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**Unformatted text preview: **ibility 5. Subspaces, kernel and image of a linear transformation 6. Linearly independent, orthogonal and orthonormal sets of vectors 7. Basis, linear combinations of basis vectors, coordinates, change of basis, similar matrices 8. Gram-Schmidt process for nding an orthonormal basis 9. Determinants, calculating the determinant, geometric interpretation of the determinant, classical adjoint 10. Eigenvalues and eigenvectors, nding them, algebraic vs. geometric multiplicity, diagonalization, powers of a matrix, complex eigenvalues 1...

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