Numerical Methods

Vrije Universiteit Amsterdam

Course Description

  • Course Name

    Numerical Methods

  • Host University

    Vrije Universiteit Amsterdam

  • Location

    Amsterdam, The Netherlands

  • Area of Study

    Mathematics

  • Language Level

    Taught In English

  • Course Level Recommendations

    Upper

    ISA offers course level recommendations in an effort to facilitate the determination of course levels by credential evaluators.We advice each institution to have their own credentials evaluator make the final decision regrading course levels.

    Hours & Credits

  • ECTS Credits

    6
  • Recommended U.S. Semester Credits
    3
  • Recommended U.S. Quarter Units
    4
  • Overview

    COURSE OBJECTIVE
    At the end of this course students will be able to ...
    ... implement the main algorithms of numerical analysis correctly and efficiently in Matlab.
    ... perform numerical calculations to solve nonlinear algebraic problems, eigenvalue problems, interpolation problems, signal processing
    and ODEs.
    ... apply methods from numerical analysis in a scientific setting.
    ... evaluate the reliability of numerical methods.
    ... report comprehensively on the structure of her/his algorithms as well as the computations performed using her/his code.

    COURSE CONTENT

    Numerical methods are used frequently in all areas of science, such as fluid dynamics, meteorology and financial risk management. Moreover, techniques from numerical analysis play an important role in mathematical research on differential equations, stochastics,
    optimization, etcetera. We focus on the main numerical methods from modern-day analysis and scientific computing.

    The list of subjects includes:
    * error analysis
    * systems of nonlinear equations
    * eigenvalue problems
    * least square methods
    * fast Fourier transform
    * ordinary (and partial) differential equations (no prerequisites
    needed)

    Applications include
    * phone number recognition
    * Google/Page rank algorithm
    * data analysis
    * curve following
    * planet motions
    * and more.

    TEACHING METHODS
    Lectures (once a week, 1x2=2 hours) and computer labs (once a week, 1x2=2 hours). A number of Matlab assignments form an integral part of the course.

    TYPE OF ASSESSMENT
    The final grade is based on a set of reports and computer codes that have to be handed in. In 2017/18 the weights were as listed below, but these may be revised for 2018/19. Precise details will be available on Canvas at the start of the course.

    First assignment; two exercises [2 x 4.5 = 9%]
    Second assignment; two exercises [2 x 5.5 = 11%]
    Third assignment; three exercises [3 x 6.5 = 19.5%]
    Fourth assignment; two exercises [2 x 8 = 16%]
    Fifth assignment; two exercises [2 x 8 = 16%]
    Sixth assignment; three exercises [3 x 9.5 = 28.5%]

    ENTRY REQUIREMENTS
    A basic course in Linear algebra (e.g. X_400041, X_400042, X_400638 or X_400639) and Multivariable calculus (e.g. XB_41008).

Course Disclaimer

Courses and course hours of instruction are subject to change.

Some courses may require additional fees.

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