This is a course in linear algebra for Computer Science graduate studies. It covers basic linear algebra tools such as matrices, matrix operations and properties and determinants, vector spaces, linear transformations, eigenvalues and eigenvectors, and diagonalization, which are essential linear algebra tools and concepts that are foundational for various applications in computer science, including machine learning, computer graphics, and data analysis.
- Teacher: Jay Vince Serato
- Enrolled students: 18