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 2, 2017 | Jan 31, 2018 |
| II sem. | Mar 1, 2018 | Jun 15, 2018 |
| Session | From | To |
|---|---|---|
| Sessione invernale d'esame | Feb 1, 2018 | Feb 28, 2018 |
| Sessione estiva d'esame | Jun 18, 2018 | Jul 31, 2018 |
| Sessione autunnale d'esame | Sep 3, 2018 | Sep 28, 2018 |
| Session | From | To |
|---|---|---|
| Sessione di laurea estiva | Jul 18, 2018 | Jul 18, 2018 |
| Sessione di laurea autunnale | Nov 22, 2018 | Nov 22, 2018 |
| Sessione di laurea invernale | Mar 20, 2019 | Mar 20, 2019 |
| Period | From | To |
|---|---|---|
| Christmas break | Dec 22, 2017 | Jan 7, 2018 |
| Easter break | Mar 30, 2018 | Apr 3, 2018 |
| Patron Saint Day | May 21, 2018 | May 21, 2018 |
| Vacanze estive | Aug 6, 2018 | Aug 19, 2018 |
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
Bloisi Domenico Daniele
domenico.bloisi@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 |
|---|
Mathematical analysis 1
Computer Architecture
| Modules | Credits | TAF | SSD |
|---|
| Modules | Credits | TAF | SSD |
|---|
1° Year
| Modules | Credits | TAF | SSD |
|---|
Mathematical analysis 1
Computer Architecture
2° Year
| Modules | Credits | TAF | SSD |
|---|
3° Year
| 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.
Linear Algebra (2017/2018)
Teaching code
4S00002
Teacher
Coordinatore
Credits
6
Scientific Disciplinary Sector (SSD)
MAT/02 - ALGEBRA
Language
Italian
Period
II sem. dal Mar 1, 2018 al Jun 15, 2018.
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 shall prove of being able to: apply linear algebra techniques to the solution of problems; to apply linear algebra techniques to solution of problems; to recognize applicability of linear algebra to various situations even in not strictly mathematical contexts; to choose among the various techniques the one better suited to the problem at hand; to describe the solution of a problem employing correct terminology; 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
Bibliografia
| 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.
Evaluation criteria:
• Knowledge and understanding: comprehension of the text of the problems and mastering of the theory behind them.
• Applying knowledge and understanding: ability to apply the general techniques to a specific problem
• Making judgements: ability to express the learned theoretical concepts in varied situations
• Communication skills: language clarity and appropriateness
• Learning skills: ability to structure a proof different from those presented during the course
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.
Graduation
List of theses and work experience 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 delle basi di dati/sistemi informativi | Various topics |
Gestione carriere
Area riservata studenti
Attendance
As stated in point 25 of the Teaching Regulations for the A.Y. 2021/2022, attendance at the course of study is not mandatory.Please refer to the Crisis Unit's latest updates for the mode of teaching.
Further services
I servizi e le attività di orientamento sono pensati per fornire alle future matricole gli strumenti e le informazioni che consentano loro di compiere una scelta consapevole del corso di studi universitario.