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Content and learning outcomes
Basic computer concept. 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, stability. Estimation of reliability: parameter sensitivity, experimental pertubation calculation. Numerical methods for linear and non-linear systems of equations, integrals, differential equations, 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
Active participation in SF1625 Calculus in one variable.
Course in One Variable, corresponding to SF1625
Announced no later than 4 weeks before the start of the course on course homepage.
Examination and completion
If the course is discontinued, students may request to be examined during the following two academic years.
- LABA - Laboratory Works, 1.5 credits, grading scale: P, F
- LABB - Laboratory Works, 1.5 credits, grading scale: P, F
- LABC - Laboratory Works, 1.5 credits, grading scale: P, F
- LABD - 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, 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
- 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 about the course can be found on the Course web at the link below. Information on the Course web will later be moved to this site.Course web SF1516
Main field of study
DD1321 Applied Programming and Computer Science, SF2520 Applied Numerical Methods.