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

This information is intended exclusively for students already enrolled in this course.
If you are a new student interested in enrolling, you can find information about the course of study on the course page:

Laurea interateneo in Ingegneria dei sistemi medicali per la persona - Enrollment from 2025/2026

Students can choose the type D training activities among a catalogue of courses, while type F activities provide additional knowledge useful for entering the job market (internships, transferable skills, project works, etc.). According to the Degree Programme description and regulation, some activities can be chosen and added autonomously by the students to the academic record, whereas others must be approved by a committee to verify their coherence with the study plan. Type D or F training activities can be covered by the following activities: 

1. Courses offered at the University of Verona: 

This includes the course listed below and/or in the Course Catalogue (which can be filtered by language using advanced search) 

Procedure for adding courses to the academic record: Ig the course is among those listed below or in the Catalogue, the student can add it independently when the study plan is open for modifications; otherwise, the student must request approval from the Student Office by sending the form to carriere.scienze@ateneo.univr.it during the specified periods

Starting from students enrolled in the Academic Year 2022/2023, courses offered in the 2nd and 3rd years of the study plan can be autonomously added to the academic record.

There is no need to submit the request to add the following courses to the academic record to the “Commissione Pratiche Studenti”: Database and Web (BSc in Bioinformatics); General Biology (BSc in Bionformatics); Molecular Biology (BSc in Bioinformatics); Probaility and Statistics (BSc in Computer Science); Programming and Network Security (BSc in Computer Science). 

2. CLA Language Certification or Equivalence 

Beside to to those already required by the study plan, the following language certifications can be added as additional training activities for students enrolled in the academic years 2021/2022 and 2022/2023: 

English language: 3 CFU will be granted for each level of proficiency above the level required by the study program (if not already granted in the previous degree programme). 

Other languages and Italian for foreigners: 3 CFU will be granted for each level of proficiency starting from A2 (if not already granted in the previous degree programme). 

These CFU will be granted as type D activities and up to a 3 CFU in total. In case the language certification is dated prior to 27/10/2023 (date of the vote of the Teaching Board of Information Engineering) the maximum CFU to be granted can be extended to 6, as for previous regulation. Additional credits for language knowledge can only be granted if consistent with the student's educational project and adequately justified. 

For students enrolled in the academic year 2023/2024, credits for language certifications beyond those specified in the teaching plan will be recorded as extra type D CFU. 

Procedure for adding the relevant academic record: Request the certificate or equivalence certificate to the CLA and send it to the Student Administration Office via email (carriere.scienze@ateneo.univr.it) for the exam to be recorded. 

3. Transferable Skills 

Discover the training paths promoted by TALC – Teaching and Learning Center of the University, intended for students regularly enrolled in the Academic Year offering the modules https://talc.univr.it/en/competenze-trasversali  

Procedure for adding the relevant academic record: the modules will not be added to the study plan, but CFU will be granted after obtaining the Open Badge. The procedure may require a certain amount of time to reach a conclusion. 

4. Contamination Lab 

The Contamination Lab Verona (CLab Verona) is an experiential program with modules dedicated to innovation and corporate culture that offers the opportunity to work in teams with students from all degree programs to solve challenges posed by companies and organizations. The program allows receiving 6 type D or F CFU. Discover the challenges: https://www.univr.it/en/clabverona. 

NOTE: To be admitted to any educational activity, including electives, students must be enrolled in the specific Academic Year of the course being offered. Therefore, it is recommended that those who foresee to graduate December and April sessions do NOT undertake extracurricular activities for the new Academic Year in which they are not enrolled, as these graduation sessions are valid for the previous Academic Year. Therefore, modules carried out in an Academic Year when the students is not enrolled with the University of Verona, the relevant CFU will not be recorded. 

5. Internship/Stage and other activities 

The student must complete a 7 CFU internship and attend a 2 CFU module on “Medical Systems Seminars”. 

Annually, the Internship Committee (tirocini-ismp@ateneo.univr.it) proposes a list of internship projects from which students can choose in line with their study plan and interests. The list can be complemented, after the approval of the Internship Committee, with proposals made by students who independently look for internship opportunities within the departments of the universities involved in the Degree programme, or within external organizations/companies. The management of the internship process is detailed in the  Vademecum delle Attività di Tirocinio. Here is the relevant information page (with a link to Moodle) and here the general information on how to activate an internship. 

Please note that for internships starting from October 1, 2024 with external partners/company, extra hours can lead to extra type D CFU. 

Academic year:

Teaching code

4S013525

Coordinator

Marco Cristani

Credits

1

Also offered in courses:

Language

Italian

Scientific Disciplinary Sector (SSD)

NN - -

Period

Semester 2 dal Mar 3, 2025 al Jun 13, 2025.

Erasmus students

Not available

Courses Single

Not Authorized

Learning objectives

The course aims to provide the fundamental and practical knowledge to tackle a Machine Learning project, integrating software development skills with modern practices of model lifecycle management. At the end of the course, the student should demonstrate that he/she has acquired an in-depth understanding of the principles underlying Machine Learning Operations (MLOps), with particular attention to aspects related to automation, versioning, release and monitoring of predictive models. He/she should also be able to apply the acquired knowledge to effectively manage a complete workflow ranging from data preparation to the deployment and maintenance of models in production environments.

Prerequisites and basic notions

A basic knowledge of the Python language and basic knowledge of statistics for data analysis are required. The student should be able to write simple scripts, use libraries such as pandas and scikit-learn and be familiar with the concept of machine learning. Knowledge of the UNIX/Linux environment and basic shell commands is also useful. Familiarity with the concepts of code versioning and the use of Git is an advantage, but is not essential. No advanced programming or machine learning skills are required, although a minimum previous experience in these areas facilitates active participation in the course.

Program

Day 1 (2h): Introduction and key concepts - Introduction to Source Control (Git); - DevOps and MLOps; development cycles and differences;
Day 2 (2h): - Data Science basics; EDA; Data preparation; - Model selection and training; Hugging faces models; - Hyperparameter tuning; Grid search;
Day 3 (2h): - Docker: basics, training and deployment; - Logging and monitoring;
Day 4 (2h): - Python packaging; - AutoML;

Didactic methods

Frontal lectures and computer laboratory exercises.

Learning assessment procedures

Individual development of a project and delivery of the related documentation to the teachers

Students with disabilities or specific learning disorders (SLD), who intend to request the adaptation of the exam, must follow the instructions given HERE

Evaluation criteria

The evaluation will be based on the student's ability to effectively and consciously apply the tools and methodologies presented during the course. In particular, the following will be evaluated: technical mastery in the use of the tools covered; the relevance and originality of the proposed solutions; the ability to integrate theoretical and practical knowledge in a design context; clarity and communicative effectiveness in presenting the project, both in content and form.

Criteria for the composition of the final grade

Final vote: Project evaluation

Exam language

italiano o inglese, a scelta