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 |
|---|---|---|
| I semestre | Oct 1, 2024 | Jan 31, 2025 |
| II semestre | Mar 3, 2025 | Jun 13, 2025 |
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 Enrollment FAQs
Academic staff
+39 045 802 7913
mariano.ceccato@univr.it
mila.dallapreda@univr.it
stefano.gatti@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 enrollment year.
1° Year
| Modules | Credits | TAF | SSD |
|---|
2° Year It will be activated in the A.Y. 2025/2026
| Modules | Credits | TAF | SSD |
|---|
| Modules | Credits | TAF | SSD |
|---|
| Modules | Credits | TAF | SSD |
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| Modules | Credits | TAF | SSD |
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1 module among the following2 modules among the following1 module among the following (A.A. 2024/2025 Network science and econophysics not activated)1 module among the following2 modules among the followingLegend | 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.
Programming and database (2024/2025)
Teaching code
4S009064
Credits
12
Language
English
Scientific Disciplinary Sector (SSD)
INF/01 - INFORMATICS
Courses Single
Authorized
The teaching is organized as follows:
Programming
Credits
6
Period
I semestre
Academic staff
Not yet assigned
Database
Credits
6
Period
II semestre
Academic staff
Elisa Quintarelli
Learning objectives
The course is structured as follows [Programming Module] The purpose of the module is to provide skills and knowledge in programming in Python and R, giving the basic concepts of algorithm with particular reference to the use of the Python language (syntax, data structures, data import / export in Python, data visualization in Python) and its applications in data science [Database form] The course aims to provide the skills necessary for the design of data according to the requirements with reference to different application contexts and within the production process of software systems; for the management and effective and efficient use of data and for the study of a system for the management of relational databases in order to create, manage and query databases.
At the end of the course the student has to show to have acquired the following skills:
- ability to develop Python code to solve concrete examples
- ability to evaluate algorithms in terms of complexity in time and space
- knowledge of the syntax and semantics of the language used
- knowledge of the bases of: database management; architecture and functionality of a database management system; concepts of physical independence, logical independence, persistence, competition, reliability, query and updating of a database; advantages of a database management system compared to an operating system file system
- ability to conceptually design databases, e.g., conceptual models for data design; the Entity-Relationship (E-R) model; elements of the E-R model: entities, attributes, relationships, generalization hierarchies and cardinality constraints; the conceptual scheme of a database
- knowledge of the basics of the logical design of a database: data models for database management systems; the relational model; relationship definitions, integrity constraints and relationship scheme; the logical scheme of a database; rules for the translation of conceptual schemes into relationship schemes
- understanding of the mechanisms of interaction with a database: introduction to languages for the definition, modification and query of a database; relational algebra; optimization of algebra expressions; the SQL language; the selection construct (Select-From-Where), nested queries, sorting and grouping of data in SQL; the concept of sight.
Learning assessment procedures
Programming and Database
To pass the exam, students must:
- complete a Python project that illustrates the fundamentals of Data Science taught during the first semester
- pass an oral exam that will test knowledge of the above project and general programming skills
- [OPTIONAL] take a mid-course written exam.
- Pass a two-hour written test, possibly supplemented by an oral at the teacher's discretion, containing some open questions on theory, an exercise on the conceptual (E-R model or DFM scheme) and logical (relational model) design of a database, and some exercises on SQL queries on an assigned database.
Evaluation criteria
To pass the exam, students must demonstrate:
- have understood the concepts underlying the theory of relational databases and data warehouses and their design;
- be able to present your arguments in a precise and organic way;
- know how to apply the knowledge acquired to solve application problems presented in the form of questions and exercises.
The grade of the written work will be up to a maximum of 33 points (30 cum laude).
The final grade will be the average of the grades obtained in the Programming and Database parts.
Type D and Type F activities
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: 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 |
|---|---|
Regulations for the final exame
|
pdf, it, 326 KB, 19/03/24 |
Modalità di frequenza
Come riportato nel Regolamento Didattico, la frequenza al corso di studio non è obbligatoria.
