Course: Linear Algebra

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Course title Linear Algebra
Course code KMA/LAA
Organizational form of instruction Lecture + Tutorial
Level of course Bachelor
Year of study not specified
Semester Winter and summer
Number of ECTS credits 5
Language of instruction Czech
Status of course Compulsory
Form of instruction Face-to-face
Work placements This is not an internship
Recommended optional programme components None
Lecturer(s)
  • Ekstein Jan, RNDr. Ph.D.
  • Kopřiva Martin, Mgr.
  • Šebková Milena, RNDr.
  • Holub Přemysl, Doc. RNDr. Ph.D.
  • Krejčíková Kateřina, Bc.
  • Melicharová Petra, Bc.
  • Teska Jakub, RNDr. Mgr. Ph.D.
Course content
1. Complex numbers, fields. Polynomials, rings. Horner scheme, polynomial factorization. 2. Vector space, linear dependence and independence, basis and dimension of vector space, coordinates of vector relative to basis 3. Matrices, determinant of matrix and its basic properties, determinant expansion 4. Gaussian elimination. Fast calculation of determinants. Vector spaces associated with matrix. Rank of matrix, calculation of rank using determinants 5. Matrix inverse, Gauss-Jordan elimination, calculation of matrix inverse using determinants 6. Linear transformation, kernel and image and their dimensions, matrix of linear transformation and its properties. Fundamental Theorem of Linear Algebra. 7. Inverse linear transformation, linear transformation composition and its matrix, vector space isomorphism, change of basis and change-of-basis matrix 8. Systems of linear equations, homogeneous and non-homogeneous systems of equations, linear systems with invertible coefficient matrix, Cramer's rule 9. Eigenvalues and eigenvectors of matrix, generalized eigenvectors. Similarity of matrices. Jordan normal form of matrix. Matrix functions 10. Metric, norm, inner product and their properties. Euclidean and unitary spaces. Orthogonal and orthonormal basis for a vector space 11. Gram-Schmidt process, orthogonal projection onto subspace. QR decomposition of a matrix. 12. Linear least squares regression. Linear forms. Multilinear forms. Quadratic forms and real valued symmetric matrices. Definiteness of a matrix. 13. Inertia of quadratic form, Sylvester's law of inertia for quadratic forms. Quadratic forms and optimization.

Learning activities and teaching methods
Interactive lecture, Collaborative instruction
  • Preparation for an examination (30-60) - 54 hours per semester
  • Contact hours - 65 hours per semester
  • Preparation for formative assessments (2-20) - 12 hours per semester
prerequisite
Knowledge
to explain the concept of a vector
to define the concept of a function
to identify equations of basic geometric configurations
Skills
to use basics of analytic geometry
to solve elementary systems of equations
Competences
N/A
N/A
learning outcomes
Knowledge
to explain the concept of a vector and matrix
to describe the concept of a vector space
to describe the concept of a linear transformation
to characterize eigenvalues and eigenvectors of a matrix
Skills
to find roots of polynomials in one variable
to calculate determinant of a matrix, matrix inverse and rank of matrix
to solve systems of linear algebraic equations
to find eigenvalues and eigenvectors of a matrix
to use the least squares method
Competences
N/A
N/A
teaching methods
Knowledge
Lecture
Skills
Practicum
Competences
Lecture
Practicum
assessment methods
Knowledge
Oral exam
Written exam
Skills
Test
Written exam
Competences
Oral exam
Recommended literature
  • Anton, H.; Rorres, Ch. Elementary Linear Algebra: Applications Version. Wiley, 2013. ISBN 978-1118434413.
  • Axler, Sheldon. Linear Algebra Done Right. Springer International Publishing, 2015. ISBN 978-3-319-11079-0.
  • Bečvář, Jindřich. Lineární algebra. MatfyzPress, 2020. ISBN 978-80-7378-378-5.
  • Bican, Ladislav. Linární algebra a geometrie. Academia, 2009. ISBN 978-80-200-1707-9.
  • Demlová, Marie; Nagy, Jozef. Algebra. 2. vyd. Praha : SNTL, 1985.
  • Havel, Václav; Holenda, Jiří. Lineární algebra. 1. vyd. Praha : SNTL, 1984.
  • Hladík, Milan. Lineární algebra (nejen) pro informatiky. MatfyzPress, 2019. ISBN 9788073783921.
  • Motl, Luboš. Pěstujeme lineární algebru. 2. vyd. Praha : Univerzita Karlova, 1999. ISBN 80-7184-815-8.
  • Motl, Luboš; Zahradník, Miloš. Pěstujeme lineární algebru. Univerzita Karlova, 2002. ISBN 80-246-0421-3.
  • Olver, Peter J.; Shakiban, Chehrzad. Applied Linear Algebra. Springer International Publishing AG, part of Springer Nature, 2018. ISBN 978-3-319-91040-6.
  • Tesková, Libuše. Lineární algebra. 1. vyd. Plzeň : Západočeská univerzita, 2001. ISBN 80-7082-797-1.
  • Tesková, Libuše. Sbírka příkladů z lineární algebry. 5. vyd. Plzeň : Západočeská univerzita, 2003. ISBN 80-7043-263-2.


Study plans that include the course
Faculty Study plan (Version) Category of Branch/Specialization Recommended year of study Recommended semester
Faculty: Faculty of Applied Sciences Study plan (Version): Geomatics (2018) Category: Construction industry, geodesy and cartography 1 Recommended year of study:1, Recommended semester: Winter