I'll list the topics that I think are the most important.
Prerequisites:
Complex numbers
Polynomials (Use Axler for this)
The basics:
Vector spaces over ##\mathbb C##
Subspaces
Linear independence
Span
Bases
Inner products and norms:
Orthogonality
The norm associated with an inner product
Orthonormal bases
Linear transformations:
Components of a linear transformation with respect to a pair of ordered bases. (I wrote a https://www.physicsforums.com/threads/matrix-representations-of-linear-transformations.694922/ about this).
Matrix multiplication (Prove that ##[T\circ S]_{E,G}=[T]_{E,F}[ S]_{F,G}##).
Change of basis (Prove that ##[T]_F## is similar to ##[T]_E##).
Kernel and range (the definitions and the rank-nullity theorem)
The adjoint of a linear transformation
Self-adjoint and unitary linear operatorsBijective linear transformations:
Determinants (Use Treil for this)
The theorem that lists conditions equivalent to ##\det T\neq 0##.
Spectral theory:
Eigenvalues and eigenvectors
The spectral theorem for self-adjoint linear operators (Surprisingly easy. See
this post).
Two more things:
Positive-semidefinite linear operators (Use Treil for this)
Projection operators (Prove the finite-dimensional versions of the theorems in section 6.3 of Friedman's "Foundations of modern analysis").