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, 2018 | Jan 31, 2019 |
| II semestre | Mar 4, 2019 | Jun 14, 2019 |
| Session | From | To |
|---|---|---|
| Sessione invernale d'esame | Feb 1, 2019 | Feb 28, 2019 |
| Sessione estiva d'esame | Jun 17, 2019 | Jul 31, 2019 |
| Sessione autunnale d'esame | Sep 2, 2019 | Sep 30, 2019 |
| Session | From | To |
|---|---|---|
| Sessione di laurea estiva | Jul 22, 2019 | Jul 22, 2019 |
| Sessione di laurea autunnale | Oct 15, 2019 | Oct 15, 2019 |
| Sessione di laurea invernale | Mar 19, 2020 | Mar 19, 2020 |
| Period | From | To |
|---|---|---|
| Sospensione attività didattica | Nov 2, 2018 | Nov 3, 2018 |
| Vacanze di Natale | Dec 24, 2018 | Jan 6, 2019 |
| Vacanze di Pasqua | Apr 19, 2019 | Apr 28, 2019 |
| Vacanze estive | Aug 5, 2019 | Aug 18, 2019 |
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
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 |
|---|
1° Year
| 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.
Statistical methods for data analysis (2018/2019)
Teaching code
4S007624
Credits
6
Coordinatore
Scientific Disciplinary Sector (SSD)
MAT/08 - NUMERICAL ANALYSIS
Language
English
The teaching is organized as follows:
Machine learning
Statistical modelling
Learning outcomes
The objective is to introduce students to statistical modelling and exploratory
data analysis. The mathematical foundations of Statistical Learning (supervised
and unsupervised learning, deep learning) are developed with emphasis on the
underlying abstract mathematical framework, aiming to provide a rigorous,
self-contained derivation and theoretical analysis of the main models currently
used in applications. Complimentary laboratory sessions will illustrate the use
of both the key algorithms and relevant case studies, mainly by using standard
software environments such as R or Python.
Program
- Introduction to data analysis with R and Python
- Linear methods for regression (linear regression, least squares, MLE: Estimation, Prediction, Tests under Gaussian assumptions, variable/subset selection
- Shrinkage/Regularization methods (Ridge regression, Least absolute shrinkage and selection operator, [Elastic net, Least angle regression])
- Linear methods for classification (Logistic regression, MLE: estimation, prediction, variable selection)
- Linear model assessment and selection (cross-validation, bootstrap methods)
- Clustering analysis (k-means, principal component analysis and spectral clustering)
Examination Methods
The purpose of the exam is to evaluate the capabilities of the student to understand and use the methodologies presented in the course. The exam consists of a project assignment about specific case studies. Alternatively, the student may choose to give a public presentation about advanced methodologies from the literature related to the topics of the course.
Bibliografia
| Activity | Author | Title | Publishing house | Year | ISBN | Notes |
|---|---|---|---|---|---|---|
| Machine learning | T. Hastie, R. Tibshirani, J. Friedman. | The elements of statistical learning. Data mining, inference, and prediction. (Edizione 2) | Springer | 2009 |
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.
Attendance
As stated in point 25 of the Teaching Regulations for the A.Y. 2021/2022, except for specific practical or lab activities, attendance is not mandatory. Regarding these activities, please see the web page of each module for information on the number of hours that must be attended on-site.Please refer to the Crisis Unit's latest updates for the mode of teaching.
Graduation
Attachments
| Title | Info File |
|---|---|
1. Come scrivere una tesi
|
31 KB, 29/07/21 |
|
2. How to write a thesis
|
31 KB, 29/07/21 |
|
4. Regolamento tesi (valido da luglio 2020)
|
259 KB, 29/07/21 |
|
5. Regolamento tesi (valido da luglio 2022)
|
256 KB, 29/07/21 |
List of theses and work experience proposals
| theses proposals | Research area |
|---|---|
| Controllo di sistemi multiagente | Calculus of variations and optimal control; optimization - Hamilton-Jacobi theories, including dynamic programming |
| Controllo di sistemi multiagente | Calculus of variations and optimal control; optimization - Manifolds |
| Controllo di sistemi multiagente | Calculus of variations and optimal control; optimization - Optimality conditions |
| Formule di rappresentazione per gradienti generalizzati | Mathematics - Analysis |
| Formule di rappresentazione per gradienti generalizzati | Mathematics - Mathematics |
| Mathematics Bachelor and Master thesis titles | Various topics |
| Stage | Research area |
|---|---|
| Internship proposals for students in mathematics | Various topics |
Gestione carriere
Double degree
The University of Verona, through a network of agreements with foreign universities, offers international courses that enable students to gain a Double/Joint degree at the time of graduation. Indeed, students enrolled in a Double/Joint degree programme will be able to obtain both the degree of the University of Verona and the degree issued by the Partner University abroad - where they are expected to attend part of the programme -, in the time it normally takes to gain a common Master’s degree. The institutions concerned shall ensure that both degrees are recognised in the two countries.
Places on these programmes are limited, and admissions and any applicable grants are subject to applicants being selected in a specific Call for applications.
The latest Call for applications for Double/Joint Degrees at the University of Verona is available now!
Alternative learning activities
In order to make the study path more flexible, it is possible to request the substitution of some modules with others of the same course of study in Mathematics at the University of Verona (if the educational objectives of the modules to be substituted have already been achieved in the previous career), or with others of the course of study in Mathematics at the University of Trento.Attachments
| Title | Info File |
|---|---|
|
1. Convenzione | Learning Agreement UNITN - UNIVR
|
167 KB, 27/08/21 |
|
2. Sostituzione insegnamenti a UNITN - Courses replacement at UNITN
|
44 KB, 30/08/21 |
|
3. Sostituzione insegnamenti a UNIVR - Courses replacement at UNIVR
|
113 KB, 30/08/21 |
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.