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.
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 |
|---|
Mathematical analysis 1
Computer Architecture
2° Year activated in the A.Y. 2022/2023
| Modules | Credits | TAF | SSD |
|---|
3° Year activated in the A.Y. 2023/2024
| Modules | Credits | TAF | SSD |
|---|
1 module among the following| Modules | Credits | TAF | SSD |
|---|
Mathematical analysis 1
Computer Architecture
| Modules | Credits | TAF | SSD |
|---|
| Modules | Credits | TAF | SSD |
|---|
1 module among the following| Modules | Credits | TAF | SSD |
|---|
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.
Linear Algebra (2021/2022)
Teaching code
4S00002
Academic staff
Coordinator
Credits
6
Language
Italian
Scientific Disciplinary Sector (SSD)
MAT/02 - ALGEBRA
Period
Secondo semestre dal Mar 7, 2022 al Jun 10, 2022.
Learning outcomes
The course aims to introduce the basic techniques of linear algebra, which is a fundamental tool in most applications of mathematics: matrices, Gauss elimination, vector spaces, inner products, determinants, eigenvalues and eigenvectors. At the end of the course, the students shall prove of being able to: apply linear algebra techniques to the solution of problems; to apply linear algebra techniques to solution of problems; to recognize applicability of linear algebra to various situations even in not strictly mathematical contexts; to choose among the various techniques the one better suited to the problem at hand; to describe the solution of a problem employing correct terminology; to widen their knowledge starting from what they learned.
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
Examination Methods
The written exam consists of solving some exercises on the topics of the course.
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
