Undergraduate Course: Computing and Numerics (MATH08065)
Course Outline
School | School of Mathematics |
College | College of Science and Engineering |
Credit level (Normal year taken) | SCQF Level 8 (Year 2 Undergraduate) |
Availability | Available to all students |
SCQF Credits | 10 |
ECTS Credits | 5 |
Summary | This 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
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Information for Visiting Students
Pre-requisites | Visiting 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
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Academic year 2020/21, Available to all students (SV1)
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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 )
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Assessment (Further Info) |
Written Exam
0 %,
Coursework
100 %,
Practical Exam
0 %
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Additional Information (Assessment) |
Coursework 100% |
Feedback |
Not entered |
No Exam Information |
Learning Outcomes
On completion of this course, the student will be able to:
- Write short programs in a professional way using Python, employing suitable tools and writing well-formatted code.
- Explain the purpose and logic of some basic numerical algorithms;
- Use a suitable programming language to investigate mathematical phenomena, to make conjectures, find counterexamples, etc;
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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 |
Keywords | CNu |
Contacts
Course organiser | Dr Charlotte Desvages
Tel: (0131 6)50 5051
Email: Charlotte.Desvages@ed.ac.uk |
Course secretary | Mr Martin Delaney
Tel: (0131 6)50 6427
Email: Martin.Delaney@ed.ac.uk |
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