First cycle
degree courses
Second cycle
degree courses
Single cycle
degree courses
School of Engineering
Course unit
NUMERICAL ANALYSIS (Ult. numero di matricola da 0 a 4)
IN18101050, A.A. 2019/20

Information concerning the students who enrolled in A.Y. 2019/20

Information on the course unit
Degree course First cycle degree in
IN0510, Degree course structure A.Y. 2012/13, A.Y. 2019/20
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Degree course track AMBIENTE E TERRITORIO [001PD]
Number of ECTS credits allocated 9.0
Type of assessment Mark
Course unit English denomination NUMERICAL ANALYSIS
Department of reference Department of Civil, Environmental and Architectural Engineering
Mandatory attendance No
Language of instruction Italian
Single Course unit The Course unit can be attended under the option Single Course unit attendance
Optional Course unit The Course unit is available ONLY for students enrolled in ENVIRONMENTAL AND LAND PLANNING ENGINEERING


Course unit code Course unit name Teacher in charge Degree course code
IN18101050 NUMERICAL ANALYSIS (Ult. numero di matricola da 0 a 4) MASSIMILIANO FERRONATO IN0505

ECTS: details
Type Scientific-Disciplinary Sector Credits allocated
Other -- -- 3.0
Basic courses MAT/08 Numerical Analysis 6.0

Course unit organization
Period Second semester
Year 1st Year
Teaching method frontal

Type of hours Credits Teaching
Hours of
Individual study
Lecture 9.0 72 153.0 No turn

Start of activities 02/03/2020
End of activities 12/06/2020
Show course schedule 2019/20 Reg.2012 course timetable

Examination board
Board From To Members of the board
15 2019 01/10/2019 15/03/2021 FERRONATO MASSIMILIANO (Presidente)
MAZZIA ANNAMARIA (Membro Effettivo)
JANNA CARLO (Supplente)
14 2018 01/10/2018 15/03/2020 FERRONATO MASSIMILIANO (Presidente)
MAZZIA ANNAMARIA (Membro Effettivo)
JANNA CARLO (Supplente)

Prerequisites: The knowledge of the main topics developed in the Mathematical Analysis course is useful.
Target skills and knowledge: The Numerical Analysis class aims at providing the engineering students with the basic knowledge of the numerical techniques for solving linear and non-linear systems of equations, computing integrals and derivatives, interpolating and approximating data.
The main skills consist in the acquisition of the principles of numerical programming and the ability to develop codes for the solution of specific numerical applications.
Examination methods: The exam is subdivided into two partial tests carried out in different dates.
1. A written test (2 hours), consisting of two exercises and a theoretical question.
2. A programming test (1 hour and 15 minutes), carried out at the computer.
Both tests are passed with a score greater than or equal 10 18/30. The final score is the weighted average of the two scores, with weight 0.75 for the written test and 0.25 for the programming test. The score registration is performed through an appropriate list. In that occasion, the student can check the partial tests and carry out an oral test on a voluntary basis.
Assessment criteria: The evaluation is based on:
- the knowledge and capability of using numerical algorithms for the solution of specific mathematical problems
- the ability of implementing at the computer the algorithms for solving specific numerical problems
- the ability of analyzing critically and independently the acquired knowledge
Course unit contents: Introduction to Numerical Analysis: problem definition, computer representation, stability and ill-conditioning. Introduction to Numerical Programming: principles, use of the Matlab language. Solution to linear systems: direct (Gauss elimination, triangular factorization) and iterative (Jacobi, Seidel) methods. Solution to non-linear systems: bisection, fixed point iteration, Newton-Raphson, Regula Falsi. Data interpolation and approximation: Lagrange polynomial, Newton differences, least square approximation. Numerical quadrature: Newton-Cotes and Gauss formulas. Numerical integration of ordinary differential equations (hints).
Planned learning activities and teaching methods: Lectures and practical exercises for numerical programming in the computer science lab.
During the lectures, the course topics are discussed. The theory is enriched by several exercises.
Lectures in the computer room consist of two parts: (1) theory by the professor; (b) practical exercises taken independently by the student under the professor supervision.
Additional notes about suggested reading: Reference textbook and lecture notes.
Textbooks (and optional supplementary readings)
  • G. Gambolati, M. Ferronato, Lezioni di Metodi Numerici per l'Ingegneria. Seconda Edizione.. Padova: Libreria Progetto, 2017. Cerca nel catalogo
  • A. Mazzia, Laboratorio di Calcolo Numerico. Milano-Torino: Pearson Italia, 2014. Cerca nel catalogo