Course details
Linear Algebra
ILG Acad. year 2025/2026 Winter semester 5 credits
Matrices and determinants. Systems of linear equations. Vector spaces and subspaces. Linear representation, coordinate transformation. Own values and own vectors. Quadratic forms and conics.
Guarantor
Course coordinator
Language of instruction
Completion
Time span
- 26 hrs lectures
- 26 hrs exercises
Assessment points
- 80 pts final exam
- 20 pts numeric exercises
Department
Lecturer
Instructor
Hliněná Dana, doc. RNDr., Ph.D. (UMAT)
Pekárková Eva, Mgr. Ing., Ph.D. (RE-OTZ)
Sedláková Eva, Mgr.
Vévodová Libuše, Mgr. (UMAT)
Vítovec Jiří, Mgr., Ph.D. (UMAT)
Learning objectives
The students will get familiar with elementary knowledge of linear algebra, which is needed for informatics applications. Emphasis is placed on mastering the practical use of this knowledge to solve specific problems.
The students will acquire an elementary knowledge of linear algebra and the ability to apply some of its basic methods in computer science.
Prerequisite knowledge and skills
Secondary school mathematics.
Study literature
- Havel, V., Holenda, J., Lineární algebra, STNL, Praha 1984.
- Kolman B., Elementary Linear Algebra, Macmillan Publ. Comp., New York 1986.
Syllabus of lectures
- Systems of linear homogeneous and non-homogeneous equations. Gaussian elimination.
- Matrices and matrix operations. Rank of the matrix. Frobenius theorem.
- The determinant of a square matrix. Inverse and adjoint matrices. The methods of computing the determinant.The Cramer's Rule.
- The vector space and its subspaces. The basis and the dimension. The coordinates of a vector relative to a given basis. The sum and intersection of vector spaces.
- The inner product. Orthonormal systems of vectors. Orthogonal projection and approximation. Gram-Schmidt orthogonalisation process.
- The transformation of the coordinates.
- Linear mappings of vector spaces. Matrices of linear transformations.
- Rotation, translation, symmetry and their matrices, homogeneous coordinates.
- The eigenvalues and eigenvectors. The orthogonal projections onto eigenspaces.
- Numerical solution of systems of linear equations, iterative methods.
- Conic sections.
- Quadratic forms and their classification using sections.
- Quadratic forms and their classification using eigenvectors.
Syllabus of numerical exercises
Examples of tutorials are chosen to suitably complement the lectures.
Progress assessment
- Evaluation of the five written tests (max 20 points).
- Participation in lectures in this course is not controlled.
- The knowledge of students is tested at exercises at five written tests for 4 points each and at the final exam for 80 points.
- If a student can substantiate serious reasons for an absence from an exercise, (s)he can either attend the exercise with a different group (please inform the teacher about that) or ask his/her teacher for an alternative assignment to compensate for the lost points from the exercise.
- The passing boundary for ECTS assessment: 50 points.
Course inclusion in study plans
- Programme BIT, 1st year of study, Compulsory
- Programme BIT (in English), 1st year of study, Compulsory