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.

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 in Informatica - Enrollment from 2025/2026

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.

2° Year  It will be activated in the A.Y. 2025/2026

ModulesCreditsTAFSSD
12
B
INF/01
12
B
INF/01
6
A
FIS/01
6
C
MAT/01

3° Year  It will be activated in the A.Y. 2026/2027

ModulesCreditsTAFSSD
6
B
INF/01
Final exam
6
E
-
It will be activated in the A.Y. 2025/2026
ModulesCreditsTAFSSD
12
B
INF/01
12
B
INF/01
6
A
FIS/01
6
C
MAT/01
It will be activated in the A.Y. 2026/2027
ModulesCreditsTAFSSD
6
B
INF/01
Final exam
6
E
-
Modules Credits TAF SSD
Between the years: 2°- 3°
Training
6
F
-
Between the years: 2°- 3°

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

4S02709

Credits

12

Scientific Disciplinary Sector (SSD)

INF/01 - INFORMATICA

Learning objectives

The course objective is to provide the foundamental tools to design algorithmic solutions for concrete programs. The algorithms are evaluated and compared based required amount of resources. At the end of the course the student will have to demonstrate knowledge and understanding of the main algorithms for the problems of sorting, selection, priority queues, visit of graphs, shortest paths, minimum spanning trees, maximum flow; have ability to apply acquired knowledge and understanding skills to compare algorithms on the basis of their complexity; know how to choose the right algorithm for a specific situation; know how to develop the skills necessary to expand the knowledge learned in order to understand algorithmic solutions to new problems.

Educational offer 2024/2025

ATTENTION: The details of the course (teacher, program, exam methods, etc.) will be published in the academic year in which it will be activated.
You can see the information sheet of this course delivered in a past academic year by clicking on one of the links below: