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 sem. | Oct 3, 2016 | Jan 31, 2017 |
II sem. | Mar 1, 2017 | Jun 9, 2017 |
Session | From | To |
---|---|---|
Sessione invernale Appelli d'esame | Feb 1, 2017 | Feb 28, 2017 |
Sessione estiva Appelli d'esame | Jun 12, 2017 | Jul 31, 2017 |
Sessione autunnale Appelli d'esame | Sep 1, 2017 | Sep 29, 2017 |
Session | From | To |
---|---|---|
Sessione estiva Appelli di Laurea | Jul 18, 2017 | Jul 18, 2017 |
Sessione autunnale Appelli di laurea | Nov 22, 2017 | Nov 22, 2017 |
Sessione invernale Appelli di laurea | Mar 20, 2018 | Mar 20, 2018 |
Period | From | To |
---|---|---|
Festa di Ognissanti | Nov 1, 2016 | Nov 1, 2016 |
Festa dell'Immacolata Concezione | Dec 8, 2016 | Dec 8, 2016 |
Vacanze di Natale | Dec 23, 2016 | Jan 8, 2017 |
Vacanze di Pasqua | Apr 14, 2017 | Apr 18, 2017 |
Anniversario della Liberazione | Apr 25, 2017 | Apr 25, 2017 |
Festa del Lavoro | May 1, 2017 | May 1, 2017 |
Festa della Repubblica | Jun 2, 2017 | Jun 2, 2017 |
Vacanze estive | Aug 8, 2017 | Aug 20, 2017 |
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
Ugolini Simone
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 |
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2° Year activated in the A.Y. 2017/2018
Modules | Credits | TAF | SSD |
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One course to be chosen among the following
3° Year activated in the A.Y. 2018/2019
Modules | Credits | TAF | SSD |
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Modules | Credits | TAF | SSD |
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Modules | Credits | TAF | SSD |
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One course to be chosen among the following
Modules | Credits | TAF | SSD |
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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.
Linear Algebra (2016/2017)
Teaching code
4S00002
Teacher
Coordinator
Credits
6
Language
Italian
Scientific Disciplinary Sector (SSD)
MAT/02 - ALGEBRA
Period
II sem. dal Mar 1, 2017 al Jun 9, 2017.
Learning outcomes
The course aims to introduce the basic techniques of linear algebra, which is a fundamental tool in most applications of mathematics: matrices, Gauss elimination, vector spaces, inner products, determinants, eigenvalues and eigenvectors.
At the end of the course, the students will be able to apply linear algebra techniques to the solution of problems about matrix decompositions, analysis of linear maps, orthogonalization and computation of eigenvalues and eigenvectors.
Knowledge and understanding: students will be able to apply linear algebra techniques to solution of problems.
Applying knowledge and understanding: students will be able to recognize applicability of linear algebra to various situations.
Making judgements: the students will be able to choose among the various techniques the one better suited to the problem at hand.
Communication skills: the students will be able to describe the solution of a problem employing correct terminology.
Learning skills: the students will be able to widen their knowledge starting from what they learned.
Program
Linear systems and matrices
Inverse matrices
Gauss elimination and LU decomposition
Vector spaces and linear maps
Bases and matrix representation of linear maps
Inner products and Gram-Schmidt algorithm
Determinants
Eigenvalues and eigenvectors, diagonalization of matrices
Author | Title | Publishing house | Year | ISBN | Notes |
---|---|---|---|---|---|
E. Gregorio, L. Salce | Algebra Lineare | Libreria Progetto Padova | 2005 |
Examination Methods
The written exam consists in discussing a topic from a theoretical point of view and in solving some exercises on the topics of the course.
The complete solution of the exercises leads to a grade not higher than 21/30.
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 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 |
Tutoring faculty members
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.