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DEGREE REGULATIONS & PROGRAMMES OF STUDY 2022/2023

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DRPS : Course Catalogue : School of Mathematics : Mathematics

Postgraduate Course: MIGS: Numerical Methods (MATH11212)

Course Outline
SchoolSchool of Mathematics CollegeCollege of Science and Engineering
Credit level (Normal year taken)SCQF Level 11 (Postgraduate) AvailabilityNot available to visiting students
SCQF Credits15 ECTS Credits7.5
SummaryIn applied mathematics, physical and other problems are often modelled by differential equations. It is extremely rare that one can obtain exact solutions to the differential equations that may occur in, for example, fluid dynamics, mathematical biology or magnetohydrodynamics. Additionally, the problems may involve the evaluation of integrals which arise, for example, through contour integration or Fourier or Laplace transform methods for solving ODEs. Thus, in many cases we are forced to employ some kind of approximation in order to make progress with our problem. Hence, we must obtain an approximate solution rather than the exact solution.

In essence there are two main types of approximation: analytical approximations and numerical approximations. This module deals with the second type; the Asymptotic and Analytical Methods module deals with the first.
Course description The aim is to learn new things to get a broad education in the area as a basis for a wide range of PhD projects and for post-PhD employment. Unless otherwise noted, the details of the content of these courses can be found on the Scottish Mathematical Sciences Training Centre web site www.smstc.ac.uk
Entry Requirements (not applicable to Visiting Students)
Pre-requisites Co-requisites
Prohibited Combinations Other requirements None
Course Delivery Information
Academic year 2022/23, Not available to visiting students (SS1) Quota:  None
Course Start Semester 2
Timetable Timetable
Learning and Teaching activities (Further Info) Total Hours: 150 ( Lecture Hours 20, Programme Level Learning and Teaching Hours 3, Directed Learning and Independent Learning Hours 127 )
Assessment (Further Info) Written Exam 0 %, Coursework 100 %, Practical Exam 0 %
Additional Information (Assessment) 100% coursework
Feedback Not entered
No Exam Information
Learning Outcomes
On completion of this course, the student will be able to:
  1. Understand the different techniques available to solve differential equations, including applications to optimization.
  2. Demonstrate familiarity with the resolution of initial and boundary value problems using numerical methods.
Reading List
None
Additional Information
Graduate Attributes and Skills Not entered
KeywordsNot entered
Contacts
Course organiserProf Benedict Leimkuhler
Tel:
Email: B.Leimkuhler@ed.ac.uk
Course secretaryMrs Katy Cameron
Tel: (0131 6)50 5085
Email: Katy.Cameron@ed.ac.uk
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