M1VM01 Algorithmization and numerical computations

Faculty of Science
Spring 2025
Extent and Intensity
0/3/0. 5 credit(s) (fasci plus compl plus > 4). Type of Completion: k (colloquium).
In-person direct teaching
Teacher(s)
doc. RNDr. Lenka Přibylová, Ph.D. (lecturer)
Guaranteed by
doc. RNDr. Lenka Přibylová, Ph.D.
Department of Mathematics and Statistics – Departments – Faculty of Science
Supplier department: Department of Mathematics and Statistics – Departments – Faculty of Science
Prerequisites
no prerequisites
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
Course objectives
This is a companion course to linear algebra. The aim of the course is practical mastery of gained theoretical knowledge using available software.
Learning outcomes
This is a companion course to linear algebra. The aim of the course is practical mastery of gained theoretical knowledge using available software.
Syllabus
  • Introduction to used software
  • Basic calculations and numerical errors
  • Calculations of linear algebra: vectors, matrices, systems of linear equations
  • Linear models, data and matrix calculus
  • Applied linear algebra
Literature
  • KLIMA, Richard E., Neil SIGMON and Ernest L. STITZINGER. Applications of abstract algebra with Maple and Matlab. 2nd. ed. Boca Raton, Fla.: Chapman & Hall/CRC, 2007, 505 s. ISBN 9781584886105. info
  • BAUER, Luboš and Arnošt SVOBODA. Výuka matematiky s využitím programu MATLAB. In Sborník příspěvků. první vydání,152str. Brno: nakladatelství KONVOJ spol. s r.o., 2003, p. 14-17. ISBN 80-7302-051-3. info
  • GANDER, Walter and Jiří HŘEBÍČEK. Solving Problems in Scientific Computing Using Maple and Matlab. 1st ed. Beijing, China: Higher Education Press, Beijing, 1999, 330 pp. ISBN 7-04-006935-0. info
  • PÄRT-ENANDER, Eva. The Matlab handbook. Harlow: Addison-Wesley, 1997, xv, 423 s. ISBN 0-201-87757-0. info
Teaching methods
Demonstration of selected methods and computer practice.
Assessment methods
Credit will be awarded on the basis of preparation during semestr and the final project.
Language of instruction
Czech
Further Comments
The course is taught annually.
The course is taught: every week.
Teacher's information
https://is.muni.cz/auth/el/sci/jaro2022/M1VM01/index.qwarp
The course is also listed under the following terms Autumn 2007 - for the purpose of the accreditation, Autumn 2011, Autumn 2011 - acreditation, Autumn 2012, Autumn 2013, Autumn 2014, Autumn 2015, Autumn 2016, autumn 2017, Autumn 2018, Autumn 2019, Spring 2021, Spring 2022, Spring 2023, Spring 2024.
  • Enrolment Statistics (recent)
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