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
I semestre Oct 1, 2020 Jan 29, 2021
II semestre Mar 1, 2021 Jun 11, 2021
Exam sessions
Session From To
Sessione invernale d'esame Feb 1, 2021 Feb 26, 2021
Sessione estiva d'esame Jun 14, 2021 Jul 30, 2021
Sessione autunnale d'esame Sep 1, 2021 Sep 30, 2021
Holidays
Period From To
Festa dell'Immacolata Dec 8, 2020 Dec 8, 2020
Vacanze Natalizie Dec 24, 2020 Jan 3, 2021
Vacanze Pasquali Apr 2, 2021 Apr 5, 2021
Festa del Santo Patrono May 21, 2021 May 21, 2021
Festa della Repubblica Jun 2, 2021 Jun 2, 2021
Vacanze estive Aug 9, 2021 Aug 15, 2021

Exam calendar

Exam dates and rounds are managed by the relevant Science and Engineering 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 I M O P Q R S T V Z

Albi Giacomo

symbol email giacomo.albi@univr.it symbol phone-number +39 045 802 7913

Badino Massimiliano

symbol email massimiliano.badino@univr.it symbol phone-number +39 045 802 8459

Bazzani Claudia

symbol email claudia.bazzani@univr.it symbol phone-number 0458028734

Begalli Diego

symbol email diego.begalli@univr.it symbol phone-number 045 8028731

Boscolo Galazzo Ilaria

symbol email ilaria.boscologalazzo@univr.it symbol phone-number +39 045 8127804

Carra Damiano

symbol email damiano.carra@univr.it symbol phone-number +39 045 802 7059

Carradore Marco

symbol email marco.carradore@univr.it

Castellini Alberto

symbol email alberto.castellini@univr.it symbol phone-number +39 045 802 7908

Ceccato Mariano

symbol email mariano.ceccato@univr.it

Chiarini Andrea

symbol email andrea.chiarini@univr.it symbol phone-number 045 802 8223

Cobelli Nicola

symbol email nicola.cobelli@univr.it symbol phone-number 0458028295

Collet Francesca

symbol email francesca.collet@univr.it symbol phone-number +39 045 802 7979

Confente Ilenia

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

Dai Pra Paolo

symbol email paolo.daipra@univr.it symbol phone-number +39 045 802 7093

Dalla Preda Mila

symbol email mila.dallapreda@univr.it

D'Asaro Fabio Aurelio

symbol email fabioaurelio.dasaro@univr.it symbol phone-number 0458028431

Di Persio Luca

symbol email luca.dipersio@univr.it symbol phone-number +39 045 802 7968

Farinelli Alessandro

symbol email alessandro.farinelli@univr.it symbol phone-number +39 045 802 7842

Gaudenzi Barbara

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

Giachetti Andrea

symbol email andrea.giachetti@univr.it symbol phone-number +39 045 8027998

Guerra Giorgia

symbol email giorgia.guerra@univr.it

Marastoni Niccolo'

symbol email niccolo.marastoni@univr.it

Mola Lapo

symbol email lapo.mola@univr.it symbol phone-number 0458028565

Owusu Abigail

symbol email abigail.owusu@univr.it

Paci Federica Maria Francesca

symbol email federicamariafrancesca.paci@univr.it symbol phone-number +39 045 802 7909

Pelgreffi Igor

symbol email igor.pelgreffi@univr.it

Quintarelli Elisa

symbol email elisa.quintarelli@univr.it symbol phone-number +39 045 802 7852
Foto Alice,  November 22, 2017

Raffaele Alice

symbol email alice.raffaele@univr.it

Setti Francesco

symbol email francesco.setti@univr.it symbol phone-number +39 045 802 7804

Troiano Stefano

symbol email stefano.troiano@univr.it symbol phone-number +39 045 8425317

Vadala' Rosa Maria

symbol email rosamaria.vadala@univr.it

Zardini Alessandro

symbol email alessandro.zardini@univr.it symbol phone-number 045 802 8565

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

2° Year  activated in the A.Y. 2021/2022

ModulesCreditsTAFSSD
Training
6
F
-
Final exam
22
E
-
activated in the A.Y. 2021/2022
ModulesCreditsTAFSSD
Training
6
F
-
Final exam
22
E
-
Modules Credits TAF SSD
Between the years: 1°- 2°
1 module among the following (1st year: Big Data epistemology and Social research; 2nd year: Cybercrime, Data protection in business organizations, Comparative and Transnational Law & Technology)
6
C
IUS/17
Between the years: 1°- 2°
2 courses among the following (1st year: Business analytics, Digital Marketing and market research; 2nd year: Logistics, Operations & Supply Chain, Digital transformation and IT change, Statistical methods for Business intelligence)
Between the years: 1°- 2°
2 courses among the following (1st year: Complex systems and social physics, Discrete Optimization and Decision Making, 2nd year: Statistical models for Data Science, Continuous Optimization for Data Science, Network science and econophysics, Marketing research for agrifood and natural resources)
Between the years: 1°- 2°
2 courses among the following (1st year: Data Visualisation, Data Security & Privacy, Statistical learning, Mining Massive Dataset, 2nd year: Machine Learning for Data Science)
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

Teaching code

4S009084

Coordinator

Barbara Vettori

Credits

6

Language

English en

Scientific Disciplinary Sector (SSD)

IUS/17 - CRIMINAL LAW

Period

Secondo semestre dal Mar 7, 2022 al Jun 10, 2022.

Learning outcomes

The course will provide the conceptual, methodological and cultural basis to analyze and study the
“ICTs Criminal Law”, cybercrimes and computer-related crimes and the “technological investigations”, developing the capacity in using correct and specific language and discourse. Students will gain, following this method and in subiecta materia, legal and technical expertise both on substantive criminal law and procedure criminal law levels.
The course will study the new illegal phenomena related to the use of the new technologies and Internet, also through social networks (for example: online defamation, frauds - connected to online banking, phishing, identity theft - privacy violation, copyright infringement, child pornography, child grooming, cyberterrorism, cyber laundering).
The course will analyze, taking into consideration real cases, the applicable criminal law, in particular for
illegal activities down to the new concept of “cybercrime”, which is a transnational and global crime.
For this reason it’s necessary to analyze the most important international and European legal sources (Cybercrime Convention and Lanzarote Convention of the Council of Europe, European directives on: attack against information systems, child pornography, intellectual property, e-commerce and privacy)
Special attention will be given to the Internet Service Providers criminal liability, subject of recent European Court of Justice and Italian Corte di Cassazione judgements (cases Google, Netlog etc.).
In this area particular attention will be paid to the need to regulate the collection of data and the digital evidence, which are becoming increasingly important for the detection and prosecution of every criminal offence, not only “cybercrime”.

At the end of the course the student has to show to have acquired the following skills:
● knowledge of the specific technical language in the context of crimes falling into to the category of cybercrime
● knowledge of the methods and tools for the determination of cybercrimes, with specific reference to current regulations and concrete cases
● knowledge of the legal consequences, both criminal and civil, of the crimes generally ascribable to the cyber-crime area.

Program

PART 1. Cybercrime: the phenomenon – prof. Andrea Di Nicola
Monday 21 Mar 10.30 -12.30 Crime in the «digital society»: examples of criminological studies
Wednesday 23 Mar 10.30 -12.30 Cybercrime typologies and modus operandi (1)
Monday 28 Mar 10.30 -12.30 Cybercrime typologies and modus operandi (2)
Wednesday 30 Mar 10.30 -12.30 AI and ML in cybercrime
Monday 4 Apr 10.30 -12.30 Defining cybercrime from a criminological perspective: cybercrime vs. digital crime
Wednesday 6 Apr 10.30 -12.30 Measuring cybercrime: data sources and challenges
Monday 11 Apr 10.30 -12.30 Explaining cybercrime: criminological theories (1)
Wednesday 13 Apr 10.30 -12.30 Explaining cybercrime: criminological theories (2)

PART 2. Cybercriminals: focusing on authors – prof. Barbara Vettori
Tuesday 19 Apr Easter holidays’ break
Wednesday 20 Apr 10.30 -12.30 Profiling cybercriminals (1)
Tuesday 26 Apr 9.30 -11.30 Profiling cybercriminals (2)
Wednesday 27 Apr 10.30 -12.30 Cyber-organised criminals / cyber-criminal associations

PART 3. Cybercrime victims – prof. Barbara Vettori
Tuesday 3 May 9.30 -11.30 The emergence of cybervictimology
Wednesday 4 May 10.30 -12.30 Profiling cybercrime victims

PART 4. Responding to cybercrime: prevention strategies –prof. Barbara Vettori
Tuesday 10 May 9.30 -11.30 Primary, secondary and tertiary prevention strategies (1)
Wednesday 11 May 10.30 -12.30 Primary, secondary and tertiary prevention strategies (2)
Tuesday 17 May 9.30 -11.30 Focusing on AI and ML as prevention strategy
Cybercrime prevention: what works, what does not, what is promising

PART 5. Responding to cybercrime: cybercriminal law and criminal procedure at the national and international level – dr. Rosa Maria Vadalà
Wednesday 18 May 10.30 -12.30 The Law Cyber-Revolution’s Challenges and the main international legal sources (1)
Tuesday 24 May 9.30 -11.30 The Law Cyber-Revolution’s Challenges and the main international legal sources (2)
Wednesday 25 May 10.30 -12.30 The EU Directives about cybercrimes
Tuesday 31 May 9.30 -11.30 EU Directive on E-commerce and Internet Service Providers criminal liability
Wednesday 1 June 10.30 -12.30 Cybercrime offences – Italian criminal legislation (1)
Tuesday 7 June 9.30 -11.30 Cybercrime offences – Italian criminal legislation (2)
Wednesday 8 June 10.30 -12.30 Cybercriminal procedure law and technological investigations (1)
Tuesday 14 June 9.30 -11.30 Cybercriminal procedure law and technological investigations (2)

Teaching rooms:
Monday and Tuesday = aula L, Ca' Vignal 2
Wednesday: aula T.02, Ca' Vignal 3
On the 4th and 11th of May lectures will be held in aula C, Ca' Vignal 1

Bibliography

Visualizza la bibliografia con Leganto, strumento che il Sistema Bibliotecario mette a disposizione per recuperare i testi in programma d'esame in modo semplice e innovativo.

Examination Methods

Oral exam on:
1) the notes and materials distributed/discussed in the classroom;
2) the materials listed in the Readings doc.
The exam will be in English.

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

Type D and Type F activities

Documents and news

Academic year:

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 also via the Univr app.

Graduation

Deadlines and administrative fulfilments

For deadlines, administrative fulfilments and notices on graduation sessions, please refer to the Graduation Sessions - Science and Engineering service.

Need to activate a thesis internship

For thesis-related internships, it is not always necessary to activate an internship through the Internship Office. For further information, please consult the dedicated document, which can be found in the 'Documents' section of the Internships and work orientation - Science e Engineering service.

Final examination regulations

Upon completion of the Degree programme, students will need to submit and present their thesis/dissertation, which must be in English and focusing on a scientific topic covered during the programme. Alternatively, the thesis/dissertation may consist of the analysis and solution of a case study (theoretical and/or relevant to a real industrial context), experimental work, possibly developed as part of an internship, or original and independent research work that may include mathematical formalisation, computer design and a business-oriented approach.

These activities will be carried out under the guidance of a Thesis Supervisor at a University facility, or even outside the University of Verona, either in Italy or abroad, provided that they are recognised and accepted for this purpose in accordance with the teaching regulations of the Master's Degree programme in Data Science.

22 CFU credits shall be awarded for the final examination (assessment of the thesis/dissertation).

The Graduation Committee, which is in charge of the evaluation of the final examination (presentation of the dissertation in English) shall evaluate each candidate, based on their achievements throughout the entire degree programme, carefully assessing the degree of consistency between educational and professional objectives, as well as their ability for independent intellectual elaboration, critical thinking, communication skills and general cultural maturity, in relation to the objectives of the Master's Degree programme in Data Science, and in particular, in relation to the topics dealt with by the candidate in their thesis.

Students may take the final exam only after they have passed all the other modules and exams that are part of their individual study plan, and fulfil all the necessary administrative requirements, in accordance with the terms indicated in the General Study Manifesto.

The graduation exam and ceremony will be carried out by the Graduation Committee appointed by the Chair of the Teaching Committee and composed of a President and at least four other members chosen among the University's lecturers.

The thesis/dissertation will be assessed by the Dissertation Committee, which is composed of three lecturers possibly including the Thesis Supervisor, and appointed by the Chair of the Teaching Committee. The Dissertation Committee shall produce an evaluation of the dissertation, which will be submitted to the Graduation Committee, which will issue the final graduation mark. The Teaching Committee shall govern the procedures of the Dissertation Committee and the Graduation Committee, and any procedures relating to the score awarded for the final exam through specific regulations issued by the Teaching Committee.

Documents

Title Info File
File pdf Regolamento esame finale | Final exam regulation pdf, it, 387 KB, 27/04/22

List of thesis proposals

theses proposals Research area
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)
Domain Adaptation Computing Methodologies - IMAGE PROCESSING AND COMPUTER VISION
Domain Adaptation Computing methodologies - Machine learning

Career management


Student login and resources


Erasmus+ and other experiences abroad


Attendance modes and venues

As stated in the Teaching Regulations, attendance at the course of study is not mandatory.

Part-time enrolment is permitted. Find out more on the Part-time enrolment possibilities page.

The course's teaching activities take place in the Science and Engineering area, which consists of the buildings of Ca‘ Vignal 1, Ca’ Vignal 2, Ca' Vignal 3 and Piramide, located in the Borgo Roma campus. 
Lectures are held in the classrooms of Ca‘ Vignal 1, Ca’ Vignal 2 and Ca' Vignal 3, while practical exercises take place in the teaching laboratories dedicated to the various activities.