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DN1212 Numerical Methods and Basic Programming 9.0 credits

Course offerings are missing for current or upcoming semesters.
Headings with content from the Course syllabus DN1212 (Autumn 2009–) are denoted with an asterisk ( )

Content and learning outcomes

Course contents

Fundamental computer concepts. Programming in a modern programming language for scientific computations (Matlab). Use of a graphic library. Problem solving by subdivision of the problem. Program structuring. Use of mathematics software for solving technical-mathematical problems, doing numerical experiments and presenting solutions. Basic concepts and ideas in numerical analysis: algorithms, computational cost, local linearization, iteration, extrapolation, discretization, convergence, stability. Reliability assessment: parameter sensitivity, experimental perturburations. Numerical methods for linear and nonlinear systems of equations, integrals, differential equations, interpolation. Model fitting with the method of least squares.

Intended learning outcomes

An overlying goal of the course is the realisation of the necessity of numerical methods and programming techniques in order to simulate technological and scientific processes.

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 suitable programming language, e.g. Matlab
  • present the results in a relevant and illustrative way
  • provide an estimate of the accuracy of the results
  • break down larger problems into subproblems, and write user functions for these
  • utilize control- and datastructures
  • handle files in various formats, both for input and output
  • utilize standard functions from Matlab's library, for calculation, visualization and efficient programming
  • write well-structured programs in the programming language.

Literature and preparations

Specific prerequisites

No information inserted

Recommended prerequisites

Corresponding to courses in Linear algebra and and Differential calculus for functions in one variable. 

Equipment

No information inserted

Literature

To be announced at least 4 weeks before course start at course home page. Probably we will use P. Pohl: Grunderna i numeriska metoder, Teknisk Högskolelitt. S. Chapman: Matlab programming for engineers, Brooks/Cole, Thomson Learning. Material produced at the department.

Examination and completion

If the course is discontinued, students may request to be examined during the following two academic years.

Grading scale

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

Examination

  • LAB1 - Laboratory Works, 1.5 credits, grading scale: P, F
  • LAB2 - Laboratory Works, 1.5 credits, grading scale: P, F
  • LAB3 - Laboratory Works, 1.5 credits, grading scale: P, F
  • LAB4 - Laboratory Works, 1.5 credits, grading scale: P, F
  • TEN1 - Examination, 3.0 credits, grading scale: A, B, C, D, E, FX, F

Based on recommendation from KTH’s coordinator for disabilities, the examiner will decide how to adapt an examination for students with documented disability.

The examiner may apply another examination format when re-examining individual students.

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.

Other requirements for final grade

Examination (TENl; 3 university credits).
Laboratory work (LAB1; 1.5 university credits), (LAB2; 1,5 university credits), (LAB3; 1,5 university credits), (LAB4; 1,5 university credits).

Opportunity to complete the requirements via supplementary examination

No information inserted

Opportunity to raise an approved grade via renewed examination

No information inserted

Examiner

No information inserted

Ethical approach

  • All members of a group are responsible for the group's work.
  • In any assessment, every student shall honestly disclose any help received and sources used.
  • In an oral assessment, every student shall be able to present and answer questions about the entire assignment and solution.

Further information

Course room in Canvas

Registered students find further information about the implementation of the course in the course room in Canvas. A link to the course room can be found under the tab Studies in the Personal menu at the start of the course.

Offered by

Main field of study

Technology

Education cycle

First cycle

Add-on studies

DD1321 Applied Programming and Computer Science and DN2221 Applied Numerical Methods, part 1.

Contact

Katarina Gustavsson (katg@kth.se)

Supplementary information

Only one of the following courses can be counted in your degree: DD100N, DD1310, DD1311, DD1312, DD1314, DD1315, DD1340, DD1341, DD1342, DD1343, DD1345, DN1212, HI1024, HI1026, ID1004, ID1301.