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).
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
! 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.
  • 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.
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
Listed among pre-requisites of other courses
Teacher's information
More information can be found in IS of the course.
The course is also listed under the following terms Spring 2020, Spring 2021, Spring 2022, Spring 2023, Spring 2024.
  • Enrolment Statistics (Spring 2025, recent)
  • Permalink: https://is.muni.cz/course/fi/spring2025/MB141