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.
Course calendar
The Academic Calendar sets out the degree programme lecture and exam timetables, as well as the relevant university closure dates..
Period | From | To |
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I semestre | Oct 1, 2020 | Jan 29, 2021 |
II semestre | Mar 1, 2021 | Jun 11, 2021 |
Session | From | To |
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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 |
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.
Academic staff
Raffaele Alice
alice.raffaele@univr.itStudy 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
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2° Year activated in the A.Y. 2021/2022
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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.
Comparative and transnational law & technology (2021/2022)
Teaching code
4S009086
Teacher
Coordinator
Credits
6
Language
English
Scientific Disciplinary Sector (SSD)
IUS/02 - COMPARATIVE PRIVATE LAW
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 offer basic legal concepts students 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 study-cases; analysis of video-clips on specific legal issues; and analysis of regulatory documents .
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
Bibliography
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
Documents and news
- Regolamento didattico 2020/2021 (pdf, it, 470 KB, 12/04/21)
years | Modules | TAF | Teacher |
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1° | The course provides an introduction to blockchain technology. It focuses on the technology behind Bitcoin, Ethereum, Tendermint and Hotmoka. | D |
Nicola Fausto Spoto
(Coordinator)
|
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 |
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Regolamento esame finale | Final exam regulation | pdf, it, 387 KB, 27/04/22 |
List of thesis proposals
theses proposals | Research area |
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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.