Course syllabus - Numerical methods with MATLAB
Scope
7.5 credits
Course code
MAA069
Valid from
Autumn semester 2026
Education level
First cycle
Progressive Specialisation
G1F (First cycle, has less than 60 credits in first-cycle course/s as entry requirements)
Main area(s)
Mathematics/Applied Mathematics
Organisation
Department of Business and Mathematics
Ratified
2024-12-10
Revised
2025-11-03
Literature lists
Course literature is preliminary up to 8 weeks before course start. Course literature can be valid over several semesters.
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Books
Miscellaneous texts
Additional lecture notes will be used in the course.
Objectives
The aim of the course is to provide knowledge about how numerical methods are applied when solving mathematical problems that are frequently occurring in natural and engineering sciences. These mathematical challenges are often very complex and cannot be treated analytically. To bypass the analytical restrictions, one resorts to numerical methods. The course focuses on development of introductory numerical methods and implementation of these algorithms using the software package MATLAB.
Learning outcomes
At the end of the course the student is expected to be able to
- explain the basics of computer arithmetic, for example machine precision and rounding errors
- approximate derivatives using various finite differences
- use numerical methods, like bisection or Newton's method, to solve nonlinear equations
- apply curve fitting to a given set of data points
- construct interpolation polynomials with specified properties
- approximate integrals numerically using quadratures
- solve ordinary differential equations numerically using explicit and implicit Runge-Kutta methods
- analyze and verify accuracy and stability properties of the studied methods
- implement, in MATLAB, numerical methods covered in the course for solving different mathematical problems
- compose structured reports while clearly presenting problem statement, methodology, analysis and assessment of results
Course content
- Introduction to MATLAB, basic programming algorithms and their implementation in MATLAB
- Basics of computer arithmetic (e.g. machine precision and rounding errors)
- Numerical approximation of derivatives using finite differences
- Numerical methods for solving nonlinear equations (e.g. bisection and Newton's method)
- Curve fitting using the least squares method
- Interpolation
- Numerical methods for approximating integrals
- Numerical methods for ordinary differential equations (explicit and implicit Runge-Kutta methods)
Specific requirements
Basic Calculus, 7.5 credits, and Basic Vector Algebra, 7.5 credits, or equivalent.
Examination
TEN1, Written examination, 5 credits, individual written examination concerning learning outcomes 1-8, grades Fail (U), 3, 4, 5.
LAB1, Laboratory work, 2.5 credits, individual and/or group laboratory work concerning learning outcomes 1-10, grades Fail (U) or Pass (G).
There may also be optional assignments that give bonus points for the examinations above. See more information in the study guide.
A student who has a certificate from MDU regarding disability study support, can request adaptions for the examination. It is the examiner who takes decisions on any adaptions, based on the certificate and other conditions.
Grade
Grading scale: 5, 4, 3
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