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DN1243 Computer Science and Numerical Methods, Part 2 7.5 credits

Datalogi och numeriska metoder, del 2

Basic course i numerical methods and computer applications.

  • Educational level

    First cycle

  • Academic level (A-D)

    A

  • Subject area

    Techonology

  • Grade scale

    A, B, C, D, E, FX, F

Course offerings

Autumn 12 CELTE for programme students

  • Periods

    Autumn 12 P1 (3.7 credits), P2 (3.8 credits)

  • Application code

    50057

  • Start date

    2012 week: 34

  • End date

    2013 week: 1

  • Language of instruction

    Swedish

  • Campus

    KTH Campus

  • Number of lectures

  • Number of exercises

  • Tutoring time

    Daytime

  • Form of study

    Normal

  • Number of places

    No limitation

  • Schedule

    Schedule (new window)

  • Target group

    Compulsary for CELTE2 but available for all programs

  • Part of programme

Learning outcomes

An overlying goal with the course is the realization of the necessity of numerical methods in order to simulate technological and scientific processes based on mathematical models.

After completing this course, the students should be able to

  • identify various mathematical problems and reformulate these in a way suitable for numerical treatment
  • select a suitable numerical method for the treatment of the given problem
  • motivate the choice of a method by describing its advantages and limitations
  • select an algorithm leading to efficient computation and implement this in a programming language, suitable for scientific computing, e.g. Matlab
  • provide an estimate of the accuracy of the results
  • utilize standard functions from e.g. Matlab's library for calculation, visualization and efficient programming
  • apply computer science for solving practical problems.

Course main content

Basic concepts and ideas: algorithm, local linearization, iteration, extrapolation, discretization, convergence, stability, condition.

Reliability assessment: parameter sensitivity, experimental perturbations, precision.

Numerical methods for: linear systems of equations, nonlinear equations and systems of equations, interpolation, model-fitting with the method of least squares, optimization, quadrature, differential equations.

The application of mathematical software in the solution of scientific and engineering problems, numerical experimentation, and the presentation of effective algorithms.

Disposition

Lectures: 30 h
Tutorials: 15 h
Laboratory assignments: 22 h

Eligibility

Prerequisites

Mandatory first year courses in mathematics and a course in computer science or programming.

Literature

G Eriksson: Numeriska algoritmer med Matlab, CSC/Nada 2002.

Examination

  • LAB1 - Laboratory Work, 1.5 credits, grade scale: P, F
  • LAB2 - Laboratory Work, 3.0 credits, grade scale: P, F
  • TEN1 - Examination, 3.0 credits, grade scale: A, B, C, D, E, FX, F

In this course all the regulations of the code of honor at the School of Computer science and Communication apply, see: http://www.kth.se/csc/student/hederskodex/1.17237?l=en_UK.

Requirements for final grade

Examination (TEN1; 3 cr)
Laboratory assignments (LAB1; 1,5 cr)
Individual programming task (LAB2; 3 cr)

Offered by

SCI/Mathematics

Contact

Lennart Edsberg, e-post: edsberg@kth.se

Examiner

Hans Lennart Edsberg <edsberg@kth.se>

Supplementary information

In this course all the regulations of the code of honor at the School of Computer science and Communication apply, see: http://www.kth.se/csc/student/hederskodex/1.17237?l=en_UK.

Add-on studies

DD1332 Object Oriented Programming, DD1347 Project in Computer Science, DD2310 Java Programming for Python Programmers, DN2220 Applied Numerical Methods I, DN2225 Numerical Solutions of Differential Equations and others.

Version

Course plan valid from: Autumn 09.
Examination information valid from: Autumn 08.