This Is Linear Algebra

Linear Systems
Overview on linear systems: 0.00%
Row Reduction: 0.00%
Plan for Row Reduction: 0.00%
Notation for Row Operations: 0.00%
Algorithm for Row Reduction: 0.00%
Matrices: 0.00%
Matrix Operations and Matrix Algebra: 0.00%
Matrix Equations: 0.00%
The Superposition Principle: 0.00%
Elementary Matrices: 0.00%
Vector Spaces and Linear Transformations
Vector Spaces: 0.00%
The vector space ℝn: 0.00%
Definition of a vector space: 0.00%
Subspaces: 0.00%
Linear combinations and linear independence: 0.00%
Constructing and Describing Vector Spaces and Subspaces: 0.00%
Spanning sets, row spaces, and column spaces: 0.00%
Nullspaces: 0.00%
Range: 0.00%
Bases and dimension: 0.00%
Coordinate systems: 0.00%
Vector spaces over ℂ: 0.00%
Linear Transformations: 0.00%
Definition: 0.00%
Matrix representations of transformations: 0.00%
Change of basis: 0.00%
Vector spaces of linear transformations: 0.00%
Eigenvalues and Eigenvectors
The Determinant: 0.00%
Cofactor expansion: 0.00%
Combinatorial definition: 0.00%
Properties of the determinant: 0.00%
Eigenvalues and Eigenvectors: 0.00%
Definition: 0.00%
Eigenspaces: 0.00%
The characteristic polynomial: 0.00%
Direct sum decomposition: 0.00%
Properties of Eigenvalues and Eigenvectors: 0.00%
Similarity and diagonalization: 0.00%
Complex eigenvalues and eigenvectors: 0.00%
Geometric versus algebraic multiplicity: 0.00%
Shur’s Theorem: 0.00%
Normal matrices: 0.00%
Generalized eigenvectors: 0.00%
Inner Product Spaces
Inner Products on ℝn: 0.00%
The dot product in ℝn: 0.00%
Symmetric bilinear pairings on ℝn: 0.00%
Orthogonal vectors and subspaces in ℝn: 0.00%
Orthonormal vectors and orthogonal matrices: 0.00%
Projections and Least-squares Approximations: 0.00%
Projection onto 1-dimensional subspaces: 0.00%
Gram-Schmidt orthogonalization: 0.00%
Least-squares approximations: 0.00%
Least-squares solutions and the Fundamental Subspaces theorem: 0.00%
Applications of least-squares solutions: 0.00%
Projection onto a subspace: 0.00%
Polynomial data fitting: 0.00%
Complex inner product spaces: 0.00%
The complex scalar product in ℂn: 0.00%
Conjugate-symmetric sesquilinear pairings on ℂn, and their representation: 0.00%
Unitary matrices: 0.00%
Singular Values
Singular value decomposition: 0.00%
Overall: 0%

https://ximera.osu.edu/certificate/H4sIAAAAAAACAyXMzQrCMBAE4FcJOdsmprW6uXkSwWO9eNumqwbbBvIDBfHdTfSwDAzf7JsvOBPX%2FJQoRHYN5PmGpxKar3Ymj7ULqaYxidIG0e3vrSEDQDkRQOKotl3T5NmIsbxSUu0q2Vby0Mu9Vkq3UDcAtyyMSz4UIya7EHqcHjR4FJHWODj3yiTaOBXRP21g7Jzv8qOMHf84m2Ccz0Z%2Bvm4Jgji%2FAAAA/1Wml3%2FCtvtj4f71sun17ovIG2Wn9Z1NHh%2BOZqREHQdfX8h8tPFRV9YU9WNSg6z3RIKIXwsubdz%2FVB%2BJReZPV2H0jFmBSHwVWesGNUJ5ARCjZigH9N%2BXwb6FWP8WnXqFE9d%2BDNYcQ3aWQpftzBazl5l1gYWoXUclnpR4YijJRuV3FI6op00o5DsH0%2FDqtyP7vJ335duM4VfgXPnjyFWdzVQ4ibmOMbAJno%2Bdhw0XEGYHJ4Y7T%2Bc%2BSXqFP0Uov%2BKc5w1nOz2wODBJbCwRVupKeHYp1S88Y9Un6C8CP1fYE3Q3XpOybverl46U5KVnOtNLTOkSimkUBMzKhkIFqFTiiyA%3D%3D