Linear algebra occupies a central position in the mathematical curriculum, bridging abstract theory and practical applications across science, engineering and data science. Teaching and learning in ...

Vector spaces, linear transformation, matrix representation, inner product spaces, isometries, least squares, generalised inverse, eigen theory, quadratic forms, norms, numerical methods. The fourth ...

*Note: This course discription is only applicable to the Computer Science Post-Baccalaureate program. Additionally, students must always refer to course syllabus for the most up to date information.

Solving linear systems of equations and LU factorization. Matrix/vector operations and algebra. Vector spaces and bases. Eigenvalues and eigenvectors, Orthogonality, solution of least squares, and QR ...