This course provides a modern elementary introduction to linear algebra and a broad selection of interesting applications. This modern approach reflects the ways data science and engineers use linear algebra in practice. The topics covered in this course are: Systems of linear equations, matrices, linear programming, determinants, vector spaces, inner product spaces, eigenvalues and eigenvectors, linear transformations, and numerical methods. Applications to different fields of data science and engineering will be a focus of this course, as this course is designed to meet the needs of students in these disciplines.

Temps présentiel : 45 heures

Charge de travail étudiant : 150 heures

Méthode(s) d'évaluation : Examen écrit

Référence :
Linear Algebra and Its Applications, 6th Edition. Lay, David | Lay, Steven | McDonald, Judi