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
primo semestre lauree magistrali Oct 1, 2018 Dec 21, 2018
secondo semestre lauree magistrali Feb 25, 2019 May 31, 2019
Exam sessions
Session From To
sessione invernale lauree magistrali Jan 7, 2019 Feb 22, 2019
sessione estiva lauree magistrali May 27, 2019 Jul 5, 2019
Sessione autunnale Aug 26, 2019 Sep 13, 2019
Degree sessions
Session From To
Sessione autunnale (validità a.a. 2017/18) Dec 6, 2018 Dec 7, 2018
Sessione invernale (validità a.a. 2017/18) Apr 3, 2019 Apr 5, 2019
Sessione estiva (validità a.a. 2018/19) Sep 10, 2019 Sep 11, 2019
Holidays
Period From To
Festa di Ognissanti Nov 1, 2018 Nov 1, 2018
Festa dell’Immacolata Dec 8, 2018 Dec 8, 2018
Vacanze di Natale Dec 22, 2018 Jan 6, 2019
Vacanze di Pasqua Apr 19, 2019 Apr 23, 2019
Festa della liberazione Apr 25, 2019 Apr 25, 2019
Festa del lavoro May 1, 2019 May 1, 2019
Festa del Santo Patrono - S. Zeno May 21, 2019 May 21, 2019
Attività sospese (vacanze estive) Aug 5, 2019 Aug 23, 2019

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

A B C D F G L M O P R S T Z

Andreoli Francesco

symbol email francesco.andreoli@univr.it symbol phone-number 045 802 8102

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)

Castellani Paola

symbol email paola.castellani@univr.it symbol phone-number 045 802 8127

Chesini Giuseppina

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

Ciampi Annalisa

symbol email annalisa.ciampi@univr.it symbol phone-number 045 802 8061

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

De Sinopoli Francesco

symbol email francesco.desinopoli@univr.it symbol phone-number 045 842 5450

Fiorentini Riccardo

symbol email riccardo.fiorentini@univr.it symbol phone-number 0444 393934 (VI) - 045 802 8335(VR)

Gaudenzi Barbara

symbol email barbara.gaudenzi@univr.it symbol phone-number 045 802 8623

Levati Maria Vittoria

symbol email vittoria.levati@univr.it symbol phone-number 045 802 8640

Lubian Diego

symbol email diego.lubian@univr.it symbol phone-number 045 802 8419

Menon Martina

symbol email martina.menon@univr.it

Messina Sebastiano Maurizio

symbol email sebastianomaurizio.messina@univr.it symbol phone-number 045 802 8052

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

Ortoleva Maria Grazia

symbol email mariagrazia.ortoleva@univr.it symbol phone-number 045 802 8052

Pellegrini Letizia

symbol email letizia.pellegrini@univr.it symbol phone-number 045 802 8345

Perali Federico

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

Pertile Paolo

symbol email paolo.pertile@univr.it symbol phone-number 045 802 8438

Picarelli Athena

symbol email athena.picarelli@univr.it symbol phone-number 045 8028242

Renò Roberto

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

Roffia Paolo

symbol email paolo.roffia@univr.it symbol phone-number 045 802 8012

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
Foto,  September 13, 2019

Taschini Luca

symbol email luca.taschini@univr.it symbol phone-number 045 802 8736

Zago Angelo

symbol email angelo.zago@univr.it symbol phone-number 045 802 8414

Zoli Claudio

symbol email claudio.zoli@univr.it symbol phone-number 045 802 8479

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.

2° Year  activated in the A.Y. 2019/2020

ModulesCreditsTAFSSD
2 courses to be chosen among the following
2 courses to be chosen among the following
6
B
SECS-P/11
6
B
SECS-P/08
Final exam
15
E
-
activated in the A.Y. 2019/2020
ModulesCreditsTAFSSD
2 courses to be chosen among the following
2 courses to be chosen among the following
6
B
SECS-P/11
6
B
SECS-P/08
Final exam
15
E
-
Modules Credits TAF SSD
Between the years: 1°- 2°

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

Academic year:
List of courses with unassigned period
years Modules TAF Teacher
Data discovery for business decisions D Claudio Zoli (Coordinator)
Elements of financial risk management D Claudio Zoli (Coordinator)
Introduction to business plan D Paolo Roffia (Coordinator)
Professional communication for economics (3 cfu) D Claudio Zoli (Coordinator)
Regulation, procurement and competition D Claudio Zoli (Coordinator)
SFIDE - Europe D Claudio Zoli (Coordinator)
1° 2° Advanced risk and portfolio management bootcamp (online) (3 cfu) D Roberto Renò (Coordinator)
1° 2° Advanced risk and portfolio management bootcamp (onsite) (6 cfu) D Roberto Renò (Coordinator)
1° 2° Convegno "gli scambi commerciali con l'estero: questioni fiscali, doganali e contrattuali" D Sebastiano Maurizio Messina (Coordinator)
1° 2° English for business and economics D Claudio Zoli (Coordinator)
1° 2° Ineka conference 2019 teamworking membership D Federico Brunetti (Coordinator)
1° 2° Introduction to spatial analysis and data visualization D Claudio Zoli (Coordinator)
1° 2° Data Visualization Laboratory D Marco Minozzo (Coordinator)
1° 2° Python Laboratory D Marco Minozzo (Coordinator)
1° 2° Advanced Excel Laboratory (Verona) D Marco Minozzo (Coordinator)
1° 2° Excel Laboratory (Verona) D Marco Minozzo (Coordinator)
1° 2° "le grandi trasformazioni degli anni '60-'70 e l'italia cinquant'anni dopo" D Angelo Zago (Coordinator)
1° 2° Social responsibility model for the restaurants' ecosystems D Silvia Cantele (Coordinator)
1° 2° Marketing Plan D Ilenia Confente (Coordinator)
1° 2° Polis - festival biblico in universita' D Giorgio Mion (Coordinator)
1° 2° Predictive analytics for business decisions D Claudio Zoli (Coordinator)
1° 2° Programming in Matlab D Diego Lubian (Coordinator)
1° 2° Programming in R D Diego Lubian (Coordinator)
1° 2° Programming in SAS D Diego Lubian (Coordinator)
1° 2° Programming Stata (3 cfu) D Diego Lubian (Coordinator)
1° 2° Quality and problem solving in business organizations D Paola Castellani (Coordinator)
1° 2° La competitività regionale e le sue risorse endogene: il concetto di capitale territoriale D Riccardo Fiorentini (Coordinator)
1° 2° Soft skills in action D Paola Signori (Coordinator)
1° 2° Tools for applied economic analysis D Claudio Zoli (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 (Verona)
  • Python Laboratory of the course Bachelor's degree in Economics and Business (Vicenza)
  • Python Laboratory of the course Master’s degree in Business Management (Vicenza)
  • 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 Business Administration and Corporate Law

Language

English en

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 in economics and business administration, 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 (46 seats).

- 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.

- 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 19 October 2018, hours 14:00-17:30, room LAB.SMS.8;
Friday 26 October 2018, hours 14:00-17:30, room LAB.SMS.8;
Friday 23 November 2018, hours 14:00-17:30, room LAB.SMS.8;
Friday 30 November 2018, hours 14:00-17:30, room LAB.SMS.8;
Friday 7 December 2018, hours 14:00-17:30, room LAB.SMS.8;
Friday 14 December 2018, hours 14:00-17:30, room LAB.SMS.8.

Tutor: dott. Marco Zanotti

Registrations are open from the 11th of October 2018 to the 18th of October 2018.

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
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

The final examination will consist in a written exam, with an oral examination if necessary, on the use of the software Python.

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.

Linguistic training CLA


Gestione carriere


Student login and resources


Graduation

List of theses and work experience proposals

theses proposals Research area
La (cattiva) gestione dei fondi comunitari in Italia ECONOMICS - ECONOMICS
Analisi dell'Impatto della Regolamentazione: potenziale e applicazioni concrete Various topics
Costs and benefits of the new Turin-Lyon railway line Various topics
Costs and benefits of new systems for speed control on italian motorways Various topics
Contingent valuation for the quality of hospital characteristics Various topics
Evaluating occupational impacts of large investment projects Various topics

Internships


Admission policy

ADMISSION POLICY

The admission procedure for international students is explained in details at:
www.magecverona.it/admission-benefits/
For further information please contact magec@dse.univr.it


Additional information

 

Additional information

For further information visit the program website, http://magec.dse.univr.it, or send an email at magec@dse.univr.it.