Linear Algebra
Vector spaces, matrix methods, linear maps, and spectral structure.
Vector spaces, matrix methods, linear maps, and spectral structure.
This course expects complete reasoning: definitions and hypotheses are stated, manual arguments remain visible, computation is labeled as exact or approximate, and conclusions are interpreted rather than merely reported.
Course outcomes
- Represent and reason about vectors, matrices, systems, and linear transformations.
- Distinguish computation from the structural claims that make an algorithm valid.
- Interpret rank, independence, bases, eigenvalues, and eigenvectors geometrically.
- Verify exact calculations with SymPy and numerical calculations with NumPy.
Prerequisites
advanced-algebra