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 |
|---|---|---|
| primo semestre (lauree magistrali) | Oct 4, 2021 | Dec 17, 2021 |
| secondo semestre (lauree magistrali) | Feb 21, 2022 | May 13, 2022 |
| Session | From | To |
|---|---|---|
| sessione invernale | Jan 10, 2022 | Feb 18, 2022 |
| sessione estiva | May 23, 2022 | Jul 1, 2022 |
| sessione autunnale | Aug 22, 2022 | Sep 23, 2022 |
| Session | From | To |
|---|---|---|
| sessione autunnale (validità a.a. 2020/2021) | Dec 6, 2021 | Dec 10, 2021 |
| sessione invernale (validità a.a. 2020/2021) | Apr 6, 2022 | Apr 8, 2022 |
| sessione estiva (validità a.a. 2021/2022) | Sep 5, 2022 | Sep 6, 2022 |
Exam calendar
Exam dates and rounds are managed by the relevant Economics 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 |
|---|
| Modules | Credits | TAF | SSD |
|---|
1° Year
| Modules | Credits | TAF | SSD |
|---|
2° 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.
Machine Learning for Economics (2022/2023)
Teaching code
4S008979
Credits
6
Scientific Disciplinary Sector (SSD)
SECS-S/01 - STATISTICA
Learning outcomes
The goal of the course is to provide students with mathematical, statistical and computational tools for a rigorous understanding of machine learning. A central aspect is the critical discussion of how and to which extent machine learning methods are essential in large scale data analysis in order to develop a professional profile combining solid quantitative skills with an in-depth knowledge of economic and corporate dynamics to support strategic decisions based on data analysis. At the end of the course students will be able to master classical methods of machine learning, implement data analysis algorithms, choose the most suitable techniques, identify relevant structures underlying the data for prediction purposes, critically discuss the output generated by a machine learning technique.
Educational offer 2021/2022
The details (teacher, program, exam methods, etc.) will be published in the academic year of delivery of the course. To consult the course sheet of a previous academic year, select the teaching plan of an academic year of enrollment prior to yours.
Machine Learning for Economics (2021/2022)Type D and Type F activities
| years | Modules | TAF | Teacher |
|---|---|---|---|
| 1° 2° | The fashion lab (1 ECTS) | D |
Caterina Fratea
(Coordinatore)
|
| 1° 2° | The fashion lab (2 ECTS) | D |
Caterina Fratea
(Coordinatore)
|
| 1° 2° | The fashion lab (3 ECTS) | D |
Caterina Fratea
(Coordinatore)
|
| years | Modules | TAF | Teacher |
|---|---|---|---|
| 1° 2° | Marketing plan | D |
Virginia Vannucci
(Coordinatore)
|
| years | Modules | TAF | Teacher |
|---|---|---|---|
| 1° 2° | Data Analysis Laboratory with R (Verona) | D |
Marco Minozzo
(Coordinatore)
|
| 1° 2° | Data Visualization Laboratory | D |
Marco Minozzo
(Coordinatore)
|
| 1° 2° | Python Laboratory | D |
Marco Minozzo
(Coordinatore)
|
| 1° 2° | Data Science Laboratory with SAP | D |
Marco Minozzo
(Coordinatore)
|
| 1° 2° | Advanced Excel Laboratory (Verona) | D |
Marco Minozzo
(Coordinatore)
|
| 1° 2° | Excel Laboratory (Verona) | D |
Marco Minozzo
(Coordinatore)
|
| 1° 2° | Programming in Matlab | D |
Marco Minozzo
(Coordinatore)
|
| 1° 2° | Programming in SAS | D |
Marco Minozzo
(Coordinatore)
|
| 1° 2° | Samsung Innovation Camp | D |
Marco Minozzo
(Coordinatore)
|
| years | Modules | TAF | Teacher |
|---|---|---|---|
| 1° 2° | Business & Predictive Analytics for International Firms (with Excel Applications) - 2021/2022 | D |
Angelo Zago
(Coordinatore)
|
| 1° 2° | What paradigms beyond the pandemic? Individual vs. Society, Private vs. Public | D |
Federico Brunetti
(Coordinatore)
|
| 1° 2° | Data Discovery for Business Decisions- 2021/2022 | D |
Claudio Zoli
(Coordinatore)
|
| 1° 2° | Elements of Financial Risk Management - 2021/2022 | D |
Claudio Zoli
(Coordinatore)
|
| 1° 2° | English for business and economics | F |
Claudio Zoli
|
| 1° 2° | Integrated Financial Planning | D |
Riccardo Stacchezzini
(Coordinatore)
|
| 1° 2° | Introduction to Business Plan- 2021/2022 | D |
Paolo Roffia
(Coordinatore)
|
| years | Modules | TAF | Teacher |
|---|---|---|---|
| 1° 2° | The fashion lab (1 ECTS) | D |
Caterina Fratea
(Coordinatore)
|
| 1° 2° | The fashion lab (2 ECTS) | D |
Caterina Fratea
(Coordinatore)
|
| 1° 2° | The fashion lab (3 ECTS) | D |
Caterina Fratea
(Coordinatore)
|
| years | Modules | TAF | Teacher |
|---|---|---|---|
| 1° 2° | How to Enter in a Foreign Market. Theory and Applications - 2021/2022 | D |
Angelo Zago
(Coordinatore)
|
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.
Gestione carriere
Internships
Linguistic training CLA
Doppio Titolo
.Graduation
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.