Covers determining vector spaces, calculating kernels and images, defining bases, and discussing subspaces and vector spaces.
Introduces linear applications, span, kernels, and images in vector spaces with illustrative examples and theorems.
Delves into the Rank Theorem's implications for linear transformations and mappings.
Covers the basics of linear algebra, including linear maps, bases, and matrix operations.
Covers the basics of linear algebra, emphasizing the identification of subspaces through key properties.
Covers the definition and properties of linear forms in vector spaces, including generating families and direct sums.
