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SF1514 Numerical Methods, Basic Course 6.0 credits

Information per course offering

Termin

Information for Autumn 2024 Start 26 Aug 2024 programme students

Course location

KTH Campus

Duration
26 Aug 2024 - 13 Jan 2025
Periods
P1 (3.0 hp), P2 (3.0 hp)
Pace of study

17%

Application code

50632

Form of study

Normal Daytime

Language of instruction

Swedish

Course memo
Course memo is not published
Number of places

Places are not limited

Target group

Only CMAST2, CLGYM3

Planned modular schedule
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Contact

Examiner
No information inserted
Course coordinator
No information inserted
Teachers
No information inserted
Contact

Christina Marianne Carlsund Levin (ninni@kth.se)

Course syllabus as PDF

Please note: all information from the Course syllabus is available on this page in an accessible format.

Course syllabus SF1514 (Autumn 2019–)
Headings with content from the Course syllabus SF1514 (Autumn 2019–) are denoted with an asterisk ( )

Content and learning outcomes

Course contents

Basic ideas and concepts: algorithm, computational cost, local linearisation, iteration, recursion, interpolation, extrapolation, discretisation, convergence, stability, condition.

Estimation of reliability: parameter sensitivity, perturbation calculation.

Numerical methods: linear and non-linear systems of equations, differential equations: initial-value problems and boundary value problems, curve fitting: interpolation and the least squares method.

Intended learning outcomes

A general aim with the course is to give the student the understanding that numerical methods and programming techniques are needed to make reliable and efficient simulations of technical and scientific processes based on mathematical models.

  • For a general formulation of a technical or scientific problem: be able to identify and classify the mathematical subproblems that need to be solved, and reformulate them to be suitable for numerical treatment.

  • Be able to choose, apply and implement numerical methods to produce a solution to a given problem.

  • Be able to use concepts in numerical analysis to describe, characterize and analyze numerical methods and estimate the reliability of numerical results.

  • Be able to clearly present problem statements, solution approaches and results.

Literature and preparations

Specific prerequisites

Completed course SF1625 Calculus in one variable or SF1673 Analysis in one variable.

Completed course DD1312 Programming Techniques and Matlab or similar.

Recommended prerequisites

SF1624 Algebra and Geometry, SF1626 Calculus in Several Variable

Equipment

No information inserted

Literature

Announced no later than 4 weeks before the start of the course on the course web page.

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

  • LABA - Laboratory Work, 1.5 credits, grading scale: P, F
  • LABB - Laboratory Work, 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, the code of honour of the school is applied, see: http://www.sci.kth.se/institutioner/math/avd/na/utbildning/hederskodex-for-studenter-och-larare-vid-kurser-pa-avdelningen-for-numerisk-analys-1.357185

The examiner decides, in consultation with KTHs Coordinator of students with disabilities (Funka), about any customized examination for students with documented, lasting disability. 

Opportunity to complete the requirements via supplementary examination

No information inserted

Opportunity to raise an approved grade via renewed examination

No information inserted

Examiner

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, SF2520 Applied Numerical Methods. 

Contact

Christina Marianne Carlsund Levin (ninni@kth.se)