Numerical Computing

This course will cover several topics, including direct and iterative methods for the solutions of linear systems of equations, solution techniques for nonlinear equations, algorithms for the computation of eigenvalues and singular values, the Page Rank algorithm, graph partitioning, polynomial interpolation, linear and nonlinear least squares, numerical differentiation and integration, constrained optimization and the simplex method. As much as possible, the numerical methods tackled during the course will be presented in the context of real-world applications. 

Numerical computing stems from the combination of computer science and mathematics and, during the course, we will develop and analyze algorithms that can be used to solve problems pertaining to different real-life domains, like, e.g., science, engineering, medicine, and finance. This course is explicitly designed for Bachelor students in Informatics and no mathematical prerequisite is needed except some of the topics tackled in the courses Calculus (1st semester) and Linear Algebra (2nd semester), which will be refreshed in the introductory lectures. Several theoretical lectures will introduce and discuss a selection of widely used numerical methods as well as their practical implementation, while the students will have the opportunity to learn the principles and practices of numerical computations by tackling three or four mini-projects based on real-world applications.

In presenza

The goal of the course is that students acquire a solid understanding and practical insights in the implementation of scientific numerical simulations. This will be achieved through both a set of theoretical lectures and a selection of mini-projects focused on numerical computing.

30% of the grade is determined by mandatory graded projects and 70% is determined by a final written or oral exam during the official examination period.