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 |
|---|---|---|
| Semester 1 | Oct 3, 2022 | Jan 27, 2023 |
| Semester 2 | Mar 6, 2023 | Jun 16, 2023 |
| 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 |
| 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 |
| 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.
Should you have any doubts or questions, please check the Enrolment FAQs
Academic staff
+39 045 802 7913
damiano.bazzoni@univr.it
marco.carradore@univr.it
mariano.ceccato@univr.it
mila.dallapreda@univr.it
stefano.gatti@univr.it
giorgia.guerra@univr.it
niccolo.marastoni@univr.it
abigail.owusu@univr.it
igor.pelgreffi@univr.it
daniela.pianezzi@univr.it
rosamaria.vadala@univr.it
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.
| Modules | Credits | TAF | SSD |
|---|
| Modules | Credits | TAF | SSD |
|---|
1° Year
| Modules | Credits | TAF | SSD |
|---|
2° Year activated in the A.Y. 2023/2024
| Modules | Credits | TAF | SSD |
|---|
| Modules | Credits | TAF | SSD |
|---|
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.
Ricerca sociale (2022/2023)
Teaching code
4S009087
Teacher
Credits
6
Language
English
Scientific Disciplinary Sector (SSD)
SPS/07 - GENERAL SOCIOLOGY
Period
Semester 2 dal Mar 6, 2023 al Jun 16, 2023.
Learning objectives
The course aims to offer students an overview of the main paradigms of social research, in order to identify the solutions proposed by these paradigms for ontological, epistemological and methodological questions related to social research. The course is also aimed at providing students with a general framework of the main quantitative and qualitative research techniques, linking them to the specific research questions for which their application is particularly relevant. Finally, the course aims to provide a presentation of the Social Network Analysis (SNA) techniques, in order to train students to the relational analysis of social reality. At the end of the course the student has to show to have acquired the following skills: -ability to identify the most effective social research strategy to deal with a cognitive problem -ability to use, with competence and appropriate language, the techniques of Social Network Analysis (SNA), finalizing them to the operational definition of social reality as a network of relationships and to the identification of the mechanisms that take place in it.
Prerequisites and basic notions
There are no prerequisites
Program
The course will provide students with the ability to learn and apply the qualitative research method, quantitative research techniques and SNA in the field of social research.
The program is divided into the following modules:
Qualitative social research
Quantitative social research
SNA
Big data and social research
Each research method will be dealt with a theoretical and practical point of view. They will be applied to analyse specific empirical research questions.
To gain experience with the practical application of these techniques, students will practice using the software most commonly applied in social research.
The course will combine theoretical lectures, data analysis activities and practice in the interpretation of the outputs obtained.
Bibliography
Didactic methods
All lectures will be delivered face-to-face.
Learning assessment procedures
Written/Oral
Evaluation criteria
The final assessment mark will combine the following three elements:
1) Practical activities of data analysis and interpretation of the outputs (30%)
2) A written assignment dealing with data analysis (min. 2000 words) (30%)
3) Oral examination (40%)
Exam language
English
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.
Modules and other activities that can be entered independently in the booklet
| years | Modules | TAF | Teacher |
|---|---|---|---|
| 1° 2° | Mathematics mini courses |
Paolo Dai Pra
(Coordinatore)
|
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.
Attachments
| Title | Info File |
|---|---|
Regolamento esame finale | Final exam regulation
|
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 |
Erasmus+ and other experiences abroad
Attendance
As stated in the Teaching Regulations for the A.Y. 2022/2023, attendance at the course of study is not mandatory.
Please refer to the Crisis Unit's latest updates for the mode of teaching.
