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
primo semestre (lauree) Sep 28, 2020 Dec 23, 2020
secondo semestre (lauree) Feb 15, 2021 Jun 1, 2021
Exam sessions
Session From To
sessione invernale Jan 11, 2021 Feb 12, 2021
sessione estiva Jun 7, 2021 Jul 23, 2021
sessione autunnale Aug 23, 2021 Sep 17, 2021
Degree sessions
Session From To
sessione autunnale (validità a.a. 2019/20) Dec 9, 2020 Dec 11, 2020
sessione invernale (validità a.a. 2019/20) Apr 7, 2021 Apr 9, 2021
sessione estiva (validità a.a. 2020/21) Sep 6, 2021 Sep 8, 2021
Holidays
Period From To
Vacanze di Natale Dec 24, 2020 Jan 6, 2021
Vacanze di Pasqua Apr 3, 2021 Apr 6, 2021
Vacanze estive Aug 9, 2021 Aug 15, 2021

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 Enrolment FAQs

Academic staff

B C F G M N P R S V

Brunetti Federico

federico.brunetti@univr.it 045 802 8494

Bucciol Alessandro

alessandro.bucciol@univr.it 045 802 8278

Corsi Corrado

corrado.corsi@univr.it 045 802 8452 (VR) 0444/393937 (VI)

Ferrari Maria Luisa

marialuisa.ferrari@univr.it 045 802 8532

Fioroni Tamara

tamara.fioroni@univr.it 0458028489

Giaretta Elena

elena.giaretta@univr.it 045 802 8051

Menon Martina

martina.menon@univr.it

Minozzo Marco

marco.minozzo@univr.it 045 802 8234

Noto Sergio

elefante@univr.it 045 802 8008

Perali Federico

federico.perali@univr.it 045 802 8486

Roveda Alberto

alberto.roveda@univr.it Dip. Sc. Ec. 045 802 8096 C.I.D.E. 045 8028084

Salomoni Alessandra

alessandra.salomoni@univr.it 045 802 8443

Sartori Fabio

fabio.sartori@univr.it
Virginia Vannucci,  October 25, 2020

Vannucci Virginia

virginia.vannucci@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
9
A
IUS/01
9
A
SECS-P/01
9
A
SECS-S/06
9
C
SECS-P/12
English language B1 level
3
E
-
ModulesCreditsTAFSSD
9
B
SECS-P/01
9
B
SECS-P/03
9
B
SECS-S/01
ModulesCreditsTAFSSD
9
B
SECS-P/05
6
B
SECS-P/02
Training
6
F
-
Final exam
3
E
-

1° Year

ModulesCreditsTAFSSD
9
A
IUS/01
9
A
SECS-P/01
9
A
SECS-S/06
9
C
SECS-P/12
English language B1 level
3
E
-

2° Year

ModulesCreditsTAFSSD
9
B
SECS-P/01
9
B
SECS-P/03
9
B
SECS-S/01

3° Year

ModulesCreditsTAFSSD
9
B
SECS-P/05
6
B
SECS-P/02
Training
6
F
-
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.




SPlacements in companies, public or private institutions and professional associations

Type D and Type F activities

primo semestre (lauree) From 9/28/20 To 12/23/20
years Modules TAF Teacher
Future matters D Alessandro Bucciol (Coordinatore)
Future matters D Alessandro Bucciol (Coordinatore)
secondo semestre (lauree) From 2/15/21 To 6/1/21
years Modules TAF Teacher
Design and Evaluation of Economic and Social Policies D Federico Perali (Coordinatore)
Public debate and scientific writing - 2020/2021 D Martina Menon (Coordinatore)
Wake up Italia - 2020/2021 D Sergio Noto (Coordinatore)
List of courses with unassigned period
years Modules TAF Teacher
Ciclo di video conferenze: "L’economia del Covid, Verona e l’Italia. Una pandemia che viene da lontano?" - 2020/21 D Sergio Noto (Coordinatore)
Ciclo tematico di conferenze (on-line): “Come saremo? Ripensare il mondo dopo il 2020” - 2020/21 D Federico Brunetti (Coordinatore)
Marketing plan - 2020/21 D Virginia Vannucci (Coordinatore)
1° 2° 3° Data Analysis Laboratory with R (Verona) D Marco Minozzo (Coordinatore)
1° 2° 3° Data Visualization Laboratory D Marco Minozzo (Coordinatore)
1° 2° 3° Python Laboratory D Marco Minozzo (Coordinatore)
1° 2° 3° Data Science Laboratory with SAP D Marco Minozzo (Coordinatore)
1° 2° 3° Advanced Excel Laboratory (Verona) D Marco Minozzo (Coordinatore)
1° 2° 3° Excel Laboratory (Verona) D Marco Minozzo (Coordinatore)
1° 2° 3° Programming in Matlab D Marco Minozzo (Coordinatore)
1° 2° 3° Programming in SAS D Marco Minozzo (Coordinatore)

Learning outcomes

The course "Data Analysis Laboratory with R" 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 Verona campus of the School of Economics and Management.

- Due to the COVID-19 emergency, this year lessons will be delivered online through Zoom meetings. Each course has, approximately, 50 places.

- There will be two courses, one in the first semester and another one in the second semester.

- Requests for participation will be considered following the registration order, considering that priority will be given to CdLM students, in particular to students of the Master’s degree in Economics, of the Master’s degree in Economics and Data Analysis, 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 communicate their absence.

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

- 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 calendar of the course of the first semester will be available as soon as possible.

The calendar of the course of the second semester will be available as soon as possible.

Tutor (first semester): dott. Luca Bisognin
Tutor (second semester): dott. Alessandro Cipolla


For the course of the first semester, it is possible to register from the 13th of October 2020 to the 18th of October 2020.

For the courses of the second semester, it is possible to register from the 13th of October 2020 to the 28th of February 2021.

Please, register through the elearning platform (Moodle). Students without a university IT account can ask to be registered by writing an email to the coordinator of the course. All other students must use the procedure on Moodle.

Program

R è un software open-source per l’analisi statistica. Nato alla fine degli anni Novanta dal software S, R è un linguaggio multi-paradigma che nell’arco di due decenni ha acquisito un ruolo centrale tra i software che si occupano di analisi statistica, grazie anche al forte sviluppo che ha ricevuto lo sviluppo di pacchetti (attualmente più di 16000) che implementano tecniche e metodi provenienti dai campi più diversi della statistica metodologica e applicata. Negli anni più recenti, grazie allo sviluppo di un’intera famiglia di pacchetti volti a semplificare ed organizzare su nuove basi le modalità di interazione e programmazione con R, il software ha trovato nuovi sbocchi per esprimere al meglio le proprie potenzialità. Il linguaggio R, assieme a Python, è oggi considerato il linguaggio di riferimento nell’ambito della moderna data science e, in particolare, nel machine learning, e si interfacciano agevolmente con molti altri software quali Excel, Tableau, Microsoft Power BI ecc.

Il corso si propone di fornire le basi della programmazione e della logica di funzionamento del software R introducendo al contempo i partecipanti ad alcune delle innovazioni più recenti che lo stanno interessando. Oltre ad un’introduzione al linguaggio R e a R Studio, il corso verterà sui seguenti argomenti: tecniche di trattamento e manipolazione dati (data management), strumenti di grafica avanzata per l’analisi statistica, cenni sulla rappresentazione grafica di informazioni geo-referenziate, analisi di regressione, simulazioni Monte Carlo, cenni sulla reportistica automatica e sulla produzione di documenti interattivi.

Reference texts
Author Title Publishing house Year ISBN Notes
Hadley Wickham Advanced R (Edizione 1) CRC Press, Taylor & Francis Group 2015 9781466586970
Espa G., Micciolo R. Analisi esplorativa dei dati con R Apogeo 2012 978-88-503-3031-7
Ronald K. Pearson Exploratory Data Analysis Using R (Edizione 1) CRC Press, Taylor & Francis Group 2018 9781138480605
Marco Bee, Flavio Santi Finanza quantitativa con R (Edizione 1) Apogeo Education 2013 9788838787041
Hadley Wickham ggplot2: Elegant Graphics for Data Analysis (Edizione 1) Springer 2009 9780387981413
Francesca Ieva, Chiara Masci, Anna Maria Paganoni Laboratorio di Statistica con R (Edizione 2) Pearson 2016 9788891901521
Christopher P. Adams Learning Microeconometrics with R (Edizione 1) Chapman and Hall/CRC 2021 9780367255381
Benjamin S. Baumer, Daniel T. Kaplan, Nicholas J. Horton Modern Data Science with R (Edizione 1) CRC Press, Taylor & Francis Group 2017 978-1-4987-2448-7
Giuseppe Espa, Rocco Micciolo Problemi ed esperimenti di statistica con R (Edizione 1) Apogeo Education 2013 9788838786105
Hadley Wickham, Garrett Grolemund R for Data Science (Edizione 1) O'Reilly 2016 9781491910399
Ngai Hang Chan, Hoi Ying Wong Simulation Techniques in Financial Risk Management (Edizione 1) Wiley 2015 9781118735817
M. Bécue-Bertaut Textual Data Science with R (Edizione 1) CRC Press, Taylor & Francis Group 2018 9781138626911
Graham J. Williams The Essentials of Data Science: Knowledge Discovery Using R (Edizione 1) CRC Press, Taylor & Francis Group 2017 9781138088634

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, which will take place online through a Zoom meeting, will consist in a written exam, followed by an oral examination, if necessary, on the use of the software R. There will be just one date for the final examination.

Bibliography

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


Student mentoring


Internships


Gestione carriere


Linguistic training CLA


Area riservata studenti