Big Data MSc
2017/18 New Entrants, Full Time
|Course start||January, September|
|Stoke-on-Trent Campus||Full-time||2017/18 Academic Year||Apply Direct|
|Stoke-on-Trent Campus||Full-time||2018/19 Academic Year||Apply Direct|
- Research-informed teaching that has direct value to industry, commerce and to you as an IT industry professional.
- You will develop a critical perspective of Big Data and be able to apply this to a range of scenarios
- Access to a wide range of facilities, including laboratories housing specialist computing equipment and software
The modern world is experiencing a growth of online data in a variety of forms, including social networks, web documents, digital libraries, blogs, medical records, biological data, remote sensing, imaging, forecasting etc. This data may not be fully structured but still contains valuable information that needs discovering, such as emerging opinions in social networks, consumer purchase behaviour, trends from search engines, and other patterns that emerge from such huge data sources.
These developments mean traditional applications are no longer appropriate to the processing and analysis of the amount of data available. Companies, such as Google, are leading the movement from a large-scale relational database reflecting the desire to analyse data automatically and on a larger scale than previously seen.
The course is designed to respond to critical skill shortages in the rapidly expanding field of Big Data. It offers a balance of practical skills combined with academic rigour in the field of Big Data. This is a unique offering which builds on the strengths and experience of Staffordshire University in delivering practical scholarship relevant to real world situations.
It is intended to assist students and career professionals enter and succeed in the growing, high demand analytics workforce. The course recognises and acknowledges the changing patterns in study including the growing demand for extended and distance learning modes of study and builds on the many years of experience we have of delivering these modes.
As a full time student, you would study in the first semester:
Managing Emerging Technologies COIS71170
Data Harvesting and Data Mining COIS71171
Distributed Storage COIS71172
Distributed Processing COIS71173
This first semester is concerned with those areas of big data fundamentals and is used to examine how big data is stored, processed and how an organisation can start to use tools to examine this data and start to improve businesses awareness of its customer base.
In the second semester you will study
Research Methods COIS71040
Big Data Applications COIS71174
Data Modelling and Analysis COIS71175
This semester encompasses a module on how to manage big data within a network, a maths module on algorithms that are required to enhance big data and a module which will prepare you for the master project in the last semester. The last module will examine existing big data applications that can help get the most out of big data.
The final semester is a major research project. The actual content is open to discussion with the award leader and project supervisor must be a discipline related to Big Data.
On completion of the award you will have developed detailed knowledge and understanding of Big Data and the ability to apply this knowledge in an academic or commercial context.
The award also aims to instil sound academic & professional skills required for lifelong learning & development - for example, skills in research methods, critical thinking & analysis, academic and professional report writing, and communication skills.
Normal requirements are at least a UK second class honours degree or equivalent in a related computing discipline
If you do not meet the above but have significant appropriate experience, your application will be considered, provided that you satisfy the University that you are capable of responding to the challenge of postgraduate work.
If your first language is not English, you will need to demonstrate that you are fluent enough to cope with the course. A minimum score of IELTS 6 or TOEFL 550 (213 computer-based) is normally required.
Cadman Information Point
t: +44(0)1782 294400
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