The course presents mathematical algorithms and analysis to solve linear systems of equations and matrix eigenvalue problems. Matrix norms and analysis. Direct and iterative methods: including factirization methods, singular value decomposition, Jacobi and Gauss-Seidel iteration, power methods, QR algorithm. Operation counts, condition numbers and error analysis. Prerequisites: MAT 215, MAT 224, and a Programming language.