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.
Type D and Type F activities
SOFT SKILLS
Find out more about the Soft Skills courses for Univr students provided by the University's Teaching and Learning Centre: https://talc.univr.it/it/competenze-trasversali
CONTAMINATION LAB
The Contamination Lab Verona (CLab Verona) is an experiential course with modules on innovation and enterprise culture that offers the opportunity to work in teams with students from all areas to solve challenges set by companies and organisations.
Upon completion of a CLab, students will be entitled to receive 6 CFU (D- or F-type credits).
Find out more: https://www.univr.it/clabverona
PLEASE NOTE: In order to be admitted to any teaching activities, including those of your choice, you must be enrolled in the academic year in which the activities in question are offered. Students who are about to graduate in the December and April sessions are therefore advised NOT to undertake extracurricular activities in the new academic year in which they are not enrolled, as these graduation sessions are valid for students enrolled in the previous academic year. Therefore, students who undertake an activity in an academic year in which they are not enrolled will not be granted CFU credits.
| years | Modules | TAF | Teacher |
|---|---|---|---|
| 1° 2° | Ciclo tematico di conferenze: “Conflitti. Riconoscere, prevenire, gestire” - 2022/2023 | D |
Riccardo Stacchezzini
(Coordinator)
|
| 1° 2° | Securitisation transactions - Focus on securitisations of OF NPL / NPE /UTP | D |
Michele De Mari
(Coordinator)
|
| 1° 2° | The Fashion Lab - 2022/23 | D |
Caterina Fratea
(Coordinator)
|
| years | Modules | TAF | Teacher |
|---|---|---|---|
| 1° 2° | Economic Thinking and Thesis Writing | D |
Marco Minozzo
(Coordinator)
|
| 1° 2° | Data Analysis Laboratory with R (Verona) | D |
Marco Minozzo
(Coordinator)
|
| 1° 2° | Data Visualization Laboratory | D |
Marco Minozzo
(Coordinator)
|
| 1° 2° | Python Laboratory | D |
Marco Minozzo
(Coordinator)
|
| 1° 2° | Data Science Laboratory with SAP | D |
Marco Minozzo
(Coordinator)
|
| 1° 2° | Advanced Excel Laboratory (Verona) | D |
Marco Minozzo
(Coordinator)
|
| 1° 2° | Excel Laboratory (Verona) | D |
Marco Minozzo
(Coordinator)
|
| 1° 2° | Laboratory on research methods for business | D |
Cristina Florio
(Coordinator)
|
| 1° 2° | Laboratory on research methods for business | D |
Cristina Florio
(Coordinator)
|
| 1° 2° | Piano di marketing 2022/23 | D |
Fabio Cassia
(Coordinator)
|
| 1° 2° | Programming in Mathlab | D |
Marco Minozzo
(Coordinator)
|
| 1° 2° | Programming in SAS | D |
Marco Minozzo
(Coordinator)
|
| years | Modules | TAF | Teacher |
|---|---|---|---|
| 1° 2° | Business & predictive analytics for International Firms (with Excel Applications) - 2022/23 | D |
Angelo Zago
(Coordinator)
|
| 1° 2° | Elements of Financial Risk Management - 2022/23 | D |
Claudio Zoli
(Coordinator)
|
| 1° 2° | English for business and economics | F |
Claudio Zoli
(Coordinator)
|
| 1° 2° | Introduction to Business Plan - 2022/23 | D |
Paolo Roffia
(Coordinator)
|
| 1° 2° | Soft skills training for economics - 2022/23 | D |
Claudio Zoli
(Coordinator)
|
| 1° 2° | Topics in applied economics and finance - 2022/23 | D |
Claudio Zoli
(Coordinator)
|
| 1° 2° | Experience 3 Days as a Manager | D |
Riccardo Stacchezzini
(Coordinator)
|
| years | Modules | TAF | Teacher |
|---|---|---|---|
| 1° 2° | Data Discovery for Business Decisions 2022/2023 | D |
Claudio Zoli
(Coordinator)
|
| 1° 2° | The Chartered Accountant as a business consultant | D |
Riccardo Stacchezzini
(Coordinator)
|
| 1° 2° | Integrated Financial Planning 2022/2023 | D |
Riccardo Stacchezzini
(Coordinator)
|
| 1° 2° | Predictive Analytics for Business Decisions 2022/2023 | D |
Claudio Zoli
(Coordinator)
|
| 1° 2° | Professional Communication for Economics 2022/2023 | D |
Claudio Zoli
(Coordinator)
|
| years | Modules | TAF | Teacher |
|---|---|---|---|
| 1° 2° | Project "B-EDUCATION: ideas that count" - 1 cfu | D |
Roberto Bottiglia
(Coordinator)
|
| 1° 2° | Project "B-EDUCATION: ideas that count" - 2 cfu | D |
Roberto Bottiglia
(Coordinator)
|
Quantitative methods for business and economics (2022/2023)
The teaching is organized as follows:
MATHEMATICAL AND COMPUTATIONAL METHODS FOR BUSINESS AND ECONOMICS
Credits
6
Period
Primo semestre (lauree magistrali)
Academic staff
Learning objectives
The course aims at providing students the capabilities for addressing, in a quantitative framework, the main issues that arise in the economic and business context. The course is organized in two modules, specifically targeting mathematical and computational tools and data management and analysis.
In the first part, the module on mathematical and computational methods presents fundamental notions on unconstrained/constrained optimization and ordinary differential equations. In the second part of the module, computational programs are used to solve optimization problems and differential equations. The module on data management deals with the tools that can be used for handling and analysing data for business and economics. Specific software will be used to summarize the main information embedded in a sample of interest and to highlight the characteristics of the economic variables under analysis both through indices and graphical representations.
At the end of the course students should be able to provide a mathematical formulation for problems related to economics and management with the aim of identifying, given the prescribed objectives, their best solution. Students will develop the capability of solving the mathematical problems presented during the course using both analytical and computational techniques. The students will also acquire autonomy in the management of databases in order to extract information that can inform the decision process in business and policy areas.
Prerequisites and basic notions
The prerequisites are the basic notions of Mathematics acquired in a bachelor’s degree in Economics; in particular, elements of analytical geometry, plot of functions of a single variable, derivatives, integrals by parts and by substitution, determinant and rank of a matrix.
Bibliography
Criteria for the composition of the final grade
The final exam is a written test. The valuation obtained in the homework related to the laboratory activity contributes to the final grade.
In particular, the homework is worth 50% of the grade of Module I (Data Management for Business and Economics), and 40% of the grade of Module II (Mathematical and Computational Methods for Business and Economics). The final grade of the exam is given by the mean of the marks obtained in the two modules.
