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.
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.
The Academic Calendar sets out the degree programme lecture and exam timetables, as well as the relevant university closure dates..
Definition of lesson periods
Oct 3, 2022
Jan 27, 2023
Mar 6, 2023
Jun 16, 2023
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.
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.
SPlacements in companies, public or private institutions and professional associations
Networked embedded & IoT systems (2023/2024)
Scientific Disciplinary Sector (SSD)
ING-INF/05 - SISTEMI DI ELABORAZIONE DELLE INFORMAZIONI
The course aims to provide the knowledge necessary for the specification, modeling, development and verification of embedded network systems for industrial applications, in particular networked control systems, cyber-physical components, network infrastructures and Internet-of-Things (IoT) applications. At the end of the course the student will have to show the acquisition of the ability to analyze and understand the functioning of the networked embedded and IoT systems and the problems related to their design, implementation, verification, certification and use, with reference to their most important properties: performance, reliability, security and privacy. This knowledge will allow the student to acquire the ability to specify, model, design and verify networked embedded systems in the industrial and IoT fields, identifying the most appropriate components to integrate with each other, with the production machinery and the company information system. At the end of the course the student will be able to apply and deepen these topics independently.
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.
The educational activities of type D are chosen by the student, those of type F are further knowledge useful for entering the world of work (internships, soft skills, project works, etc.). According to the Didactic Regulations of the Course, some activities can be chosen and included autonomously in the booklet, others must be approved by a special committee to verify their consistency with the study plan. Type D or F educational activities can be covered by the following activities.
1. Teachings taught at the University of Verona.
Include the teachings listed below and/or in the Course Catalogue (which can also be filtered by language of delivery via Advanced Search).
Booklet entry mode: if the teaching is included among those listed below, the student can include it autonomously during the period in which the study plan is open; otherwise, the student must submit a request to the Secretariat, sending the form to firstname.lastname@example.org during the period indicated.
2. CLA certificate or language equivalency.
In addition to those required by the curriculum, the following are recognized for those matriculated from A.Y. 2021/2022:
English language: 3 CFUs are recognized for each level of proficiency above the one required by the course of study (if not already recognized in the previous course of study).
Other languages and Italian for foreigners: 3 cfu are recognized for each proficiency level starting from A2 (if not already recognized in the previous study cycle).
These cfu will be recognized, up to a maximum of 6 cfu in total, as type F if the teaching plan allows, or as type D. Additional elective credits for language knowledge may be recognized only if consistent with the student's educational project and if adequately justified.
Those enrolled until A.Y. 2020/2021 should consult the information found here.
Booklet entry mode: request the certificate or equivalency to the CLA and send it to the Student Secretariat - Careers for career entry of the exam, via email: email@example.com
Booklet entry mode: the teaching is not expected to be included in the curriculum. Only after obtaining the Open Badge, the CFUs in the booklet will be automatically validated. The registration of CFUs in career is not instantaneous, but there will be some technical time to wait.
4. Stage/internship period
In addition to the CFUs required by the curriculum (check carefully what is indicated on the Didactic Regulations): here information on how to activate the internship.
Check in the regulations which activities can be Type D and which can be Type F.
Teachings and other activities that can be entered autonomously in the booklet
Modules not yet included
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.
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.
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)