MWF 10am - Mill Lane Room 3

- Lecture 1: Interpolation
- Lecture 2: Finite differences and Newton's interpolation formula
- Lecture 3: Orthogonal polynomials
- Lecture 4: Least-squares polynomial fitting and Gaussian quadrature
- Lecture 5: Gaussian quadrature (continued) and Peano kernel theorem
- Lecture 6: Peano kernel theorem (continued) and Euler's method for ODEs
- Lecture 7: Multistep methods for ODEs
- Lecture 8: Convergence of multistep methods
- Lecture 9: Runge-Kutta methods
- Lecture 10: Stiffness and linear stability domains
- Lecture 11: Implementation of ODE methods: error control
- Lecture 12: LU decomposition
- Lecture 13: Pivoting in LU factorization, symmetric matrices and LDL^T factorization
- Lecture 14: LU factorization for sparse matrices; QR factorization
- Lecture 15: QR factorization: Gram-Schmidt algorithm and Givens algorithm
- Lecture 16: QR factorization: Householder reflections; least-squares

- Matlab demos
- Lecture notes for the same course by Dr. Stephen Cowley [also inspired by the 2010 edition]
- The definition of numerical analysis by L. N. Trefethen
- Top ten algorithms of the 20th century, by Barry Cipra