Furnish beginning graduate students with computational techniques needed for their research, such as programming, data analysis, and use of scientific software. Provide numerical skills useful in today's academic job market.

**Outline:**

). Useful Software: | Mathematica and Xmgrace. |

1. Basic Numerical Techniques: | interpolation, differentiation, integration, fitting, root finding. |

2. Ordinary and Partial Differential Equations: | Euler and Runge-Kutta methods, initial-value, and eigenvalue problems. |

3. Chaotic Systems: | driven damped pendulum, spectral analysis. |

4. Monte Carlo Simulations: | random number generators, multi-dimensional integrals, many-body systems, Ising model. |

5. Matrix Manipulations: | eigenvalue problems, multi-dimensional fitting. |

6. Molecular Dynamic and Parallel Computing: | atomic motion in a solid, message passing interface. |

**Syllabus:**

**The grade will be based 50% on homework, and 50% on the term project.**