•      About OUHK     

  •      Admissions     

  •      Academics     

  •     Administration    

  •      Library     

  •     Research    

  • Registration

    MATH S811F
    Computer Algebra and Simulations
    MATH S811F
    Computer Algebra and Simulations
    Course Start Date
    Aut 2021
    Course Level
    Length in Terms
    2 terms
    Fees ($) (including lab fees)
    Future Terms
    Aut 2022
    Quota and Schedule
    Start Date
    Course Level Length in Terms Credits
    Fees ($)
    (including lab fees)
    Future Terms
    Aut 2021
    Postgraduate 2 terms 10
    Aut 2022

    Course Coordinator: Dr Tony M T Chan, Grad Dip, MPhil (CUHK); PhD (CityU)

    Important note
    This course will be taught through a part-time face-to-face mode. The course will be presented in English. Lectures and tutorials will be scheduled on either weekday evenings, or on Saturdays or Sundays.

    MATH S811F is one of the core courses in the Master of Science in Quantitative Analysis and Computational Mathematics. It is also one of the courses in the Postgraduate Diploma in Quantitative Analysis and Computational Mathematics, and the Postgraduate Certificate in Computational Mathematics.

    The course aims to help students develop an understanding of the concepts of computer algebra and its applications in the fields of science, business, financial engineering, etc. Students will learn both the theoretical basis for these methods and how to apply them.

    Advisory prerequisite(s)
    You are advised to have some background knowledge in mathematics and quantitative science, computing or a related discipline.

    This course aims to:

    • Develop students' mathematical understanding of the numerical methods used in linear algebra;

    • Enable students to apply the efficiency and stability of algorithms in numerical linear algebra to various applications;

    • Teach various Monte Carlo techniques, such as generation of random variables, stochastic processes, Monte Carlo integration and correlated sampling;

    • Prepare students to write program code and choose a generator, or pseudo-random or quasi-random sequences;

    • Demonstrate the applicability of Monte Carlo simulation methods to scientific, project management, financial engineering and transportation applications.

    The course will cover the following topics:

    • Introduction to symbolic computing software

    • Computer algebra with applications

    • Case studies and applications using computing algebra

    • Random processes and Monte Carlo simulations

    • The computer simulation approach

    • Modelling systems with Monte Carlo simulations

    Learning support
    There will be regular face-to-face lectures and tutorials throughout the course.

    Course assessment
    Course assessment will be divided into continuous assessment (50%) and a final examination (50%). The continuous assessment portion will include four assignments (from which the best three scores will be used to determine the final grade). A final examination lasting three hours will be conducted at the end of the course. Students are required to submit assignments via the Online Learning Environment (OLE).

    Online requirement
    This course is supported by the Online Learning Environment (OLE). You can find the latest course information from the OLE. Through the OLE, you can communicate electronically with your lecturer as well as other students. To access the OLE, you will need to have access to the Internet. The use of the OLE is required for the study of this course.

    Students will need access to a computer system suitable for connecting to the Internet. The recommended minimum computing requirements are:

    • Pentium IV CPU

    • SVGA display card and monitor

    • 1 GB RAM

    • 500 MB free hard disk space

    • Broadband Internet access

    Set book(s)
    There are no set books for this course. The following books will be the main references of study:

    Kroese, D P, Taimre, T and Botev, Z I (2011) Handbook of Monte Carlo Methods, Wiley.

    Rubinstein, R Y and Kroese, D P (2008) Simulation and the Monte Carlo Method, 2nd edn, Wiley.

    Trefethen, L N and Bau, D (1997) Numerical Linear Algebra, Philadelphia: Society for Industrial and Applied Mathematics.

    Accessibility | Privacy policies | Policy on Equal Opportunities | Terms and policies | Webmaster
    © 2022 by The Open University of Hong Kong. All Rights Reserved.
    Site Map Site map
    About OUHK
    President's Message
    Vision & Mission
    Strategic Plan
    Governance & Organization
    Principal Officers
    Honorary Graduates & University Fellows
    Facts & Figures
    School of Arts and Social Sciences
    Lee Shau Kee School of Business and Administration
    School of Education and Languages
    School of Nursing and Health Studies
    School of Science and Technology
    Li Ka Shing School of Professional and Continuing Education (LiPACE)
    Office for Advancement of Learning and Teaching
    Finance and Facilities Management Unit
    Human Resources Unit
    Information Technology Unit
    Mainland and International Affairs Office
    OUHK Shenzhen Office
    Public Affairs Unit
    Quality Assurance Office
    Research Office
    Student Affairs Office
    Research Postgraduate Programmes
    Postgraduate Programmes
    Postgraduate Programmes (Part-time)
    Undergraduate Programmes
    Undergraduate Programmes (Part-time)
    Sub-degree Programmes
    Sub-degree Programmes (Part-time)
    Continuing Professional Development (CPD) Programmes
    Programmes from LiPACE
    Annual Review 2017-2018
    Choose your study programme
    Events Calendar
    Giving to OUHK
    Information for
    Prospective Students
    Current Students
    Jockey Club Home Health Watch Programme
    Media coverage
    Motto: Disce, Progredere, Crea
    Open Learning Resources
    iTunes U
    Knowledge for All
    OUHK Great Speakers Series
    Privacy policies
    Terms and policies
    Research Office (RO)
    RGC Funded Projects
    Institutional Repository
    Other Funded Research Projects
    Staff Publications
    Research Degree Programmes
    External Research Funding
    Internal Research Funding
    External Funding for Development Project
    Site Search
    Social Media
    YouTube Channel
    Student Life & Support
    Students' Achievements
    Switch on to e-materials
    Useful Information
    Adverse weather arrangements
    Campus location
    Job Openings
    Contact us
    Telephone: (852-2711-2100)
    Facsimile: (852-2715-0760)
    Email: info@ouhk.edu.hk
    View the videos of Full-time Face-to-face Undergraduate Programme selected seminars
    Web for All
    Back To Top