MSc Big Data Analytics

Attendance

Full-time, Part-time

Full-time – 12 to 18 months
Part-time – up to 6 years

At a glance

Develop the skills to become a talented data scientist able to complete technical roles, such as data mining specialist, predictive modeller, computational linguist and statistical analyst on this course. It develops both the analytical and technical skills you need, and gives you experience of using industry standard software and technologies.

Key points
• Gain expertise in industry standard software such as SAS and SAP.
• Integrate your analytical and technical skills.
• Gain skills so you are ready to meet the predicted skills shortage in this area.

About this course

Big data is the description used to encompass the huge amounts of data that is common to many businesses. It has been described as the next frontier for innovation, competition and productivity in business. It is essential for companies to embrace so that they can understand their customers better, develop new products and cut operational costs.

This course has been developed to create graduates who can become data scientists capable of working with the massive amounts of data now common to many businesses. It is aimed at people who want to move into this rapidly expanding and exciting area.

The modules on this course help you develop the core skills and expertise needed by the data scientist. The course can be split into three main areas, statistics, computing and management.

In the statistics section you study modules on data quality, data mining and data modelling. These modules cover the three main data areas, which are ensuring that data is reliable and of a high quality, searching the data to discover new information and presenting interpretations of that data to the end user.

The computing section covers areas related to massive datasets stored in the cloud, how data is stored and utilised within the distributed systems of an enterprise and how organisations can utilise data to change and improve business processes.

The management modules are focused on developing your core skills around professionalism and research. All of which are valuable skills during your university studies and in your career.

Our partnerships with business inform the course design, ensuring the content is relevant, up to date and meets the needs of industry. These partnerships also enable the inclusion of some leading edge software such as SAS, SAP Hana, and Hadroop within the course.

Key areas of study
Key areas of study include • data quality and analysis • technologies to store and mine data • professionalism and research

Associated careers

Many jobs for data scientists, data analysts and data mining analysts are available with salaries ranging from £35,000 to £80,000. 

Jobs typically list the skills to be in areas such as statistical analysis and machine learning techniques, database and programming technologies, and expertise in statistical theory, which are all areas you cover on this course. 

You also gain skills and knowledge in HaDoop, MapReduce, Java, SAS, MSQL which are some of the common technologies used in data scientist roles.

Course content

Core modules

• study skills for professionals • industrial expertise • research principles and practice • data quality • statistical modelling • data mining • data in the cloud • big data and distributed systems • change management and SI • advanced statistical modelling and data mining • dissertation

Assessment

• essays • assignments • computer-based tests • practical projects • presentations • vivas

Entry requirements

A good honours degree in computing, computer science, maths or statistics or other relevant areas or equivalent.

We consider your application if you do not have a relevant degree but have at least one year's direct work experience in computing or a relevant area

Non-native speakers of English need an IELTS score of 6.0 with 5.5 in all skills (or equivalent). If your English language skill is currently below an IELTS score of 6.0 with a minimum of 5.5 in all skills we recommend you consider a Sheffield Hallam University Pre-sessional English course which will enable you to achieve an equivalent English level.

Fees

Home and EU students

2013/14 academic year

Typically £5,355 for the course
Part-time study should be calculated pro rata

International students

2013/14 academic year

Typically £10,980 for the course

2014/15 academic year

Typically £11,250 for the course

How to apply

Complete the application form available at www.shu.ac.uk/study/form

Contact details

For further information please contact the Faculty of Arts, Computing, Engineering and Sciences, Sheffield Hallam University, City Campus, Sheffield S1 1WB. Phone +44 (0)114 225 6777 or email aces-helpdesk@shu.ac.uk