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..

Definition of lesson periods
Period From To
Semester 1 Oct 3, 2022 Jan 27, 2023
Semester 2 Mar 6, 2023 Jun 16, 2023
Exam sessions
Session From To
Sessione invernale d'esame Jan 30, 2023 Mar 3, 2023
Sessione estiva d'esame Jun 19, 2023 Jul 31, 2023
Sessione autunnale d'esame Sep 4, 2023 Sep 29, 2023
Degree sessions
Session From To
Sessione estiva di laurea Jul 19, 2023 Jul 19, 2023
Sessione autunnale di laurea Oct 18, 2023 Oct 18, 2023
Sessione invernale di laurea Mar 11, 2024 Mar 11, 2024
Holidays
Period From To
Ponte Festa di tutti i Santi Oct 31, 2022 Nov 1, 2022
Ponte dell'Immacolata Concezione Dec 8, 2022 Dec 9, 2022
Vacanze natalizie Dec 23, 2022 Jan 8, 2023
Vacanze di Pasqua Apr 7, 2023 Apr 10, 2023
Festa della Liberazione Apr 24, 2023 Apr 25, 2023
Festa dei Lavoratori May 1, 2023 May 1, 2023
Festa del Santo Patrono May 21, 2023 May 21, 2023
Festa della Repubblica Jun 2, 2023 Jun 2, 2023
Chiusura estiva Aug 14, 2023 Aug 19, 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 Enrollment FAQs

Academic staff

A B C D 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

Bazzoni Damiano

symbol email damiano.bazzoni@univr.it

Begalli Diego

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

Blasi Silvia

symbol email silvia.blasi@univr.it symbol phone-number 045 8028218

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

Collet Francesca

symbol email francesca.collet@univr.it symbol phone-number +39 045 8027979

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 0458027093

Dalla Preda Mila

symbol email mila.dallapreda@univr.it

D'Asaro Fabio Aurelio

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

Di Nicola Andrea

Di Persio Luca

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

Gatti Stefano

symbol email stefano.gatti@univr.it

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

Pianezzi Daniela

symbol email daniela.pianezzi@univr.it

Quintarelli Elisa

symbol email elisa.quintarelli@univr.it symbol phone-number +390458027852

Rizzi Romeo

symbol email romeo.rizzi@univr.it symbol phone-number +39 045 8027088

Setti Francesco

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

Toniolo Sara

symbol email sara.toniolo@univr.it symbol phone-number 045 802 8683

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. 2023/2024

ModulesCreditsTAFSSD
activated in the A.Y. 2023/2024
ModulesCreditsTAFSSD
Modules Credits TAF SSD
Between the years: 1°- 2°1 module among the following (a.a. 2023/24: Data protection in business organizations not activated)
6
C
IUS/17
Between the years: 1°- 2°2 modules among the following (a.a. 2023/24: Statistical methods for business intelligence not activated)
Between the years: 1°- 2°2 modules among the following (a.a. 2023/24: Complex systems and social physics not activated)
Between the years: 1°- 2°2 modules among the following
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

4S009066

Credits

6

Language

English en

Scientific Disciplinary Sector (SSD)

INF/01 - INFORMATICS

Period

Semester 2 dal Mar 6, 2023 al Jun 16, 2023.

Learning objectives

The course aims to provide students with an introduction to the main security and privacy issues related to the collection, storage and processing of Big Data and the technical and organizational solutions that can be adopted to protect such data. The course also aims to give an overview of the ethical, legal and social aspects related to the processing of Big Data. At the end of the course the student has to show to have acquired the following skills:
- understanding of the main security and privacy attacks on Big Data
- knowledge of the techniques to make systems for collecting, storing and processing Big Data, resistant to such attacks and the limitations of these techniques
- knowledge of the ethical principles concerning the processing of Big Data
- knowledge of the principles for data protection imposed by existing legislation
- ability to identify the main attacks and compare different techniques for Big Data protection and choose among the most suitable ones according to the a-specific context.

Prerequisites and basic notions

none

Program

The syllabus of the course includes the following topics:
- Introduction to information security: definitions, security properties, cyber attacks related to collection, storage and processing of Big Data
- Authentication: digital certificates, public key infrastructures, single sign on, challenge-response protocols.
- Access Control: access control models, specification and enforcement of policies. Applications to systems
for the elaboration of Big Data
-Cryptographic techniques to protect data access: symmetric, e public key cryptography, multiparty computation, secret sharing schemes, oblivious transfer, homomorphic and functional encryption, private set intersection.
- Data provenance: models to represent data provenance, query languages and mechanisms to store and visualize provenance data and their application to Big Data
- Introduction to Privacy: definitions, Solove's Taxonomy, privacy attacks related to collection, storage and processing of Big Data
-Anonymization techniques: pseudoanonymity and hashing, k-anonymity, l-diversity, t-closeness and their attacks. Limitations of anonymization techniquest for Big Data.
- Privacy preserving data mining: clustering, classification, association rule/pattern mining, outliers.
- Differential Privacy: main concepts, Laplace mechanism, privacy budget, global sensitivity, group privacy.
- Privacy Ethics: behavioural economics of privacy, trust frameworks and transparency, fairness.
- Data Protection: principles of data protection, GDPR, compliance techniques.

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.

Didactic methods

Lectures, seminars, laboratory activities

Learning assessment procedures

Students will be assessed through a project /assigned to them in agreement with the teachers on the topics of the course. The results of the project will then be presented orally to the teachers who will be able to request and deepen the student's training on the various topics covered during the course.

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

Evaluation criteria

The project aims to verify the ability to deepen (researching material in a critical way) and autonomously rework the concepts presented during the course.

Criteria for the composition of the final grade

The teacher evaluates the presentation and discussion of the project and proposes a mark out of thirty

Exam language

inglese

Type D and Type F activities

Type D learning activities are the student's choice, type F activities are additional knowledge useful for job placement (internships, transversal skills, project works, etc.). According to the Teaching Regulations of the Course, some activities can be chosen and entered independently in the booklet, others must be approved by a special committee to verify their consistency with the study plan. Type D or F learning activities can be covered by the following activities.

1. Modules taught at the University of Verona

Include the modules listed below and/or in the Course Catalogue (which can also be filtered by language of delivery via Advanced Search).

Booklet entry mode: if the teaching is included among those listed below, the student can enter it independently during the period in which the curriculum is open; otherwise, the student must make a request to the Secretariat, sending the form to carriere.scienze@ateneo.univr.it during the period indicated.

2. CLA certificate or language equivalency

In addition to those required by the curriculum/study plan, the following are recognized for those matriculated from A.Y. 2021/2022:

  • English language: 3 CFUs are recognized for each level of proficiency above that required by the course of study (if not already recognized in the previous course of study).
  • Other languages and Italian for foreigners: 3 CFUs are recognized for each proficiency level starting from A2 (if not already recognized in the previous study cycle).

These CFUs will be recognized, up to a maximum of 6 CFUs in total, of type F if the study plan allows it, or of type D. Additional elective credits for language knowledge may be recognized only if consistent with the student's educational project and if adequately justified.

Those enrolled until A.Y. 2020/2021 should consult the information found here.

Method of inclusion in the booklet: request the certificate or equivalency from CLA and send it to the Student Secretariat - Careers for the inclusion of the exam in the career, by email: carriere.scienze@ateneo.univr.it

Warning: to students, who have achieved the B2 level of English in their three-year careers (bachelor), we emphasize the need to replace the full B2 level of English, provided by the study plan, with the C1 level of "computerized" English (prova informatizzata) or to acquire other language proficiency in a community language at least at the full B1 level.

3. Transversal skills

Discover the training paths promoted by the University's TALC - Teaching and learning center intended for students regularly enrolled in the academic year of course delivery

Mode of inclusion in the booklet: the teaching is not expected to be included in the curriculum. Only upon obtaining the Open Badge will the booklet CFUs be automatically validated. The registration of CFUs in career is not instantaneous, but there will be some technical time to wait.  

4. CONTAMINATION LAB 

The Contamination Lab Verona (CLab Verona) is an experiential course with modules on innovation and enterprise culture that offers the opportunity to work in teams with students from all areas to solve challenges set by companies and organisations.  

Upon completion of a CLab, students will be entitled to receive 6 CFU (D- or F-type credits).  

Find out more:  https://www.univr.it/clabverona 

PLEASE NOTE: In order to be admitted to any teaching activities, including those of your choice, you must be enrolled in the academic year in which the activities in question are offered. Students who are about to graduate in the December and April sessions are therefore advised NOT to undertake extracurricular activities in the new academic year in which they are not enrolled, as these graduation sessions are valid for students enrolled in the previous academic year. Therefore, students who undertake an activity in an academic year in which they are not enrolled will not be granted CFU credits.

5. Internship/internship period

In addition to the CFUs stipulated in the curriculum/study plan (check carefully what is indicated on the Teaching Regulations): here information on how to activate the internship. 

Check in the regulations which activities can be Type D and which can be Type F.

Modules and other activities that can be entered independently in the booklet

Academic year:
List of courses with unassigned period
years Modules TAF Teacher
1° 2° Mathematics mini courses Paolo Dai Pra (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 soon 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 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

Attendance

As stated in the Teaching Regulations for the A.Y. 2022/2023, attendance at the course of study is not mandatory.
 


Career management


Student login and resources


Erasmus+ and other experiences abroad