Course content

Error analysis. Polynomial interpolation, splines and approximation. Numerical quadrature. Numerical solution of ordinary differential equations. Linear and nonlinear equations.

Learning outcome

1. Knowledge. The student has knowledge of basic numerical methods for approximation of functions, numerical quadrature, numerical solution of ordinary differential equations, and numerical solution of linear and nonlinear equations. The student masters error analysis of numerical methods and understands the concepts stability and convergence.

2. Skills. The student masters basic techniques for analyzing a large selection of numerical algorithms. The student is able to implement the algorithms in a chosen programming language, set up numerical experiments and interpret the results. The student has established sound routines for quality assurance in implemented algorithms.


3. General competence. The student can describe the chosen scientific method and communicate his or her findings in a written scientific report using precise language.

Learning methods and activities

Lectures and exercises. The exercises demand the use of a computer. Portfolio assessment is the basis for the grade awarded in the course. This portfolio comprises a written final examination (70%) and a term project (30%). The results for the constituent parts are to be given in %-points, while the grade for the whole portfolio (course grade) is given by the letter grading system. Retake of examination may be given as an oral examination. All teaching materials are available in English. The lectures will be given in English if they are attended by students from the Master's Programme in Mathematics for International students. Students are free to choose Norwegian or English for written assessments.

Compulsory assignments

• Exercises

Recommended previous knowledge

TMA4100/05/15/20, Calculus 1/2/3/4K. Some programming experience.

Course materials

Will be announced at the start of the course.

Credit reductions