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.

Academic calendar

Course calendar

The Academic Calendar sets out the degree programme lecture and exam timetables, as well as the relevant university closure dates..

Definition of lesson periods
Period From To
Primo semestre Oct 3, 2022 Jan 27, 2023
Secondo semestre Mar 6, 2023 Jun 16, 2023

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.

Exam calendar

Should you have any doubts or questions, please check the Enrolment FAQs

Academic staff

A B C D G M O P Q R S T V Z

Albi Giacomo

giacomo.albi@univr.it +39 045 802 7913

Badino Massimiliano

massimiliano.badino@univr.it +39 045 802 8459

Bazzani Claudia

claudia.bazzani@univr.it 0458028734

Begalli Diego

diego.begalli@univr.it +39 045 8028491

Blasi Silvia

silvia.blasi@univr.it 045 8028218

Boscolo Galazzo Ilaria

ilaria.boscologalazzo@univr.it +39 045 8127804

Carra Damiano

damiano.carra@univr.it +39 045 802 7059

Carradore Marco

marco.carradore@univr.it

Castellini Alberto

alberto.castellini@univr.it +39 045 802 7908

Ceccato Mariano

mariano.ceccato@univr.it

Chiarini Andrea

andrea.chiarini@univr.it 045 802 8223

Collet Francesca

francesca.collet@univr.it

Confente Ilenia

ilenia.confente@univr.it 045 802 8174

Dai Pra Paolo

paolo.daipra@univr.it +39 0458027093

Dalla Preda Mila

mila.dallapreda@univr.it

D'Asaro Fabio Aurelio

fabioaurelio.dasaro@univr.it 0458028431

Di Persio Luca

luca.dipersio@univr.it +39 045 802 7968

Gaudenzi Barbara

barbara.gaudenzi@univr.it 045 802 8623

Giachetti Andrea

andrea.giachetti@univr.it +39 045 8027998

Guerra Giorgia

giorgia.guerra@univr.it

Marastoni Niccolo'

niccolo.marastoni@univr.it

Mola Lapo

lapo.mola@univr.it 045/8028565

Owusu Abigail

abigail.owusu@univr.it

Paci Federica Maria Francesca

federicamariafrancesca.paci@univr.it +39 045 802 7909

Pelgreffi Igor

igor.pelgreffi@univr.it

Pianezzi Daniela

daniela.pianezzi@univr.it

Quintarelli Elisa

elisa.quintarelli@univr.it +39 045 802 7852

Rizzi Romeo

romeo.rizzi@univr.it +39 045 8027088

Setti Francesco

francesco.setti@univr.it +39 045 802 7804

Toniolo Sara

sara.toniolo@univr.it 045 802 8683

Vadala' Rosa Maria

rosamaria.vadala@univr.it

Zardini Alessandro

alessandro.zardini@univr.it 045 802 8565

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.

ModulesCreditsTAFSSD

1° Year

ModulesCreditsTAFSSD

2° Year

ModulesCreditsTAFSSD
Modules Credits TAF SSD
Between the years: 1°- 2°1 module among the following
6
C
IUS/17
Between the years: 1°- 2°2 modules among the following
Between the years: 1°- 2°

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.




S Placements in companies, public or private institutions and professional associations

Teaching code

4S009072

Coordinatore

Barbara Gaudenzi

Credits

6

Language

English en

Scientific Disciplinary Sector (SSD)

SECS-P/08 - MANAGEMENT

Period

Primo semestre dal Oct 3, 2022 al Jan 27, 2023.

Learning objectives

The course provides a consistent knowledge of the activities and processes of logistics concerning the following operations: supply management, inventory and warehouse management, production planning and demand planning, distribution and service to the customer. The course also aims to deepen the tools that allow to achieve customer satisfaction, from a business to business and business to consumer perspective, integrating the activities of planning, implementation and control of logistics with the efficient and effective management of customer service . At the end of the course the student has to show to have acquired the following skills:
- knowledge of the main characteristics of the following topics: Logistics management, warehousing and inventory management; global customer service and LSA (Logistics and Service Agreements); demand planning; supply chain strategy (lean-agile); transportation management; e-commerce, distribution management and retail
- ability to understand and develop outsourcing and process optimization solutions.
- ability to develop solutions aimed at customer satisfaction (BtB and BtC)
- ability to integrate planning and organization activities in the logistics sector

Prerequisites and basic notions

The course has no prerequisites. It aims to allow the student to acquire adequate knowledge of the activities and processes inherent to logistics related to operations: procurement management, inventory and warehouse management, production planning and demand planning, distribution and customer service. . The course also aims to deepen the tools that allow you to achieve customer satisfaction, from a business to business and business to consumer perspective, integrating the planning, implementation and control of logistics with the efficient and effective management of customer service.

Program

The course will describe the main data science’s approaches and tools on the key themes of logistics management, operations management and supply chain management, in particular:

Logistics management
Supply chain management and network design
Warehousing and inventory management
Demand planning and management
Production strategy
Transportation management and optimization
Distribution management and retail management
Outsourcing and process optimization
Global customer service and LSA (Logistics and Service Agreements);
Service and E-commerce

An assignment is finally proposed to students as additional work during the course, that will offer extra points for the exam.

Bibliography

Visualizza la bibliografia con Leganto, strumento che il Sistema Bibliotecario mette a disposizione per recuperare i testi in programma d'esame in modo semplice e innovativo.

Didactic methods

The Course is structured in lessons (using slides), working groups and case studies. A lecturer, prof. Trilce Encarnation, from the UMSL (USA) will participate in the course. She will offer her lessons in streaming, that can be attended either from home or in-class. Managers from companies will provide their practical insights on the key themes of the course.

Learning assessment procedures

The final exam is written and includes theoretical open questions and multiple-choice questions.
The student will study on the slides and materials provided by the professors. The reference book is: Christopher Martin, "Logistics and Supply Chain Management", 5th ed., Pearson.

Evaluation criteria

The assessment is based on the verification of: 1) the knowledge of the theoretical topics addressed during the lessons and of the texts under study; 2) the ability to apply theoretical concepts to the practical cases studied.

Criteria for the composition of the final grade

The final grade is based on the sum of the final exam grade and the evaluation of an (opitional) project work, which will be assigned during the course.
The project work consists of the development of a business case and adds a maximum of 3 points to the final grade.

Exam language

inglese

Type D and Type F activities

Le attività formative di tipologia D sono a scelta dello studente, quelle di tipologia F sono ulteriori conoscenze utili all’inserimento nel mondo del lavoro (tirocini, competenze trasversali, project works, ecc.). In base al Regolamento Didattico del Corso, alcune attività possono essere scelte e inserite autonomamente a libretto, altre devono essere approvate da apposita commissione per verificarne la coerenza con il piano di studio. Le attività formative di tipologia D o F possono essere ricoperte dalle seguenti attività.

1. Insegnamenti impartiti presso l'Università di Verona

Comprendono gli insegnamenti sotto riportati e/o nel Catalogo degli insegnamenti (che può essere filtrato anche per lingua di erogazione tramite la Ricerca avanzata).

Modalità di inserimento a libretto: se l'insegnamento è compreso tra quelli sottoelencati, lo studente può inserirlo autonomamente durante il periodo in cui il piano di studi è aperto; in caso contrario, lo studente deve fare richiesta alla Segreteria, inviando a carriere.scienze@ateneo.univr.it il modulo nel periodo indicato.

2. Attestato o equipollenza linguistica CLA

Oltre a quelle richieste dal piano di studi, per gli immatricolati dall'A.A. 2021/2022 vengono riconosciute:

  • Lingua inglese: vengono riconosciuti 3 CFU per ogni livello di competenza superiore a quello richiesto dal corso di studio (se non già riconosciuto nel ciclo di studi precedente).
  • Altre lingue e italiano per stranieri: vengono riconosciuti 3 CFU per ogni livello di competenza a partire da A2 (se non già riconosciuto nel ciclo di studi precedente).

Tali cfu saranno riconosciuti, fino ad un massimo di 6 cfu complessivi, di tipologia F se il piano didattico lo consente, oppure di tipologia D. Ulteriori crediti a scelta per conoscenze linguistiche potranno essere riconosciuti solo se coerenti con il progetto formativo dello studente e se adeguatamente motivati.

Gli immatricolati fino all'A.A. 2020/2021 devono consultare le informazioni che si trovano qui.

Modalità di inserimento a librettorichiedere l’attestato o l'equipollenza al CLA e inviarlo alla Segreteria Studenti - Carriere per l’inserimento dell’esame in carriera, tramite mail: carriere.scienze@ateneo.univr.it

3. Competenze trasversali

Scopri i percorsi formativi promossi dal TALC - Teaching and learning center dell'Ateneo, destinati agli studenti regolarmente iscritti all'anno accademico di erogazione del corso https://talc.univr.it/it/competenze-trasversali

Modalità di inserimento a libretto: non è previsto l'inserimento dell'insegnamento nel piano di studi. Solo in seguito all'ottenimento dell'Open Badge verranno automaticamente convalidati i CFU a libretto. La registrazione dei CFU in carriera non è istantanea, ma ci saranno da attendere dei tempi tecnici.  

4. Periodo di stage/tirocinio

Oltre ai CFU previsti dal piano di studi (verificare attentamente quanto indicato sul Regolamento Didattico): qui informazioni su come attivare lo stage. 

Verificare nel regolamento quali attività possono essere di tipologia D e quali di tipologia F.

Insegnamenti e altre attività che si possono inserire autonomamente a libretto

 

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

For schedules, administrative requirements and notices on graduation sessions, please refer to the Graduation Sessions - Science and Engineering service.

Attachments

Title Info File
Doc_Univr_pdf Regolamento esame finale | Final exam regulation 387 KB, 27/04/22 

List of theses and work experience proposals

theses proposals Research area
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)
Domain Adaptation Computing Methodologies - IMAGE PROCESSING AND COMPUTER VISION
Domain Adaptation Computing methodologies - Machine learning

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.

Career management


Area riservata studenti