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 Oct 4, 2021 Jan 28, 2022
Secondo semestre Mar 7, 2022 Jun 10, 2022
Exam sessions
Session From To
Sessione invernale d'esame Jan 31, 2022 Mar 4, 2022
Sessione estiva d'esame Jun 13, 2022 Jul 29, 2022
Sessione autunnale d'esame Sep 1, 2022 Sep 29, 2022
Degree sessions
Session From To
Sessione di laurea estiva Jul 20, 2022 Jul 20, 2022
Sessione di laurea autunnale Oct 19, 2022 Oct 19, 2022
Sessione invernale Mar 15, 2023 Mar 15, 2023

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 Enrolment FAQs

Academic staff

A B C D F G I M P Q S Z

Albi Giacomo

giacomo.albi@univr.it +39 045 802 7913

Badino Massimiliano

massimiliano.badino@univr.it +39 045 802 8459

Bazzani Claudia

claudia.bazzani@univr.it 0458028734

Begalli Diego

diego.begalli@univr.it +39 045 8028731

Boscolo Galazzo Ilaria

ilaria.boscologalazzo@univr.it +39 045 8127804

Carra Damiano

damiano.carra@univr.it +39 045 802 7059

Carradore Marco

marco.carradore@univr.it

Castellini Alberto

alberto.castellini@univr.it +39 045 802 7908

Ceccato Mariano

mariano.ceccato@univr.it

Chiarini Andrea

andrea.chiarini@univr.it 045 802 8223

Confente Ilenia

ilenia.confente@univr.it 045 802 8174

Dai Pra Paolo

paolo.daipra@univr.it +39 0458027093

Dalla Preda Mila

mila.dallapreda@univr.it

Di Persio Luca

luca.dipersio@univr.it +39 045 802 7968

Farinelli Alessandro

alessandro.farinelli@univr.it +39 045 802 7842

Gaudenzi Barbara

barbara.gaudenzi@univr.it 045 802 8623

Giachetti Andrea

andrea.giachetti@univr.it +39 045 8027998

Guerra Giorgia

giorgia.guerra@univr.it

Mola Lapo

lapo.mola@univr.it 045/8028565

Paci Federica Maria Francesca

federicamariafrancesca.paci@univr.it +39 045 802 7909

Pelgreffi Igor

igor.pelgreffi@univr.it

Quintarelli Elisa

elisa.quintarelli@univr.it +39 045 802 7852

Setti Francesco

francesco.setti@univr.it +39 045 802 7804

Zardini Alessandro

alessandro.zardini@univr.it 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 enrolment year.

ModulesCreditsTAFSSD
ModulesCreditsTAFSSD
9
B/C
(IUS/01 ,M-FIL/03)
Training
6
F
-
Final exam
22
E
-

1° Year

ModulesCreditsTAFSSD

2° Year

ModulesCreditsTAFSSD
9
B/C
(IUS/01 ,M-FIL/03)
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
(SPS/07)
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.




SPlacements in companies, public or private institutions and professional associations

Teaching code

4S009086

Coordinatore

Giorgia Guerra

Credits

6

Scientific Disciplinary Sector (SSD)

IUS/02 - COMPARATIVE PRIVATE LAW

Language

English en

Period

Primo semestre dal Oct 4, 2021 al Jan 28, 2022.

Learning outcomes

This course provides students with legal notions and concepts necessary to understand the meaning, reach and scope of application of legal rules in the field of new technologies from a comparative and transnational perspective. The law of new technologies is dealt with both from a theoretical perspective, with focus on the effectiveness and efficacy of legal rules, and from a practical one, with focus on normative and contractual texts and relevant court decisions from multiple jurisdictions.

At the end of the course the student has to show to have acquired the following skills:
● knowledge of objects and methodologies of comparative law applied to new technologies, with specific reference to the notions and fundamental concepts relating to data (personal data, sensitive data, economic data, "big data")
● ability to develop an economic analysis in relations with the law of new technologies, in particular for what concerns the theory of monopoly and economies of scale (consumption, production, innovation)
● familiarity with European legal rules relating to conflict of laws and conflict of jurisdiction in matters of law and technologies and associated online dispute resolution methods
● knowledge of the basics of comparative and transnational personal identity law and in relation to digital identity and data protection laws, in particular for what concerns Europe, United States and China
● knowledge of the concept of property in comparative law, in relation to the different methods of data processing
● knowledge of the basics of comparative and European intellectual property law and competition applied to new technologies (data protection, software and database protection in Europe, the United States and China, unfair competition and competition, abuse of a dominant position, anti-competitive agreements , relations between competition law and "big data"
● knowledge of the basics of European, comparative and transnational law for what concerns contracts based on new technologies and data transfer
● ability to evaluate the transmission and processing of data and consumer protection rules.

Program

Detailed program - Comparative and Transnational Law & Technology
!! Students are not required to have a background in Law or any specific preparation in law. Every class will explain you basic legal concepts you need to know.
Classes will be based on frontal lectures - devoted to the transmission of key notions and concepts and supported by PowerPoint presentations - and group discussions on cases.
From time to time you will be required to read in advance an article or to find out information about a current case. Every class will be introduced by discussion a case scenario/phenomenon. Active participation is highly encouraged!
INTRODUCTION
1. Introduction to the course: general information, a whole perspective of “Technology governance” and the Algorithm Regulation; Methods and perspective; Typical structure of the class, included lectures, workshops, study of literature, analysis of case studies, Work and discussion groups

PART I TECHNOLOGY LAW, REGULATION AND GOVERNANCE. INTRODUCTORY THEORETICAL CONCEPTS AND BASIC NOTIONS
1. The regulatory tool box for technology
2. (continue) Technological change: challenges for law
3. The legal value of DATA (Big Data; AI..)
4. Discussion groups (the “Moral Machine”)

PART II MAIN REGULATORY COORDINATES: AN INTRICATE FRAMEWORK
5. Data governance and data driven regulation
6. Artificial Intelligence governance and regulation in EU and in Comparative Perspective
7. The law of Digital Platforms
9. Privacy and Data Protection: the intersection between data and fundamental rights
10. (continue) The data protection: technology and the legal change in data protection
11. Complicating the picture: the regulation of a “digital ecosystem”

PART III REGULATING DIGITAL DATA IMPACTS ON DIFFERENT DOMAINS
12. Contracts in the Digital Single Market
13. (continue) Payment with data (“How much is it? It’s free”….)
14. Smart contracts and blockchain
15. Safety and Liability for AI, algorithms and robots
16. (continue) Safety and Liability for AI, algorithms and robots in different domains
17. Consumers Protection and the Challenges of Smart Products
18. (continue) Consumer protection: The right to be informed in digital context. Discussion Group
19. Intellectual Property and digital data
20. Competition law in digital market
21. (continue) Competition Law matters
22. Digital Data and personal rights post mortem
23. AI, the judiciary system and the on-line dispute resolutions
24. Conclusions

Examination Methods

Students that have regularly attended classes (both in class or via streaming) will have an oral exam. Active participation during the classes will be positively take into account.
Non-attending students are required to take an oral exam. The exam will consist of an oral discussion, aimed at verifying the knowledge of the fundamentals of Technology Law as dealt with in the textbook.

Erasmus students that have regularly attended classes are granted the possibility to write an essay on a topic assigned by the instructor.

Type D and Type F activities

Le attività formative di tipologia D o F comprendono gli insegnamenti impartiti presso l'Università di Verona o periodi di stage/tirocinio professionale.
Nella scelta delle attività di tipo D, gli studenti dovranno tener presente che in sede di approvazione si terrà conto della coerenza delle loro scelte con il progetto formativo del loro piano di studio e dell'adeguatezza delle motivazioni eventualmente fornite. Dal 1° dicembre 2021 al 27 febbraio 2022 e dal 2 maggio 2022 al 15 luglio 2022, tramite il presente modulo gli studenti possono richiedere l'inserimento di attività didattiche in TAF D ed F che non possono inserire autonomamente nel proprio piano di studi tramite la procedura on-line.

COMPETENZE LINGUISTICHE - dal 1° ottobre 2021 (Delibera del Consiglio della Scuola di Scienze e Ingegneria del 30 marzo 2021) per gli immatricolati dall'A.A. 2021/2022

  • Lingua inglese: vengono riconosciuti automaticamente 3 CFU per ogni livello di competenza superiore a quello richiesto dal corso di studio (se non già riconosciuto nel ciclo di studi precedente).
  • Altre lingue e italiano per stranieri: vengono riconosciuti automaticamente 3 CFU per ogni livello di competenza a partire da A2 (se non già riconosciuto nel ciclo di studi precedente).
Tali CFU saranno riconosciuti, fino ad un massimo di 6 CFU complessivi, di tipologia F se il piano didattico lo consente, oppure di tipologia D.
Ulteriori crediti a scelta per conoscenze linguistiche potranno essere riconosciuti solo se coerenti con il progetto formativo dello studente e se adeguatamente motivati.

COMPETENZE TRASVERSALI
Scopri i percorsi formativi promossi dal  Teaching and learning centre dell'Ateneo, destinati agli studenti iscritti ai corsi di laurea, volti alla promozione delle competenze trasversali:

Modules not yet included

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

List of theses and work experience 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

Gestione carriere


Attendance

As stated in point 25 of the Teaching Regulations for the A.Y. 2021/2022, attendance at the course of study is not mandatory.
Please refer to the Crisis Unit's latest updates for the mode of teaching.

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.