# FI:MB141 Linear alg. and discrete math - Course Information

## MB141 Linear algebra and discrete mathematics

**Faculty of Informatics**

Spring 2025

**Extent and Intensity**- 2/2/0. 3 credit(s) (plus extra credits for completion). Type of Completion: zk (examination).

In-person direct teaching **Teacher(s)**- Mgr. David Kruml, Ph.D. (lecturer)

doc. RNDr. Martin Čadek, CSc. (seminar tutor)

Mgr. Martin Doležal (seminar tutor)

Mgr. Petr Liczman (seminar tutor)

Mgr. Miloslav Štěpán (seminar tutor)

Mgr. Dominik Trnka (seminar tutor)

Mgr. Matouš Trnka (seminar tutor)

Mgr. Petr Vlachopulos (seminar tutor)

doc. Lukáš Vokřínek, PhD. (seminar tutor)

Mgr. Jan Vondruška (seminar tutor) **Guaranteed by**- Mgr. David Kruml, Ph.D.

Department of Mathematics and Statistics – Departments – Faculty of Science

Supplier department: Department of Mathematics and Statistics – Departments – Faculty of Science **Prerequisites**- !NOW(
**MB151**Linear models ) && ( !**MB151**Linear models || !**MB154**Discrete mathematics )

MB141 is a lightweight version of MB151 and MB154, so it can be replaced by completing both full courses. **Course Enrolment Limitations**- The course is also offered to the students of the fields other than those the course is directly associated with.
**fields of study / plans the course is directly associated with**- there are 38 fields of study the course is directly associated with, display
**Course objectives**- Introduction to linear algebra, analytical geometry and elementary number theory.
**Learning outcomes**- At the end of this course, students should be able to: understand basic concepts of linear algebra; apply these concepts to iterated linear processes; solve basic problems in analytical geometry; apply elemntary number theory on kryptography.
**Syllabus**- Obsah kurzu Lineární:
- 1. Geometry in plane. Complex numbers. 2. Systems of linear equations. Gauss elimination. 3. Operation with matrices. Inverse matrix, determinent. 4. Vector spaces, báses, dimension, coordinates. 5. Linear mappings, eigenvalues and eigenvectors. 6. Afinne geometry. 7. Eukleidian geometr. 8. Elementry number theory. 9. Congruences. 10. Application in kryptography. 11. Linear processes. 12. Linear optimization.

**Literature**- PANÁK, Martin, Jan SLOVÁK and Michal BULANT.
*Matematika drsně a svižně (Brisk quide to mathematics)*. 2013. ISBN 978-80-210-6307-5. Available from: https://dx.doi.org/10.5817/CZ.MUNI.O210-6380-2013.*Základní učebnice matematiky pro vysokoškolské studium. Na MU využívána zejména jako podpora výuky matematiky na Fakultě informatiky.*info

*recommended literature*- PANÁK, Martin, Jan SLOVÁK and Michal BULANT.
**Teaching methods**- Lecture covering the theory with illustrative solved problems. Tutorials devoted to solving numerical problems.
**Assessment methods**- Examination is written. A student needs to attend at least 9 of 13/14 seminars and to achieve at least 40% points at the exam to pass the course.
**Language of instruction**- Czech
**Listed among pre-requisites of other courses****MB143**Design and analysis of statistical experiments

(MB141 || MB142 || MB151 || MB152) && !MB153 && !NOW(MB153)**MB151**Linear models

!NOW(MB141)**PV275**Introduction to Quantum Computer Programming

( MB141 || MB151 || MB101 || MB201 ) && IB111

**Teacher's information**- https://is.muni.cz/auth/ucitel/?fakulta=1433;obdobi=7644

More information can be found in IS of the course.

- Enrolment Statistics (Spring 2025, recent)
- Permalink: https://is.muni.cz/course/fi/spring2025/MB141