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Big Data Analytics MSc

Volume. Velocity. Variety. Veracity. Big data poses challenges never faced before. Master the theories, algorithms and techniques that untangle large and complex data sets on a Masters degree awarded initial accreditation by BCS, The Chartered Institute IT.

Closed to further applications for January 2023 entry. For September 2023 entry onwards, please see MSc Data Science & Artificial Intelligence.

Overview

Course length: 12-16 months full-time
2-3 years part-time
Start dates: January 2023
Location: Edge Hill University
Subject(s): Computing and IT
Faculty: Arts and Sciences
Department: Computer Science
Three students study a spreadsheet on a laptop.

What revelations hide in social media, mobile applications or Internet of Things (IoT) sensor data? Our MSc Big Data Analytics unlocks the theories, skills and tools you need to uncover hidden patterns, correlations and trends.

As a recent computer science graduate or IT industry career changer, you’ll become a big data specialist on this course.

Big data analysts work in a changing and evolving technology landscape. You need imagination and creativity to come up with novel ways to answer questions. We’ll teach you to assess new and advanced solutions then adapt them as you process, analyse and make sense of big and complex data.

Study visualisation, modelling, and the foundations of artificial intelligence and machine learning algorithms. Assess issues presented by big data in different situations. Learn essential methods, practices, and theories. Study relevant computational techniques. You’ll develop the skills and confidence you need to succeed with our Masters in big data analytics.

Please note, there is an intake to the 12-month full-time route each September and 16-month full-time route each January. The 16-month full-time route includes the UK summer break between semesters. The part-time route takes 2-3 years to complete and typically has intakes in both September and January.

BCS, The Chartered Institute for IT logo. Subject to re-approval.

Course features

  • Professional accreditation

What you'll study

Data mining. Virtual reality. Practical maths. Our Masters programme gives you the full skillset and experience you need to become a big data expert.

Become an expert in choosing the right tools and methods for a specific task. Study the tools and techniques for advanced analytics. Get a deep understanding of the ideas and theories behind different algorithmic approaches. Learn to handle, manage, process and analyse different kinds of data in different ways.

Help people make sense of big data sets. Learn the latest ways to share your results using graphs, pictures and virtual reality. Explore what’s new in computing and judge its usefulness for data analysis while assessing its ethical impact. Put your knowledge into practice as you get creative to solve big data problems.

Compulsory modules:

Expand all

Advanced Analytics: Tools and Techniques

Algorithms for Big Data

Applications in Big Data

Data Visualisation

Emerging Technologies

Research and Development Project

Research Methods

How you'll study

The course is delivered through a combination of lectures, seminars and tutorials with a mixture of daytime and evening classes. Sessions will frequently be highly interactive with a focus on the practical application of concepts and the use of case studies drawn from real life. An emphasis on small group sizes ensures that you will have plenty of opportunities for individual discussions with your tutors. Typically, you will study for approximately nine hours a week if you are studying on a full-time basis.

There is typically an intake to the 12-month full-time route each September and 16-month full-time route each January. The 16-month full-time route includes the UK summer break between semesters. The part-time route takes 2-3 years to complete and typically has intakes in both September and January.

You can expect to receive your timetable at enrolment. Please note that while we make every effort to ensure that timetables are as student-friendly as possible, scheduled teaching can take place on any day or evening of the week.

How you'll be assessed

Your vocational capability, academic critical thinking and intellectual development will be assessed throughout the course. This is achieved through a combination of coursework, case studies, problem-solving exercises and examinations. You may be assessed individually or as part of a group.

Who will be teaching you

You will be taught by highly qualified, experienced and enthusiastic academic staff who are research-active and fully engaged with the wider business and academic community. The programme team specialise in a variety of subjects. You will benefit from a wide range of expertise in areas such as the Internet of Things, smart devices, cloud/edge/distributed computing, data science, data analytics and visualisation, computer vision, artificial intelligence, machine learning and deep learning. There will also be occasional input from external IT professionals who will be invited to teach particular sessions.

Entry criteria

Entry requirements

You should have a degree equivalent to UK first-class or second-class honours (2:2 or above), comprising 50% or more of content in a computing discipline.

Equivalent knowledge gained in alternative ways, for example through professional experience or completion of BCS Professional Diploma in IT (Level 6), is also accepted.

English language requirements

International students require IELTS 6.5, with a score no lower than 6.0 in each individual component, or an equivalent English language qualification.

If your current level of English is half a band, one band, or one-and-a-half bands lower, either overall or in one or two elements, you may want to consider our Pre-Sessional English course.

How to apply

There is an online application process for this course.

The course is closed to further applications for January 2023 entry. For September 2023 entry onwards, please see MSc Data Science & Artificial Intelligence.

Please see our international student pages for further information about how to apply as a prospective international student.

Should you accept an offer of a place to study with us and formally enrol as a student, you will be subject to the provisions of the regulations, rules, codes, conditions and policies which apply to our students. These are available at www.edgehill.ac.uk/studentterms.

Did you know?

If you join a full time undergraduate degree at Edge Hill University, we will guarantee you the offer of a room in our halls of residence for the first year of your course.

Discover our accommodation

Facilities

Tech Hub.The Department of Computer Science is based in the state-of-the-art £13million Tech Hub. This purpose-built development offers highly contemporary suites of outstanding facilities for Computer Science and Engineering students. Our modern computing and engineering laboratories are equipped with comprehensive test and measurement equipment, high-specification computers, high-resolution screens and the latest hardware and software.

A four-screen CAVE (Computer Augmented Virtual Environment) provides a super immersive 3D virtual environment, enabling users to immerse themselves in a virtual room and experience real life scenarios in 4K resolution. There are also specialist laboratories for networking and games programming, in addition to a specialist research laboratory, open access laboratory, a Harvard style lecture theatre, and ‘The Hatchery’, a working space for new business ideas.

Where you'll study

Tech Hub

Learning resources

Learning resources include robots and a robotics simulator, wired and wireless networking hardware, graphics software, web development tools, software development environments, big data servers, eye trackers, giant 3D interactive teaching screens, and other specialist software required for studying forensics and internet security techniques.

Finance

Tuition fees

UK Full-Time

£7,000

for the course

UK Part-Time

£39 per credit

for 180 credits

International

£13,500

for the course

EU/EEA and Swiss students who have settled or pre-settled status under the EU Settlement Scheme, as well as Irish nationals, may be eligible for the UK tuition fee rate.

Financial support

Please view the relevant Money Matters guide for comprehensive information about the financial support available to eligible UK students joining postgraduate courses at Edge Hill University.

EU/EEA and Swiss students who have settled or pre-settled status under the EU Settlement Scheme may be eligible to apply for financial support. Irish nationals can ordinarily apply to Student Universal Support Ireland (SUSI). If you are an EU student who does not have settled or pre-settled status, or are an international student from a non-EU country, please see our international student finance pages.

Your future career

You’ll develop the skills and knowledge you need for a career in data science with our MSc Big Data Analytics. Apply for roles like data scientist, data analyst, big data developer or data engineer. Many industries are looking for graduates with these skills, including:

  • banking and finance
  • healthcare and pharmaceutical
  • telecommunications
  • internet and online sales
  • energy
  • cars and transport

If industry doesn’t appeal, you could create your own start up or study to PhD level like previous students.

This programme starts you on the path to chartered status.

This course has initial accreditation from BCS, The Chartered Institute for IT, on behalf of the Engineering Council, for the purposes of partially meeting the academic requirement for registration as a Chartered Engineer. It also has initial accreditation from BCS, The Chartered Institute for IT, for the purposes of partially meeting the academic requirement for registration as a Chartered IT Professional. Initial accreditation is granted to new programmes which are yet to have a graduating cohort. Successfully completing an accredited BCS course is the first step to full BCS membership and to being awarded chartered status.

Download our course leaflet