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 technicaladministrative 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, 2019  Jan 31, 2020 
II semestre  Mar 2, 2020  Jun 12, 2020 
Session  From  To 

Sessione invernale d'esame  Feb 3, 2020  Feb 28, 2020 
Sessione estiva d'esame  Jun 15, 2020  Jul 31, 2020 
Sessione autunnale d'esame  Sep 1, 2020  Sep 30, 2020 
Session  From  To 

Sessione Estiva  Jul 15, 2020  Jul 15, 2020 
Sessione Autunnale  Oct 16, 2020  Oct 16, 2020 
Sessione Autunnale Dicembre  Dec 11, 2020  Dec 11, 2020 
Sessione Invernale  Mar 17, 2021  Mar 17, 2021 
Period  From  To 

Festa di Ognissanti  Nov 1, 2019  Nov 1, 2019 
Festa dell'Immacolata  Dec 8, 2019  Dec 8, 2019 
Vacanze di Natale  Dec 23, 2019  Jan 6, 2020 
Vacanze di Pasqua  Apr 10, 2020  Apr 14, 2020 
Festa della Liberazione  Apr 25, 2020  Apr 25, 2020 
Festa del lavoro  May 1, 2020  May 1, 2020 
Festa del Santo Patrono  May 21, 2020  May 21, 2020 
Festa della Repubblica  Jun 2, 2020  Jun 2, 2020 
Vacanze estive  Aug 10, 2020  Aug 23, 2020 
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
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 

Mathematical analysis 1
Computer Architecture
2° Year activated in the A.Y. 2020/2021
Modules  Credits  TAF  SSD 

3° Year activated in the A.Y. 2021/2022
Modules  Credits  TAF  SSD 

Modules  Credits  TAF  SSD 

Mathematical analysis 1
Computer Architecture
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.
Mathematical analysis 2 (2020/2021)
Teaching code
4S00031
Teacher
Coordinator
Credits
6
Language
Italian
Scientific Disciplinary Sector (SSD)
MAT/05  MATHEMATICAL ANALYSIS
Period
II semestre dal Mar 1, 2021 al Jun 11, 2021.
Learning outcomes
The aim of the course is to provide students with the fundamental notions of differential and integral calculus in many variables, generalizing and mastering the notions learned in the course “Mathematical Analysis I” and employing, if needed, the notions of the other courses attended during the first year of the Bachelor in Computer Science. At the end of the course the student must prove:  to know and to be able to understand the tools and the advanced notions of the mathematical analysis and to use such notions for the solution of problems;  to be able to use the notions learned in the course for the comprehension of the topics of further courses, not necessarily in the mathematical area, where the knowledge of mathematical analysis can be a prerequisite;  to be able to choose which mathematical tool or theoretical result can be useful for the solution of a problem;  to be able to appropriately use the language and the formalism of the mathematical analysis;  to be able to broaden the knowledge in Mathematics, Computer Science or in any scientific area using, when needed, the notions of the course.
Program
Cauchy problem for first order differential equations (ODE). Separable equations and the theorem of existence and local uniqueness.
Structure of the space of the solutions of a homogeneous linear ODE (first and second order). Solutions in the nonhomogeneous case. The variation of constants method in the case of an equation of order 2. Slope fields and graphical analysis of an ODE in very simple cases.
Differential calculus in several real variables: limits and continuity. Directional derivatives and the gradient of a scalar function. Differentiability and the differential, the theorem on the total differential. Higher order derivatives, the Hessian matrix and Schwarz's theorem. Taylor's formula with Lagrange and Peano remainders. Unconstrained optimization: necessary and sufficient conditions for having local extrema. Constrained optimization: Lagrange multipliers. Dini's theorem.
The Riemann integral over the cartesian product of real intervals: definition and techniques for the calculation. The Riemann integral on admissible domains. Change of variables and special coordinate systems: polar, cylindrical and spherical. Parametric curves. Line integrals of scalar functions. Parametric surfaces in space, area of a surface, surface integrals. Vector fields.
Author  Title  Publishing house  Year  ISBN  Notes 

M. Bramanti, C. D. Pagani, S. Salsa  Analisi Matematica 2  Zanichelli  2009  9788808122810 
Examination Methods
The final exam consists of a written test including a series of exercises to be solved related to the academic program (specific instructions will be communicated throughout the course).
The final exam could be substituted by two ongoing tests, the former scheduled in mid April and the latter coinciding with the first exam date in June. In this case, the exam grade will be given by the sum of the two partial assesments, with a maximum of 16 points each.
The exam aims to verify the candidate's ability to solve programrelated problems, their possession of adequate analytical skills, as well as the ability to synthetize and abstract, starting from requests formulated in natural or specific language.
Exams will be carried out remotely.
Type D and Type F activities
years  Modules  TAF  Teacher 

3°  The fashion lab (1 ECTS)  D 
Maria Caterina Baruffi
(Coordinator)

years  Modules  TAF  Teacher 

3°  Control theory  D 
Riccardo Muradore
(Coordinator)

3°  Biomedical Data and Signal Processing  D 
Silvia Francesca Storti
(Coordinator)

3°  Python programming language  D 
Maurizio Boscaini
(Coordinator)

years  Modules  TAF  Teacher 

3°  CyberPhysical Laboratory  D 
Andrea Calanca
(Coordinator)

3°  C++ Programming Language  D 
Federico Busato
(Coordinator)

3°  LaTeX Language  D 
Enrico Gregorio
(Coordinator)

3°  MatlabSimulink programming  D 
Bogdan Mihai Maris
(Coordinator)

years  Modules  TAF  Teacher 

3°  Corso Europrogettazione  D  Not yet assigned 
3°  The course provides an introduction to blockchain technology. It focuses on the technology behind Bitcoin, Ethereum, Tendermint and Hotmoka.  D 
Matteo Cristani

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
List of thesis proposals
theses proposals  Research area 

Analisi e percezione dei segnali biometrici per l'interazione con robot  AI, Robotics & Automatic Control  AI, Robotics & Automatic Control 
Integrazione del simulatore del robot Nao con Oculus Rift  AI, Robotics & Automatic Control  AI, Robotics & Automatic Control 
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) 
BS or MS theses in automated reasoning  Computing Methodologies  ARTIFICIAL INTELLIGENCE 
Domain Adaptation  Computing Methodologies  IMAGE PROCESSING AND COMPUTER VISION 
Domain Adaptation  Computing methodologies  Machine learning 
Dati geografici  Information Systems  INFORMATION SYSTEMS APPLICATIONS 
Analisi e percezione dei segnali biometrici per l'interazione con robot  Robotics  Robotics 
Integrazione del simulatore del robot Nao con Oculus Rift  Robotics  Robotics 
BS or MS theses in automated reasoning  Theory of computation  Logic 
BS or MS theses in automated reasoning  Theory of computation  Semantics and reasoning 
Proposte di tesi/collaborazione/stage in Intelligenza Artificiale Applicata  Various topics 
Proposte di Tesi/Stage/Progetto nell'ambito dell'analisi dei dati  Various topics 
Attendance modes and venues
As stated in the Teaching Regulations, attendance at the course of study is not mandatory.
Parttime enrolment is permitted. Find out more on the Parttime 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.