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..

Academic year:
Definition of lesson periods
Period From To
First semester bachelor degree Sep 16, 2019 Jan 10, 2020
Second semester bachelor degree Feb 17, 2020 Jun 5, 2020
Exam sessions
Session From To
First semester intermediate tests Nov 4, 2019 Nov 8, 2019
Winter exam session Jan 13, 2020 Feb 14, 2020
Second semester intermediate tests Apr 15, 2020 Apr 17, 2020
Summer session exam Jun 8, 2020 Jul 10, 2020
Autumn Session exams Aug 24, 2020 Sep 11, 2020
Degree sessions
Session From To
Autumn Session Dec 2, 2019 Dec 4, 2019
Winter Session Apr 7, 2020 Apr 9, 2020
Summer session Sep 7, 2020 Sep 9, 2020

Exam calendar

Exam dates and rounds are managed by the relevant Economics 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 Enrollment FAQs

Academic staff

B C D F G L M P R S

Bonfanti Angelo

symbol email angelo.bonfanti@univr.it symbol phone-number 045 802 8292

Broglia Angela

symbol email angela.broglia@univr.it symbol phone-number 045 802 8240

Brunetti Federico

symbol email federico.brunetti@univr.it symbol phone-number 045 802 8494

Bucciol Alessandro

symbol email alessandro.bucciol@univr.it symbol phone-number 045 802 8278

Cantele Silvia

symbol email silvia.cantele@univr.it symbol phone-number 045 802 8220 (VR) - 0444 393943 (VI)

Chesini Giuseppina

symbol email giusy.chesini@univr.it symbol phone-number 045 802 8495 (VR) -- 0444/393938 (VI)

Cipriani Giam Pietro

symbol email giampietro.cipriani@univr.it symbol phone-number 045 802 8271

Confente Ilenia

symbol email ilenia.confente@univr.it symbol phone-number 045 802 8174

Corbella Silvano

symbol email silvano.corbella@univr.it

Corsi Corrado

symbol email corrado.corsi@univr.it symbol phone-number 045 802 8452 (VR)

Demo Edoardo

symbol email edoardo.demo@univr.it symbol phone-number 045 802 8782 (VR) 0444.393930 (VI)

Ferrari Maria Luisa

symbol email marialuisa.ferrari@univr.it symbol phone-number 045 802 8532

Giaretta Elena

symbol email elena.giaretta@univr.it symbol phone-number 045 802 8051

Guiglia Giovanni

symbol email giovanni.guiglia@univr.it symbol phone-number 045 802 8225

Lubian Diego

symbol email diego.lubian@univr.it symbol phone-number 045 802 8419
Elena Manzoni,  February 4, 2020

Manzoni Elena

symbol email elena.manzoni@univr.it symbol phone-number 8783

Mariutti Gianpaolo

symbol email gianpaolo.mariutti@univr.it symbol phone-number +390458028241

Menon Martina

symbol email martina.menon@univr.it

Minozzo Marco

symbol email marco.minozzo@univr.it symbol phone-number 045 802 8234

Mion Giorgio

symbol email giorgio.mion@univr.it symbol phone-number 045.802 8172

Pasquariello Federica

symbol email federica.pasquariello@univr.it symbol phone-number 045 802 8233

Perali Federico

symbol email federico.perali@univr.it symbol phone-number 045 802 8486

Pilati Andrea

symbol email andrea.pilati@univr.it symbol phone-number 045 802 8444 (VR) - 0444 393938 (VI)

Pizzamiglio Maurizio

symbol email maurizio.pizzamiglio@univr.it

Renò Roberto

symbol email roberto.reno@univr.it symbol phone-number 045 802 8526

Roveda Alberto

symbol email alberto.roveda@univr.it symbol phone-number Dip. Sc. Ec. 045 802 8096 C.I.D.E. 045 8028084

Salomoni Alessandra

symbol email alessandra.salomoni@univr.it symbol phone-number 045 802 8443
profilo,  January 21, 2019

Santi Flavio

symbol email flavio.santi@univr.it symbol phone-number 045 802 8239

Sartori Fabio

symbol email fabio.sartori@univr.it

Signori Paola

symbol email paola.signori@univr.it symbol phone-number 0458028492

Sommacal Alessandro

symbol email alessandro.sommacal@univr.it symbol phone-number 045 802 8716

Sproviero Alice Francesca

symbol email alicefrancesca.sproviero@univr.it symbol phone-number 045 802 8216

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 enrollment year.

1° Year

ModulesCreditsTAFSSD
9
A
IUS/01
6
B
IUS/09
9
A
SECS-P/01
9
A
SECS-S/06
English language (B1 level)
6
E/F
-

2° Year  activated in the A.Y. 2020/2021

ModulesCreditsTAFSSD
9
A
IUS/04
9
B
SECS-P/01
9
B
SECS-P/03
9
B
SECS-S/01

3° Year  activated in the A.Y. 2021/2022

ModulesCreditsTAFSSD
6
B
IUS/07
9
B
SECS-P/02
9
C
SECS-P/12
Stage
6
S
-
Final exam
3
E
-
ModulesCreditsTAFSSD
9
A
IUS/01
6
B
IUS/09
9
A
SECS-P/01
9
A
SECS-S/06
English language (B1 level)
6
E/F
-
activated in the A.Y. 2020/2021
ModulesCreditsTAFSSD
9
A
IUS/04
9
B
SECS-P/01
9
B
SECS-P/03
9
B
SECS-S/01
activated in the A.Y. 2021/2022
ModulesCreditsTAFSSD
6
B
IUS/07
9
B
SECS-P/02
9
C
SECS-P/12
Stage
6
S
-
Final exam
3
E
-
Modules Credits TAF SSD
Between the years: 1°- 2°- 3°

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

Type D and Type F activities

Nei piani didattici di ciascun Corso di studio è previsto l’obbligo di conseguire un certo numero di crediti formativi mediante attività a scelta (chiamate anche "di tipologia D e F").

Oltre che in insegnamenti previsti nei piani didattici di altri corsi di studio e in certificazioni linguistiche o informatiche secondo quanto specificato nei regolamenti di ciascun corso, tali attività possono consistere anche in iniziative extracurriculari di contenuto vario, quali ad esempio la partecipazione a un seminario o a un ciclo di seminari, la frequenza di laboratori didattici, lo svolgimento di project work, stage aggiuntivo, eccetera.

Come per ogni altra attività a scelta, è necessario che anche queste non costituiscano un duplicato di conoscenze e competenze già acquisite dallo studente.

Quelle elencate in questa pagina sono le iniziative extracurriculari che sono state approvate dal Consiglio della Scuola di Economia e Management e quindi consentono a chi vi partecipa l'acquisizione dei CFU specificati, alle condizioni riportate nelle pagine di dettaglio di ciascuna iniziativa.

Si ricorda in proposito che:
- tutte queste iniziative richiedono, per l'acquisizione dei relativi CFU, il superamento di una prova di verifica delle competenze acquisite, secondo le indicazioni contenute nella sezione "Modalità d'esame" della singola attività;
- lo studente è tenuto a inserire nel proprio piano degli studi l'attività prescelta e a iscriversi all'appello appositamente creato per la verbalizzazione, la cui data viene stabilita dal docente di riferimento e pubblicata nella sezione "Modalità d'esame" della singola attività.

ATTENZIONE: Per essere ammessi a sostenere una qualsiasi attività didattica, inlcuse quelle a scelta, è necessario essere iscritti all'anno di corso in cui essa viene offerta. Si raccomanda, pertanto, ai laureandi delle sessioni di dicembre e aprile di NON svolgere attività extracurriculari del nuovo anno accademico, cui loro non risultano iscritti, essendo tali sessioni di laurea con validità riferita all'anno accademico precedente. Quindi, per attività svolte in un anno accademico cui non si è iscritti, non si potrà dar luogo a riconoscimento di CFU.

Academic year:
Second semester bachelor degree From 2/17/20 To 6/5/20
years Modules TAF Teacher
1° 2° 3° Enactus Verona 2020 D Paola Signori (Coordinator)
1° 2° 3° Parlare in pubblico e economic writing D Martina Menon (Coordinator)
1° 2° 3° Samsung Innovation Camp D Marco Minozzo (Coordinator)
1° 2° 3° Simulation and Implementation of Economic Policies D Federico Perali (Coordinator)
List of courses with unassigned period
years Modules TAF Teacher
1° 2° 3° Il Futuro Conta! D Alessandro Bucciol (Coordinator)
1° 2° 3° Il Futuro Conta! D Alessandro Bucciol (Coordinator)
1° 2° 3° Data Analysis Laboratory with R D Marco Minozzo (Coordinator)
1° 2° 3° Data Analysis Laboratory with R (Verona) D Marco Minozzo (Coordinator)
1° 2° 3° Data Visualization Laboratory D Marco Minozzo (Coordinator)
1° 2° 3° Python Laboratory D Marco Minozzo (Coordinator)
1° 2° 3° Data Science Laboratory with SAP D Marco Minozzo (Coordinator)
1° 2° 3° Advanced Excel Laboratory (Verona) D Marco Minozzo (Coordinator)
1° 2° 3° Excel Laboratory (Verona) D Marco Minozzo (Coordinator)
1° 2° 3° The fashion lab (1 ECTS) D Angela Broglia (Coordinator)
1° 2° 3° The fashion lab (2 ECTS) D Angela Broglia (Coordinator)
1° 2° 3° The fashion lab (3 ECTS) D Angela Broglia (Coordinator)
1° 2° 3° Marketing Plan D Ilenia Confente (Coordinator)
1° 2° 3° Presente e futuro del pianeta D Federico Brunetti (Coordinator)
1° 2° 3° Programming in Matlab D Marco Minozzo (Coordinator)
1° 2° 3° Programming in SAS D Marco Minozzo (Coordinator)
1° 2° 3° Robo-Ethics D Giorgio Mion (Coordinator)
1° 2° 3° Univero' - Job Orienteering festival D Paola Signori (Coordinator)

Teaching code

4S007120

Coordinator

Marco Minozzo

Credits

3

Also offered in courses:

  • Python Laboratory of the course Bachelor's degree in Business Administration (Verona)
  • Python Laboratory of the course Bachelor's degree in Business Administration (Vicenza)
  • Python Laboratory of the course Bachelor's degree in Economics and Business (Vicenza)
  • Python Laboratory of the course Master’s degree in Economics
  • Python Laboratory of the course Master’s degree in Business Management (Vicenza)
  • Python Laboratory of the course Master’s degree in Business Administration and Corporate Law
  • Python Laboratory of the course Master’s degree in Marketing and Corporate Communication
  • Python Laboratory of the course Master’s degree in Banking and Finance
  • Python Laboratory of the course Master's degree in International Economics and Business Management
  • Python Laboratory of the course Master’s degree in Management and business strategy

Language

Italian

Scientific Disciplinary Sector (SSD)

NN - -

Period

Not yet assigned

Learning outcomes

The course "Python Laboratory" is an optional "type f" activity, which allows to students to obtain 3 CFU, once a final examination is passed. In particular:

- The course is open to all CdL and CdLM students of the School of Economics and Management, in particular to the students of the Master’s degree in Economics and of the Master’s degree in Banking and Finance.

- The lessons will take place in a computer laboratory (48 seats). To promote an active participation, students are required to bring their own portable computer.

- Requests for participation will be considered following the registration order considering that priority will be given to CdLM students, in particular to the students of the Master’s degree in Economics and of the Master’s degree in Banking and Finance. Students are required to be present at the first lesson, or to send an email to the tutor to comunicate their absence.

- Participation to the course does not require any particular background knowledge of the software Python.

- The frequency to the classes is compulsory. Students are required to attend at least 2/3 of the exercise lessons and tutorial activities in order to be admitted to the final evaluation.

The course consists of 18 hours of exercise lessons and tutorial activities (plus 2 hours of final examination).

The tentative calendar of the course is the following:

Friday 18 October 2019, hours 15:00-18:30, room LAB.SMS.4;
Friday 25 October 2019, hours 15:00-18:30, room LAB.SMS.4;
Friday 15 November 2019, hours 15:00-18:30, room LAB.SMS.1;
Friday 22 November 2019, hours 15:00-18:30, room LAB.SMS.1;
Friday 29 November 2019, hours 15:00-18:30, room LAB.SMS.1;
Friday 6 December 2019, hours 15:00-18:30, room LAB.SMS.1;
Friday 13 December 2019, hours 15:00-18:30, room LAB.SMS.8 (final exam).


Tutor: dott. Marco Zanotti

Registrations are open from the 5th of October 2019 to the 13th of October 2019.

Please, register through the elearning platform.

Program

Python is a widely used high-level programming language for general-purpose programming. It is an interpreted language, it has a design philosophy that emphasizes code readability and it has a syntax that allows programmers to express concepts in fewer lines of code than might be used in other languages, allowing new users to learn it in a few days. Python features a dynamic type system and automatic memory management and supports multiple programming paradigms, including object-oriented, imperative, functional programming, and procedural styles. It has a large and comprehensive standard library and it can easily be integrated with other programming languages, in particular with R. Python interpreters are available for many operating systems, allowing Python code to run on a wide variety of systems.

Python has gained wide popularity mainly for its use in the management and analysis of large data sets (data science). Today, R and Python are the two most widely used programming languages among data scientists. Both of them have rapidly advanced over the past few years. For these languages there exist many libraries for collecting, handling, visualizing and analyzing large data volumes and for implementing advanced machine learning models. Python is used in many organizations like NASA, Yahoo and Google. Python is open source and free software and has a community-based development model. Other information can be found at https://www.python.it/ and https://www.python.org/

The program of the course will start with an introduction to the software Python and its main functions. Then, some of the topics encountered in mathematical and statistic courses will be considered, as for example, matrix algebra, optimization and interpolation. Arguments will be presented mainly through examples. The course aims at improving the computational and programming skills of the students and at providing instruments that might be useful for the subsequent thesis work. The activity will allow students to improve the knowledge of a programming language that is highly requested in some sectors of the job market.

Reference texts
Author Title Publishing house Year ISBN Notes
Joel Grus Data Science con Python: dai fondamenti al Machine Learning (Edizione 1) Egea 2020 9788823822948
Dmitry Zinoviev Data Science con Python: dalle stringhe al machine learning, le tecniche essenziali per lavorare sui dati (Edizione 1) APOGEO 2017 9788850334148
Joel Grus Data Science from Scratch: First Principles with Python (Edizione 1) O'Reilly Media, Inc. 2015 9781491901410
Sarah Guido, Andreas C. Müller Introduction to Machine Learning with Python (Edizione 1) O'Reilly Media, Inc. 2016 9781449369880
Tony Gaddis Introduzione a Python (Edizione 1) Pearson Italia, Milano-Torino 2016 9788891900999
Samir Madhavan Mastering Python for Data Science (Edizione 1) Packt Publishing 2015 9781784390150
Ahmed Sherif Practical Business Intelligence (Edizione 1) Packt Publishing 2016 9781785885433
Toby Segaran Programming Collective Intelligence (Edizione 1) O'Reilly Media, Inc. 2007 9780596529321
Jake VanderPlas Python Data Science Handbook: Essential Tools for Working with Data (Edizione 1) O'Reilly Media, Inc. 2016 9781491912126
William Wesley McKinney Python for Data Analysis: Data Wrangling with Pandas, NumPy, and IPython (Edizione 2) O'Reilly Media, Inc. 2017 9781491957653
Vahid Mirjalili, Sebastian Raschka Python Machine Learning (Edizione 2) Packt Publishing 2017 9781787125933
Chris Albon Python Machine Learning Cookbook (Edizione 1) O'Reilly Media, Inc. 2018 9781491989371
Allen B. Downey Think Stats: Exploratory Data Analysis (Edizione 2) O'Reilly Media, Inc. 2014 9781491907344
Richard Lawson Web Scraping with Python (Edizione 1) Packt Publishing 2015 9781782164364

Examination Methods

Students are required to attend at least 2/3 of the exercise lessons/tutorial activity in order to be admitted to the final evaluation. The final examination will consist in a written exam, with an oral examination if necessary, on the use of the software Python. There will be just one date for the final examination.

Students with disabilities or specific learning disorders (SLD), who intend to request the adaptation of the exam, must follow the instructions given HERE

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: only in this way will you be able to receive notification of all the notices from your teachers and your secretariat via email and soon also via the Univr app.

Graduation

List of theses and work experience proposals

theses proposals Research area
Tesi di laurea - Il credit scoring Statistics - Foundational and philosophical topics
La performance delle imprese che adottano politiche di Corporate Social responsibility Various topics
La previsione della qualita' dei vini: Il caso dell'Amarone Various topics
Proposte di tesi Various topics
Tesi in Macroeconomia Various topics
tesi triennali Various topics

Student mentoring


Linguistic training CLA


Gestione carriere


Internships


Student login and resources