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Course, academic year 2019/2020
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Linear Algebra 1 - NMAI057
Title in English: Lineární algebra 1
Guaranteed by: Department of Applied Mathematics (32-KAM)
Faculty: Faculty of Mathematics and Physics
Actual: from 2019
Semester: winter
E-Credits: 5
Hours per week, examination: winter s.:2/2 C+Ex [hours/week]
Capacity: unlimited
Min. number of students: unlimited
State of the course: taught
Language: Czech, English
Teaching methods: full-time
Guarantor: doc. Mgr. Milan Hladík, Ph.D.
doc. Mgr. Petr Kolman, Ph.D.
Class: Informatika Bc.
Classification: Mathematics > Algebra
Annotation -
Last update: G_I (11.04.2003)
Basics of linear algebra (vector spaces and linear maps, solutions of linear equations, matrices).
Course completion requirements -
Last update: doc. RNDr. Jiří Fiala, Ph.D. (15.10.2019)

Tutorial requirements: Weekly/biweekly quizzes (worth 50%) and homework (worth 50%). The passing score is 60%. Students who earn 40-59% for quizzes and homework together will be given a test at the end of the semester, and those who pass the test will be given tutorial credit. Students who earn less than 40% for quizzes and homework together will not be given tutorial credit.

Literature -
Last update: Andrew Goodall, Ph.D. (11.10.2017)

D. Poole. Linear Algebra, A Modern Introduction. 3rd Int. Ed., Brooks Cole, 2011. Chapters 1,2,3,6.

Also useful:

G. Strang. Linear algebra and its applications. Thomson, USA, 4rd edition, 2006.

C. D. Meyer. Matrix analysis and applied linear algebra. SIAM, Philadelphia, PA, 2000.

W. Gareth. Linear Algebra with Applications. Jones and Bartlett Publishers, Boston, 4th edition, 2001.

R. Beezer, A First Course in Linear Algebra - a free online textbook.

Requirements to the exam -
Last update: doc. RNDr. Jiří Fiala, Ph.D. (14.10.2019)

The exam is primarily oral. The students will be given enough time to prepare their answers in written form.

The exam is focused on theory - knowledge of concepts, facts, arguments and applications (i.e. definitions, theorems, proofs and examples).

Class credits ("zápočet") are prerequisite for taking the examination.

Syllabus -
Last update: Andrew Goodall, Ph.D. (11.10.2017)

Basic matrix operations, inverse matrices. Gaussian elimination, row echelon form, solving systems of linear equations.

Vector spaces: basic concepts, basis, dimension, linear mapping. Applications of linear algebra.

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