|Location||United Kingdom, London, Campus Cavendish|
|Type||Master courses, full-time|
|Nominal duration||1 year|
|Tuition fee||£13,500.00 per year|
Undergraduate diploma (or higher)
Suitable Honours degree from a UK university (or equivalent qualification) in a scientific or engineering discipline with some exposure to the use of IT, or in an area of computer science or IT with a strong interest in quantitative analysis
IELTS 6.5 with a minimum score of 6 in each element or TOEFL or CAE equivalent
At least 2 reference(s) must be provided.
This course addresses the need to propel information gathering and data organisation, and exploit potential information and knowledge hidden in routinely collected data to improve decision making. The course, which builds on the strengths of two successful courses on data mining and on decision sciences, is more technology focused, and stretches the datamining and decision-sciences theme to the broader agenda of business intelligence.
You will focus on developing solutions to real-world problems associated with the changing nature of IT infrastructure and increasing volumes of data, through the use of applications and case studies, while gaining a deep appreciation of the underlying models and techniques. You will also gain a greater understanding of the impact technological advances have on the nature and practices adopted within the business intelligence and analytics environments, and know how to adapt to these changes.
Embedded into the course are two key themes. The first will help you to develop your skills in the use and application of various technologies, architectures, techniques, tools and methods. These include data warehousing and data mining, distributed data management, and the technologies, architectures, and appropriate middleware and infrastructures supporting application layers. The second theme will enhance your knowledge of algorithms and the quantitative techniques suitable for analysing and mining data and developing decision models in a broad range of application areas. The project consolidates the taught subjects covered, while giving you the opportunity to pursue in-depth study in your chosen area.
Teaching approaches include lectures, tutorials, seminars and practical sessions. You will also learn through extensive coursework, class presentations, group research work, and the use of a range of industry standard software such as SAS, SPSS, iThink, Simul8, MS SQL Server 2005 Analysis Services, and Oracle Data Mining Suite. Taught modules may be assessed entirely through coursework, or may include a two-hour exam at the end of the year.
The module provides you with an in-depth analysis of the most practical topics in data mining and knowledge discovery, such as decision tree and other classification methods, association analysis, clustering and statistical mining.
The project module plays a unifying role and it aims to encourage and reward your individual inventiveness and application of effort. The scope of the project is not only to complete a well-defined piece of work in a professional manner, but also to place the work into the context of the current state of the art in business intelligence and/or analytics.
RESEARCH METHODS AND PROFESSIONAL PRACTICE
You will strengthen your skills for the research and industry needs of the course, the final project, and for your future career and study. The module guides your personal development plan towards the professional requirements of the discipline, and covers methods of critical evaluation, gathering and analysing information, and preparing and defending a project proposal.
STATISTICS AND OPERATIONAL RESEARCH
This is a self-contained module in applied statistics and operational research that lays the foundations for more advanced modules in data mining and analytics. You will cover topics such as hypothesis testing, regression, forecasting, linear programming and network modelling, and use software such as EXCEL Solver, SPSS, R, SAS, and AIMMS.
At Westminster, we have always believed that your University experience should be designed to enhance your professional life. Today’s organisations need graduates with both good degrees and employability skills, and we are committed to enhancing your graduate employability by ensuring that career development skills are embedded in all courses.
Opportunities for part-time work, placements and work-related learning activities are widely available, and can provide you with extra cash and help you to demonstrate that you have the skills employers are looking for. In London there is a plentiful supply of part-time work – most students at the University of Westminster work part time (or full time during vacations) to help support their studies.
We continue to widen and strengthen our links with employers, involving them in curriculum design and encouraging their participation in other aspects of career education and guidance. Staff take into account the latest data on labour market trends and employers’ requirements to continually improve the service delivered to students.