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 Bioinformatica - 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.

1° Year

ModulesCreditsTAFSSD
12
C
CHIM/03 ,CHIM/06
6
A
FIS/01
English B2
6
E
-

2° Year  activated in the A.Y. 2023/2024

ModulesCreditsTAFSSD
12
B
INF/01
6
C
BIO/18

3° Year  activated in the A.Y. 2024/2025

ModulesCreditsTAFSSD
Final exam
3
E
-
activated in the A.Y. 2023/2024
ModulesCreditsTAFSSD
12
B
INF/01
6
C
BIO/18
Modules Credits TAF SSD
Between the years: 2°- 3°
Further activities
3
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

4S00002

Coordinator

Enrico Gregorio

Credits

6

Language

Italian

Scientific Disciplinary Sector (SSD)

MAT/02 - ALGEBRA

Period

Semester 1 dal Oct 3, 2022 al Jan 27, 2023.

Learning objectives

The course introduces the basic techniques of linear algebra, which is a fundamental tool in most applications of mathematics. At the end of the course, the students will be able to analyze and model problems in a rigorous way and to recognize applicability of linear algebra in different contexts. In particular, they will be able to employ tools and techniques of linear algebra to solve problems of matrix decompositions, analysis of linear maps, orthogonalization and computation of eigenvalues and eigenvectors. The students will be able to precisely describe the solution of a problem employing the appropriate terminology. Moreover, they will acquire adequate confidence on the topics studied that will allow them to independently deepen their knowledge starting from what they learned.

Prerequisites and basic notions

Standard high school mathematical curriculum

Program

Linear systems and matrices
Inverse matrices
Gauss elimination and LU decomposition
Vector spaces and linear maps
Bases and matrix representation of linear maps
Inner products and Gram-Schmidt algorithm
Determinants
Eigenvalues and eigenvectors, diagonalization of matrices

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

In-person lectures along with exercise classes preparing to the written exam.

Learning assessment procedures

The written exam consists in discussing a topic from a theoretical point of view and in solving some exercises on the topics of the course.

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

• Knowledge and understanding: comprehension of the text of the problems and mastering of the theory behind them.
• Applying knowledge and understanding: ability to apply the general techniques to a specific problem
• Making judgements: ability to express the learned theoretical concepts in varied situations
• Communication skills: language clarity and appropriateness
• Learning skills: ability to structure a proof different from those presented during the course

Criteria for the composition of the final grade

Theory: maximum 10/30
Exercises: maximum 22/30

Exam language

Italiano