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.
SF1522 Numerical Computations 6.0 credits
Information per course offering
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]
- Schedule
- Part of programme
Contact
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–)Content and learning outcomes
Course contents
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
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
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
Opportunity to raise an approved grade via renewed examination
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
Offered by
Main field of study
Education cycle
Add-on studies
SF1523 Analytical and Numerical Methods for Differential Equations
DD1321 Applied Programming and Computer Science