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SF1522 Numerical Computations 6.0 credits

Information per course offering

Termin

Information for Autumn 2024 CDEPR1 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

51305

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 CDEPR1

Planned modular schedule
[object Object]

Contact

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

Course syllabus as PDF

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

Course syllabus SF1522 (Autumn 2019–)
Headings with content from the Course syllabus SF1522 (Autumn 2019–) are denoted with an asterisk ( )

Content and learning outcomes

Course contents

Basic computer concepts. Programming in a modern programming language for technical calculations (Matlab). Using graphical routines. Problem-solving through division into sub problems. Program structuring. Using mathematical software to solve engineering mathematical problems, make numerical experiments and present solutions. Basic ideas and concept within numerical methods: algorithms, computational cost, local linearisation, iteration, extrapolation, discretisation, convergence. Estimation of reliability: parameter sensitivity, experimental pertubation calculation. Numerical methods for linear systems of equations and non-linear equations, integrals, interpolation, 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.
  • Be able to use basic control and data structures of the programming language used in the course to solve problems.

Literature and preparations

Specific prerequisites

Basic requirements. 

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

  • LAB1 - Laboratory Works, 3.0 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

SF1523  Analytical and Numerical Methods for Differential Equations

DD1321 Applied Programming and Computer Science