21067 - MATHEMATICS FOR DAIHS - PREPARATORY COURSE
Department of Computing Sciences
Course taught in English
Go to class group/s: 1
Course Director:
FABRIZIO IOZZI
FABRIZIO IOZZI
Mission & Content Summary
MISSION
This preparatory course introduces the basis of linear algebra and probability theory.
In the first part of the course, we will cover some basic topics of linear algebra, including vectors, matrices, linear systems, vector spaces, linear maps, eigenvalues and eigenvectors, the spectral theorem, and the singular value decomposition.
CONTENT SUMMARY
- Complex Numbers
- Vectors
- Linear Systems and Matrices
- Vector Spaces
- Linear Maps and their Matrix Representation
- Invertible Linear Maps and Isomorphism
- Norms and Inner Products
- Eigenvalues and Eigenvectors
- Change of Basis
- Spectral Theorem
- Positive Definite and Semidefinite Matrices
Intended Learning Outcomes (ILO)
KNOWLEDGE AND UNDERSTANDING
At the end of the course student will be able to...
Demonstrate basic knowledge of linear algebra.
Linear algebra course covers the following topics: vectors, vector spaces, matrices, linear maps, eigenvalues and eigenvectors, spectral theorem, and singular value decomposition.
APPLYING KNOWLEDGE AND UNDERSTANDING
At the end of the course student will be able to...
Understand the fundamental concepts of linear algebra and probability theory, and solve basic exercises.
Teaching methods
- Lectures
- Practical Exercises
DETAILS
Classes are taken online, with a set of prerecorded video lectures.
Assessment methods
| Continuous assessment | Partial exams | General exam | |
|---|---|---|---|
|
x |
ATTENDING AND NOT ATTENDING STUDENTS
The course has no exams.
Teaching materials
ATTENDING AND NOT ATTENDING STUDENTS
Suggested textbooks:
- Sheldon Axler, Linear Algebra Done Right
- Marc Peter Deisenroth, A. Aldo Faisal, Cheng Soon Ong, Mathematics for Machine Learning
- Gilbert Strang, Introduction to Linear Algebra
Last change 28/04/2026 12:01