Linear Algebra

Vector spaces, linear maps, and matrix theory. Essential for numerical methods, PCA, and portfolio optimization.

Topics

• Vectors and matrices
• Systems of linear equations
• Eigenvalues and eigenvectors
• Decompositions (LU, QR, SVD)
• Applications in finance