THE UNIVERSITY of EDINBURGH

DEGREE REGULATIONS & PROGRAMMES OF STUDY 2020/2021

Information in the Degree Programme Tables may still be subject to change in response to Covid-19

University Homepage
DRPS Homepage
DRPS Search
DRPS Contact
DRPS : Course Catalogue : School of Mathematics : Mathematics

Undergraduate Course: Computing and Numerics (MATH08065)

Course Outline
SchoolSchool of Mathematics CollegeCollege of Science and Engineering
Credit level (Normal year taken)SCQF Level 8 (Year 2 Undergraduate) AvailabilityAvailable to all students
SCQF Credits10 ECTS Credits5
SummaryThis course introduces numerical methods, which are now an essential component in a diverse range of disciplines.
Course description The course will cover:
- Creation and manipulation of arrays
- Solutions of linear systems
- Gaussian elimination with partial pivoting
- Numerical differentiation and integration
- Introductory numerical differential equations
- Root finding methods, including bisection and fixed-point iteration
- Newton's method in one and higher dimensions
- Functional minimization in multiple dimensions

Within these topics students will be introduced to:
- Variables and functions
- Floating point arithmetic
- Flow control
- Container types
- Plotting
- Symbolic expressions
Entry Requirements (not applicable to Visiting Students)
Pre-requisites Students MUST have passed: ( Introduction to Linear Algebra (MATH08057) AND Several Variable Calculus and Differential Equations (MATH08063)) OR ( Accelerated Algebra and Calculus for Direct Entry (MATH08062) AND Introductory Dynamics (PHYS08052)) OR ( Several Variable Calculus and Differential Equations (MATH08063) AND Accelerated Algebra and Calculus for Direct Entry (MATH08062))
Co-requisites
Prohibited Combinations Other requirements None
Information for Visiting Students
Pre-requisitesVisiting students are advised to check that they have studied the material covered in the syllabus of each prerequisite course before enrolling
High Demand Course? Yes
Course Delivery Information
Academic year 2020/21, Available to all students (SV1) Quota:  None
Course Start Semester 2
Timetable Timetable
Learning and Teaching activities (Further Info) Total Hours: 100 ( Lecture Hours 11, Supervised Practical/Workshop/Studio Hours 22, Programme Level Learning and Teaching Hours 2, Directed Learning and Independent Learning Hours 65 )
Assessment (Further Info) Written Exam 0 %, Coursework 100 %, Practical Exam 0 %
Additional Information (Assessment) Coursework 100%
Feedback Not entered
No Exam Information
Learning Outcomes
On completion of this course, the student will be able to:
  1. Write short programs in a professional way using Python, employing suitable tools and writing well-formatted code.
  2. Explain the purpose and logic of some basic numerical algorithms;
  3. Use a suitable programming language to investigate mathematical phenomena, to make conjectures, find counterexamples, etc;
Reading List
S. Linge and H. P. Langtangen, Programming for Computations Python, Springer, 2016

P.R. Turner, T. Arildsen, and K. Kavanagh, Applied Scientific Computing with Python, Springer, 2018
Additional Information
Graduate Attributes and Skills Not entered
KeywordsCNu
Contacts
Course organiserDr Charlotte Desvages
Tel: (0131 6)50 5051
Email: Charlotte.Desvages@ed.ac.uk
Course secretaryMr Martin Delaney
Tel: (0131 6)50 6427
Email: Martin.Delaney@ed.ac.uk
Navigation
Help & Information
Home
Introduction
Glossary
Search DPTs and Courses
Regulations
Regulations
Degree Programmes
Introduction
Browse DPTs
Courses
Introduction
Humanities and Social Science
Science and Engineering
Medicine and Veterinary Medicine
Other Information
Combined Course Timetable
Prospectuses
Important Information