MA1MPRNU-Mathematical Programming

Module Provider: Mathematics and Statistics
Number of credits: 10 [5 ECTS credits]
Level:4
Terms in which taught: Spring term module
Pre-requisites:
Non-modular pre-requisites:
Co-requisites:
Modules excluded:
Current from: 2021/2

Module Convenor: Dr Peter Sweby
Email: p.k.sweby@reading.ac.uk

Type of module:

Summary module description:

This module introduces students to the valuable skill of programming with clear links to applications in mathematics. Programming concepts will be taught in the context of the MATLAB programming language but are applicable to other programming languages. Examples from other mathematics modules taken will be used to illustrate various programming techniques.

The Module lead at NUIST is Dr Raul Sanchez Galan.

Aims:

• To develop basic and intermediate programming skills in the context of other modules being taken or having been taken in Part 1;


• To introduce the concepts of program design;


• To introduce computer programming languages relevant to mathematics; namely, MATLAB;


• To introduce good programming practice in the structure, maintenance and in-program documentation of the code;


• To be able to display results visually using graphics capabilities of the languages;


• By the end of the module students should be able to dissect a given problem into an algorithm suitable for programming in languages such as MATLAB

Assessable learning outcomes:

• Students will be able to demonstrate the ability to transfer mathematical problems into programs in computer languages such as MATLAB;


• Students will be able to demonstrate good programming practice in structure, maintenance and documentation of code;


• Student will be able to display results visually using graphics capabilities of the languages;


• Students will be able to formulate simple real-world problems into computer programs and f ind the numerical solutions accordingly;


• Students will be able to appreciate and analyse the errors in the numerical outputs of their programs by comparing with exact solutions.

Additional outcomes:

• Students will further develop their transferable skills in the area of programming for the mathematical sciences;


• This module will support the learning process in other mathematical modules;


• Students will have a basic knowledge of Python and its library NumPy.

Outline content:

• An introduction to the concept of programming, including top-down design


• Various mathematical concepts will be analysed and appropriate programming techniques applied to facilitate solution and understanding


• The MATLAB programming languages will be introduced, in which developed algorithms will be implemented.

Brief description of teaching and learning methods:

Lectures, computer labs, self-guided study as well as summative and formative assignments. Worksheets and self- evaluation /feedback mechanisms.

Contact hours:

Ìý	Autumn	Spring	Summer
Lectures		8
Practicals classes and workshops		24
Guided independent study:	Ìý	Ìý	Ìý
Ìý Ìý Wider reading (independent)		24
Ìý Ìý Wider reading (directed)		10
Ìý Ìý Exam revision/preparation		24
Ìý Ìý Completion of formative assessment tasks		10
Ìý	Ìý	Ìý	Ìý
Total hours by term	0	100	0
Ìý	Ìý	Ìý	Ìý
Total hours for module	100

Summative Assessment Methods:

Method	Percentage
Set exercise	100

Summative assessment- Examinations:

Summative assessment- Coursework and in-class tests:

A number of programming assignments during the term.

Formative assessment methods:

A number of non-assessed programming exercises and worksheets to illustrate the material being taught, resulting in detailed feedback to enhance programming skills.

Penalties for late submission:

The Support Centres will apply the following penalties for work submitted late:

• where the piece of work is submitted after the original deadline (or any formally agreed extension to the deadline): 10% of the total marks available for that piece of work will be deducted from the mark for each working day (or part thereof) following the deadline up to a total of five working days;
• where the piece of work is submitted more than five working days after the original deadline (or any formally agreed extension to the deadline): a mark of zero will be recorded.

The University policy statement on penalties for late submission can be found at:
You are strongly advised to ensure that coursework is submitted by the relevant deadline. You should note that it is advisable to submit work in an unfinished state rather than to fail to submit any work.

Assessment requirements for a pass:

A mark of 40% overall.

Reassessment arrangements:

Alternative course work.

Additional Costs (specified where applicable):

Last updated: 8 April 2021