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2019/20 Undergraduate Module Catalogue

COMP2421 Numerical Computation

10 creditsClass Size: 250

Module manager: Professor Netta Cohen
Email: n.cohen@leeds.ac.uk

Taught: Semester 1 (Sep to Jan) View Timetable

Year running 2019/20

Pre-requisites

COMP1421Fundamental Mathematical Concepts
COMP1721Object Oriented Programming

This module is not approved as a discovery module

Module summary

Accuracy of floating-point computation. Standard numerical algorithms for linear equation systems, nonlinear equations, ordinary differential equations and data interpolation. The design of robust and efficient implementations in code.

Objectives

On completion of this module, students should be able to:
- Appreciate the role of numerical computation in computer science;
- Choose a computational algorithm appropriately, accounting for issues of accuracy, reliabilty and efficiency;
- Understand how to assess/measure the error in a numerical algorithm and be familar with how such errors are controlled;
- Implement simple numerical algorithms

Learning outcomes
On completion of the year/programme students should have provided evidence of being able to:
-demonstrate a broad understanding of the concepts, information, practical competencies and techniques which are standard features in a range of aspects of the discipline;
-apply generic and subject specific intellectual qualities to standard situations outside the context in which they were originally studied;
-appreciate and employ the main methods of enquiry in the subject and critically evaluate the appropriateness of different methods of enquiry;
-use a range of techniques to initiate and undertake the analysis of data and information;
-effectively communicate information, arguments and analysis in a variety of forms;


Syllabus

Approximation: converting a real-world problem, via a mathematical model, to a form which can be understood by a computer; discretising a continuous model; measuring, analysing and controlling approximation errors; balancing accuracy and efficiency. Static systems: simple iterative methods for solving nonlinear scalar equations; direct and iterative methods for solving linear systems of equations.
Evolving systems: differentiation as rate of change and as the limit of a gradient (including derivatives of simple functions); initial value ordinary differential equations, simple methods for initial value problems.

Teaching methods

Delivery typeNumberLength hoursStudent hours
Example Class101.0010.00
Lecture201.0020.00
Private study hours70.00
Total Contact hours30.00
Total hours (100hr per 10 credits)100.00

Opportunities for Formative Feedback

Coursework and tutorial / lab sessions.

Methods of assessment


Coursework
Assessment typeNotes% of formal assessment
AssignmentAssignment 110.00
AssignmentAssignment 210.00
Total percentage (Assessment Coursework)20.00

This module is re-assessed by exam only


Exams
Exam typeExam duration% of formal assessment
Standard exam (closed essays, MCQs etc)2 hr 00 mins80.00
Total percentage (Assessment Exams)80.00

This module is re-assessed by exam only

Reading list

The reading list is available from the Library website

Last updated: 30/04/2019

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