02023 - Numerical Computing

Course Unit Page

Academic Year 2018/2019

Learning outcomes

At the end of the course students learn the basics of Numerical Computation as error analysis, data interpolation, numerical integration, non-linear equations, linear systems. They are able to solve problems of scientific computing.

Course contents

Floating point numbers and floating points arithmetics; polynomial functions; interpolation and least square best fitting; numerical integration; non linear equations; linear systems: direct and iterative methods; matrix eigenvalues and eigenvectors computation.
The course foresees an optional laboratory activity in which the Matlab system is used.


1. R.Bevilacqua, D.Bini, M.Capovani, O.Menchi, Metodi numerici, Zanichelli (1992)
2. J.Stoer, R.Bulirisch, Introduction to Numerical Analisysy, (second edition) Springer Verlag (1997)

Teaching methods

Frontal lessons in class;
Software presentation.

Assessment methods

The assessment of learning is done through an oral exam in which students must demonstrate knowledge of the arguments put forward during the course and know how to explain in a concise and correct form, from a mathematical point of view. The student must also demonstrate that they have acquired the elements of the course in order to be able to solve problems in scientific computing.

Teaching tools

Teacher’s pantries.

Links to further information


Office hours

See the website of Giulio Casciola

See the website of Elena Loli Piccolomini