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Big Data Analytics at Sheffield Hallam University - UCAS

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2024 - 20252025 - 2026
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There are other course options available which may have a different vacancy status or entry requirements – view the full list of options

Course summary

Please check the Sheffield Hallam University website for the latest information. Course summary

  • Learn to use industry-leading software including SAS, R, Python and the Apache HaDoop Ecosystem.
  • Obtain knowledge of data storage, data mining and statistical modelling techniques.
  • Study aspects related to the distribution and integration of data.
  • Gain up to twelve months real-world experience through the two-year work experience route.
This course has been developed in consultation with industry to produce graduates equipped to work with the large amounts of data now common to many businesses. How you learn All our courses are designed around a set of key principles based on engaging you with the world, collaborating with others, challenging you to think in new ways, and providing you with a supportive environment in which you can thrive. This course explores statistics, computing and management to help put you at the forefront of this vitally important field. You will gain an insight into Data Analytics, including Statistical Modelling and Data Mining, Big Data and Distributed Systems, Data Integration, Programming Concepts and Practice, and the core skills around professionalism, project management and research. 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 cutting-edge software such as SAS, Python, RStudio and others. You learn through
  • Teaching sessions
  • Learning materials
  • Recommended readings
  • Problem-based learning
  • Group projects
  • Contemporary software platforms
This course is delivered face-to-face over three semesters - teaching is scheduled based on the length of your course and the academic calendar. Applied learning Live projects You will have the opportunity to work on real work-based projects supplied by an external company or emulated industry case studies. You apply the skills and knowledge gained from your studies in topics such as data integration, statistical modelling, big data and distributed systems to situations of genuine complexity. Networking opportunities The teaching team make use of their research and industry connections to facilitate the inclusion of real work scenarios and case studies within many of the modules. There are many industries that make use of the skills developed on the course once you have graduated, including:
  • Pharmaceuticals
  • Finance
  • Marketing
  • Retail
Public and Private Sector organisations such as: Police, Government, NHS, Amazon, Facebook, UK Ministry of Defence, HSBC and GSK all make use of data management/analytics extensively to help them to better understand their customers and to make informed business decisions. IBM ranked these jobs as one of the most difficult for employers to recruit, due in part to the shortage of skills in this area.

Modules

Module and assessment information for future years is displayed as currently validated and may be liable to change. When selecting electives, your choices will be subject to the core requirements of the course. As a result, selections may be limited to a choice between one of two or more specified electives in some instances. Modules studied may differ depending on when you start your course. Compulsory modules Advanced Data Management Project Data Analytics: Tools And Techniques Dissertation For Computing Industrial Expertise Programming Concepts And Practice Research Skills For Computing Study Skills And Project Management

Assessment method

Coursework | Practical

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. You may also be able to claim credit points which can reduce the amount of time it takes to complete your qualification at Sheffield Hallam.

English language requirements

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.

Please click the following link to find out more about English language requirements for this course

https://www.shu.ac.uk/Courses/Computing/MSc-Big-Data-Analytics/Full-time/

Fees and funding

Tuition fees

No fee information has been provided for this course

Tuition fee status depends on a number of criteria and varies according to where in the UK you will study. For further guidance on the criteria for home or overseas tuition fees, please refer to the UKCISA website .

Additional fee information

Our postgraduate fees vary depending on course, level and mode of study. Each postgraduate course page tells you how much the tuition fees are, and what additional costs you might have to budget for during your studies. Please refer to our website for up-to-date information on costs and fees for both full-time and part-time postgraduate study options.

Sponsorship information

Scholarships, discounts and bursaries may be available to students who study this course.

Big Data Analytics at Sheffield Hallam University - UCAS