This module explicitly focuses on significant elements required for the achievement of the STAFFORDSHIRE GRADUATE ATTRIBUTES.

The mathematical content consists of a taught and a research/investigation element.

1) The taught part of the course will give a revision of the fundamental concepts of mathematics applicable to computing.
- Propositional Logic - The basics and operators, truth tables, equivalence, valid arguments.
- Matrices - The basics and operators, inverse of 2 x 2 matrix, solving systems of linear equations, linear transformations in 2 dimensions.
- Elements of Set Theory - The basics concept and operators, Venn diagrams, the concept of a function and inverse functions for simple polynomials.
- Functions - an introduction to low order polynomial, logarithmic, exponential, and trigonometric functions. Solving simple equations involving these functions.
- Probability - Rules of probability, Probability trees, Conditional Probability.
- Descriptive Statistics - tabulating and charting data, averages, measures of spread.
- Introduction to graph theory - The basics, trees, least weight spanning tree, least weight path between two points, tree traversal.
- Introduction to principles of computational modelling.

All of the above will be illustrated throughout with relevant examples of application to computing.

2) The investigation element. You will select a topic with agreement of a tutor and conduct a critical review and investigation into the application and applicability of some mathematical concept(s) or principle(s) to an area of computing that lies within the subject domain of your award discipline. The concept may be one covered in the revision above or it may be different.

Data analytic content:
- Knowledge management concepts
- Analysis Services/Business Reporting in an OR environment
- Implementation issues and technologies for non standard data, large Data sets, document handling (NoSQL)
- Data quality and reporting
- Data visualisation and analysis

- Data Mining applications & algorithms
- Data warehousing - design , implementation and querying
- Data cleansing, ETL, treatment of outliers Data Marts

Assessment point 1 - Maths assessment.
A REPORT length 2400 WORDS weighted at 40%. (learning outcomes 5-7)

Assessment is to include both a formative and summative component

Summative:
40% 2400-word in-depth report providing a critical review of the application of mathematical concepts within their chosen domain of investigation (related to their award subject area)
(Learning outcomes 5-7)

Additional Details. The summative report will only be considered for marking if the formative portfolio of tests have been completed to a satisfactory level.

Formative: series of 3/4 tests that assess understanding from the 'taught' part of the course.

Assignment 60% consisting of:
Assessment point 2 weighted at 40% Creation, demonstration and justification of an Analysis and Reporting Artefact (learning outcomes 1, 2 & 3)
Assessment point 3 weighted at 20% Research Portfolio (learning outcome 4). Final assessment.

Students enrolled on the Computing Science Top Up award

Database Systems 5th Edition Connolly T, Begg C (2009) International Computer Science Series ISBN 0321173503
Big Data, Big Analytics: Emerging Business Intelligence and Analytic Trends for Today's Businesses Minelli M, Chambers M, Dhiraj A (2013) Wiley ISBN 9781118147603
Foundation Mathematics, K. A. Stroud & D. J. Book, Palgrave Macmillan, 2009, ISBN-10: 0230579078, ISBN-13: 978-0230579071

Mathematics in Computing: An Accessible Guide to Historical, Foundational and Application Contexts, O'Regan, 2012, Springer, ISBN-13: 978-1447145332.

Modelling Computing Systems: Mathematics for Computer Science (Undergraduate Topics in Computer Science), Moller, F. and Georg Struth, 2013, Springer, ISBN-13: 978-1848003217

ArgoUML
Weka Data mining tool or equivalent
Oracle 11g (with data warehouse module) or higher
SQL Server Enterprise with Business Analytics 2008 or higher
MongoDB

26 lectures and 13 practicals. Concepts will be introduced through lectures and through prescribed reading and independent study exercises. Theoretical material will be supported by practical sessions which will give students hands on experience with established and emerging technologies. The module uses an enquiry based approach which facilitates students researching and exploring material for themselves and introduces them to new approaches in data management The mathematical revision material will be supported by the VLE and students will work through the module material at a pace suggested within the VLE for the module. Weekly surgery sessions will be provided to help students who have difficulties with specific aspects of the revision material.