Scientific Computing

This course covers numerical analysis and solution techniques for common scientific and engineering problems and provides essential foundation for important computational subject areas such as medical imaging, bioinformatics, financial modeling, to name a few. The course covers a variety of topics including numerical approximations and errors, roots of equations, systems of linear algebraic equations, curve fitting, integration, optimization, and numerical solutions for ordinary differential equations. The course will place major emphasis on case studies and practical projects to address realistic computational problems using high-performance numerical techniques that utilize recent advances in grid-computing and graphical processing units (GPUs).

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