Linear Algebra for Computer Science

Linear Algebra is an important Mathematics course of a bachelor educational program of Computer Science. The course is to lay a foundation for future study of subjects like computer graphics, machine learning and quantum computing. This course serves as a cornerstone for applications; we will not only to evaluate students’ theoretical knowledge, but also assess their skills for modelling practical problems and finding solutions to them.

Rough course content:

• Linear systems, existence of solutions.
• Basic concepts of vectors, vector spaces, span, basis, linear independence, linear transformations.
• Fundamentals of complex numbers.
• Fundamental properties of matrices: row echelon form, determinants, transpose and inverse matrices, eigenvalues, eigenvectors, similarity, diagonalization, representation of linear transformations.
• Applications of linear algebra.

Literature used:

• Linear Algebra and Its Applications by Gilbert Strang, 2006.
• Introduction to Linear Algebra by Gilbert Strang, 2009.
• Linear Algebra Done Right by Sheldon Axler, 2015.
• Undergraduate Algebra by Serge Lang, 2000.
• Linear Algebra with Applications by Otto Bretscher, 2013.

Some handwritten notes by weeks:

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Weekly exercises are usually posted in the relevant online platform.