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. 2021/2022

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 20, 2021 Jan 14, 2022
secondo semestre (lauree) Feb 21, 2022 Jun 1, 2022
Exam sessions
Session From To
sessione invernale Jan 17, 2022 Feb 18, 2022
sessione estiva Jun 6, 2022 Jul 8, 2022
sessione autunnale Aug 22, 2022 Sep 16, 2022
Degree sessions
Session From To
sessione autunnale (validità a.a. 2020/2021) Dec 6, 2021 Dec 10, 2021
sessione invernale (validità a.a. 2020/2021) Apr 6, 2022 Apr 8, 2022
sessione estiva (validità a.a. 2021/2022) Sep 5, 2022 Sep 6, 2022

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

C F G M P R S V

Cantele Silvia

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

Cicogna Veronica

veronica.cicogna@univr.it 045 802 8246

Cipriani Giam Pietro

giampietro.cipriani@univr.it 045 802 8271

Corbella Silvano

silvano.corbella@univr.it 045 802 8217

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

Manzoni Elena

elena.manzoni@univr.it 8783

Menon Martina

martina.menon@univr.it 045 802 8420

Minozzo Marco

marco.minozzo@univr.it 045 802 8234

Pasquariello Federica

federica.pasquariello@univr.it 045 802 8233

Peretti Alberto

alberto.peretti@univr.it 0444 393936 (VI) 045 802 8238 (VR)

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

Sommacal Alessandro

alessandro.sommacal@univr.it 045 802 8716

Sproviero Alice Francesca

alicefrancesca.sproviero@univr.it 045 802 8216

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/07)
9
A
(SECS-P/01)
9
A
(SECS-S/06)
9
B
(SECS-P/08)
9
C
(SECS-P/12)
ModulesCreditsTAFSSD
9
B
(SECS-P/01)
9
B
(SECS-P/07)
9
B
(SECS-P/03)
9
B
(SECS-S/01)
9
C
(SECS-P/09)
ModulesCreditsTAFSSD
9
B
(SECS-P/05)
6
B
(SECS-P/02)
2 MODULES TO BE CHOSEN AMONG THE FOLLOWING
6
F
(-)
Prova finale
3
E
(-)

1° Year

ModulesCreditsTAFSSD
9
A
(IUS/01)
9
A
(SECS-P/07)
9
A
(SECS-P/01)
9
A
(SECS-S/06)
9
B
(SECS-P/08)
9
C
(SECS-P/12)

2° Year

ModulesCreditsTAFSSD
9
B
(SECS-P/01)
9
B
(SECS-P/07)
9
B
(SECS-P/03)
9
B
(SECS-S/01)
9
C
(SECS-P/09)

3° Year

ModulesCreditsTAFSSD
9
B
(SECS-P/05)
6
B
(SECS-P/02)
2 MODULES TO BE CHOSEN AMONG THE FOLLOWING
6
F
(-)
Prova finale
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

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.

secondo semestre (lauree) From 2/21/22 To 6/1/22
years Modules TAF Teacher
1° 2° AN INTRODUCTION TO LATEX TYPESETTING SYSTEM D Alberto Peretti (Coordinatore)

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.

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

- The course will take place in the first semester; there will be just one course.

- 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, of the Master’s degree in Economics and Data Analysis, and of the Master’s degree in Banking and Finance. Students are required to participate to 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 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 calendar of the course will be available as soon as possible.

Tutor: dott. Enrico De Vecchi


Registrations are open from the 13th of October 2020 to the 18th of October 2020.

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

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.

Bibliografia

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
Paul Deitel, Harvey Deitel Introduzione a Python: per l'informatica e la data science (Edizione 1) Pearson Italia 2021 9788891915924
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, 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 Python. There will be just one date for the final examination.

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


Internships


Student mentoring


Linguistic training CLA


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.