database management system and developing web applications exploiting databases. The main technologies considered during the course are based on Python language. Python will be introduced during the course. To attend the course in a productive way, students have to be confident with object-oriented programming.

Module of Database technology
------------------------
The second part of the course has the aim to provide the student with the necessary concepts and methods for the effective usage of relational database systems (RDBMS). In particular, this module will focus on: transactions, concurrency control techniques, recovery management, indices, techniques for interacting with a RDBMS from a program. Finally some concepts regarding current approaches for modeling semi-structured data will be presented (XML and XML schema).

At the end of the course, the students will be able to understand how a database management system works and they will know how to:
- design and implement relational databases;
- develop web applications that interact with relational databases.

Considering the learning targets of the degree in Computer Science this course helps to provide the student with:
- the necessary expertise for designing, development, implementation, management and maintenance of database management systems
- the basic expertise in the fields: programming, database and information systems

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, join in SQL, the GROUP BY and ORDER BY clauses, using subqueries. Views.

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.
- Introduction to Flask (Python) micro framework for developing simple database-based web applications.

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.

Examination Methods

The exam is composed of two parts: theory and laboratory.

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 and Database technology
----------------------------------------------------------------
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 three tests: the first test regards the design of a relational database: conceptual design (E-R model) and logic design (relational model), this weighs 4/9 of the theory grade; the second test regards the specification of queries on a relational database in relational algebra and SQL, this test weighs 3/9 of the theory grade; the third test on the program module of Databases Technologies, the latter test weighs 2/9 of the theory grade.

Module of Laboratorio
---------------------------------
The examination consists of a written test containing 5 exercises based on the module program. The grade in this module is worth 1/4 of the grade in the course examination. A selection of previous exam tests is published at http://profs.scienze.univr.it/~posenato/courses/labBD/raccoltaTemiEsameLaboratorioBasiDatiDal2016.pdf

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

Bibliografia

Reference texts
Activity Author Title Publishing house Year ISBN Notes
Teoria P. Atzeni, S. Ceri, P. Fraternali, S. Paraboschi, R. Torlone Basi di dati (Edizione 4) McGraw-Hill 2014 978-88-386-6587-5
Teoria E. Baralis, A. Belussi, G. Psaila Basi di dati - Temi d'esame svolti (Edizione 1) Progetto Leonardo Società Editrice Esculapio Bologna 1999 B135655713
Laboratorio Autori Vari Flask (http://flask.pocoo.org/) Flask 2016
Laboratorio Autori Vari Manuale di Postgresql (https://www.postgresql.org/docs/) Postgresql  
Tecnologie per le basi di dati P. Atzeni, S. Ceri, P. Fraternali, S. Paraboschi, R. Torlone Basi di dati (Edizione 4) McGraw-Hill 2014 978-88-386-6587-5

Tipologia di Attività formativa D e F

Academic year

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.

University Language Centre - CLA

Allegati


Area riservata studenti


Tutorato per gli studenti

I docenti dei singoli Corsi di Studio erogano un servizio di tutorato volto a orientare e assistere gli studenti del triennio, in particolare le matricole, per renderli partecipi dell’intero processo formativo, con l’obiettivo di prevenire la dispersione e il ritardo negli studi, oltre che promuovere una proficua partecipazione attiva alla vita universitaria in tutte le sue forme.

TUTORATO PER GLI STUDENTI DELL’AREA DI SCIENZE E INGEGNERIA
Tutorato finalizzato a offrire loro un’attività di orientamento che possa essere di supporto per gli aspetti organizzativi e amministrativi della vita universitaria.
Le tutor attualemente di riferimento sono:
  • Dott.ssa Luana Uda, luana.uda@univr.it
  • Dott.ssa Roberta RIgaglia, roberta.rigaglia@univr.it

Tirocini e stage

Le attività di stage sono finalizzate a far acquisire allo studente una conoscenza diretta in settori di particolare attività per l’inserimento nel mondo del lavoro e per l’acquisizione di abilità specifiche di interesse professionale.
Le attività di stage sono svolte sotto la diretta responsabilità di un singolo docente presso studi professionali, enti della pubblica amministrazione, aziende accreditate dall’Ateneo veronese.
I crediti maturati in seguito ad attività di stage saranno attribuiti secondo quanto disposto nel dettaglio dal “Regolamento d’Ateneo per il riconoscimento dei crediti maturati negli stage universitari” vigente.

Tutte le informazioni in merito agli stage sono reperibili al link https://www.univr.it/it/i-nostri-servizi/stage-e-tirocini.
 

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

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.