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 |
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I semestre | Oct 1, 2024 | Jan 31, 2025 |
II semestre | Mar 3, 2025 | Jun 13, 2025 |
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 Enrollment 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 enrollment year.
1° Year
Modules | Credits | TAF | SSD |
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Algebra lineare e analisi
2° Year It will be activated in the A.Y. 2025/2026
Modules | Credits | TAF | SSD |
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3° Year It will be activated in the A.Y. 2026/2027
Modules | Credits | TAF | SSD |
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Modules | Credits | TAF | SSD |
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Algebra lineare e analisi
Modules | Credits | TAF | SSD |
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Modules | Credits | TAF | SSD |
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Modules | Credits | TAF | SSD |
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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.
Tecniche avanzate di apprendimento automatico per dati biomedici (It will be activated in the A.Y. 2025/2026)
Teaching code
4S012348
Credits
6
Scientific Disciplinary Sector (SSD)
INF/01 - INFORMATICA
Learning objectives
The course intends to provide the main theoretical and application concepts of some advanced machine learning techniques for the analysis and management of biological data, with particular emphasis on biomedical image. The problems and techniques related to the development of unsupervised Pattern Recognition systems will be presented and discussed, such as clustering, anomaly detection and similar. The main problems related to the processing and analysis of clinical studies based on diagnostic imaging will also be addressed, as well as the fundamental algorithms for resolving such situations such as image segmentation, registration and compression. After the course, students will be able to analyze a large class of unsupervised biological problems, using the Pattern Recognition point of view, and will have the necessary knowledge to design, develop and manage the different components of a pattern recognition system in real-world biomedical data contexts. They will also be able to use the image processing algorithms seen in class to solve typical problems that arise in clinical studies based on diagnostic imaging, by applying state-of-the-art methodologies and software.
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: only in this way will you be able to receive notification of all the notices from your teachers and your secretariat via email and soon also via the Univr app.
Tutoring faculty members
Graduation
Attendance
As stated in the Teaching Regulations for the A.Y. 2022/2023, attendance at the course of study is not mandatory.