Scientific Computing
Study plans 20162017

IMT3881
 10 ECTS
Prerequisite(s)
 TØL1001 Introduction to Engineering
 IMT1031 Fundamental Programming
 REA1141 Mathematics 1
 REA2091 Mathematics 2 for Computer Science or REA2081 Mathematics 2 for Electical Engineering
On the basis of
 IMT1082 ObjectOriented Programming
 IMT2021 Algorithmic Methods
 REA2101 Physics and Chemistry
Expected learning outcomes
After completing the course, the candidate will be able to
Knowledge:
 describe, explain and derive methods for numerical solution of selected problems
 assess which methods to use for solving a given problem, and analyse the accuracy of the methods
Skills:
 implement numerical algorithms in suitable highlevel languages
 apply highlevel languages for scientific computing
 apply numerical methods for solving practical problems
General competence:
 document methods and results from scientific computations in the form of technical reports, with suitable use of figures, tables, equations, cross references, and bibliography
Topic(s)
 Numerical solution of
 definite integrals
 ordinary differential equations and systems of such
 the diffusion equation
 nonlinear algebraic equations
 the method of least squares
 Highlevel scientific computing for
 visualisation of multidimensional data
 linear algebra
 optimisation
 statistics, combinatorics, and random numbers
 interpolation
 signal and image processing
 machine learning
Teaching Methods
Lectures
Mandatory assignments
Form(s) of Assessment
Written exam, 4 hours
Grading Scale
Alphabetical Scale, A(best) – F (fail)
External/internal examiner
Internal and external examiner.
Resit examination
Resit examination in August.
Tillatte hjelpemidler
Code D: No printed or handwritten support material is allowed. A specific basic calculator is allowed.
Read more about permitted examination aids.
Coursework Requirements
2 compulsory assignments
Teaching Materials
A. Tveito, H. P. Langtangen, B. F. Nielsen, X, Cai: Elements of Scientific Computing. Springer, 2010
EuroScipy tutorial team: Python Scientific lecture notes. http://scipylectures.github.com.