MSc Big Data Analytics

  • International Students Can Apply

Overview

UCAS Code:P060386
Course Length:12-18 Months Full-Time, 2-3 Years Part-Time
Start Dates:January 2020, September 2020, January 2021
Department:Department of Computer Science
Location:Edge Hill University

Please note, there is an intake to the 12-month full-time route each September and 18-month full-time route each January. The part-time route takes 2-3 years to complete and typically has intakes in both September and January.

  • Gain the skills and knowledge to work within a growing sector of the IT industry in the UK and beyond;
  • Develop a range of IT and personal skills and apply these to real life problems;
  • Obtain specific core data science skills that can be applied across industries.

This Masters degree provides you with a strong conceptual and theoretical understanding of big data analytics. You will gain the essential skills and confidence required to apply and produce knowledge and understanding of issues surrounding big data analytics in a range of contexts. This will enable you to evaluate, adapt, create and utilise appropriate models, methods, practices, theories and computational techniques in the face of changing and evolving technology. There is the opportunity to develop a critical understanding of visualisation concepts, modelling and algorithmic foundations, as well as to develop and evaluate new or advanced bespoke solutions for processing, analysing and making sense of big and/or complex data. The programme enables you concentrate on a specific practical area within computer science and is suitable whether you are a recent graduate or already working in the IT industry and looking to change career paths.

In Depth

What will I study?

Gaining an in-depth and systematic knowledge of big data management theories, concepts, methodologies and professional practice, you will develop a systematic and critical understanding of algorithms and programming techniques for processing, storing, analysing, visualising and interpreting data.

You will learn the practical skills of mathematics that underpin the processing of data, the programming applications required to manage big data, and the visualisation techniques necessary to make sense of large data sets. There will also be the opportunity to work with emerging technologies derived from industry.

How will I 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.

How will I 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 me?

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 so you will benefit from a wide range of expertise. There will also be occasional input from external IT professionals who will be invited to teach particular sessions.

A Great Study Environment

Two students with rucksacks walk in front of the Tech Hub.The Department of Computer Science is based in the state-of-the-art £13m Technology Hub. This purpose-built development offers highly contemporary suites of outstanding facilities for Computer Science students.

Our modern computer laboratories are equipped with 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.

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.

The department has strong links with industry and the curriculum is kept current and highly relevant through input from our Employer Advisory Panel.

Modules

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CIS4114Research and Development Project (60 credits)

Research and Development Project provides experience of designing and executing a substantial project in a limited time, based on a project plan, employing practical skills, problem solving and underpinned by relevant research. You will apply and extend skills and knowledge learned in taught modules and demonstrate your competency to construct and complete a coherent project as a Computing professional.


Assessment: Coursework: 100%.

CIS4115Research Methods (20 credits)

Research Methods provides you with the knowledge and skills to develop a proposal for, and subsequently undertake, a research project at Masters level. You will engage with the essential considerations when analysing a problem and designing a solution. The module will also immerse you in data collection from the user, literature reviews, interface designs and project planning. On successful completion, you will have a well-formed proposal suitable for Masters level study.


Assessment: Coursework: 100%.

CIS4116Emerging Technologies (20 credits)

Emerging Technologies equips you with an advanced understanding of emerging technology and develops the appropriate skills to critically evaluate their suitability, impact and applicability to new scenarios. The module also strengthens your ability to identify and analyse ethical issues related to the use of new technology for both development and research purposes, including an overview of the professional and legal constraints within which computing specialists operate.


Assessment: Coursework: 80%, Practical(s): 20%.

CIS4117Advanced Analytics: Tools and Techniques (20 credits)

Advanced Analytics: Tools and Techniques provides a systematic overview of various aspects of data analysis and data processing. On the theoretical side of the module, you will be introduced to the advanced data structures, programming techniques and effective approaches to achieve a better understanding of data. On the practical side, you will utilise a selected modern programming language and data analysis software to resolve real world tasks.


Assessment: Coursework: 70%, Written Exam(s): 30%.

CIS4118Data Visualisation (20 credits)

Data Visualisation immerses you in the techniques used for understanding and interpreting data to present it in a pictorial or graphical format. These approaches enable people to present analytics visually in order to aid the grasping of difficult concepts or to help identify new patterns. The module will enable you to understand and interpret unstructured heterogeneous real-word data and present it visually in a quick and easy way to convey concepts in a universal manner. In particular, you will learn cutting edge techniques linked to information visualisation, scientific visualisation and visual analytics and experiment in visualising big data in immersive virtual reality environments. Many aspects of the module will be supported by real-world examples and case studies.


Assessment: Coursework: 100%.

CIS4119Algorithms for Big Data (20 credits)

Algorithms for Big Data equips you with a critical, systemic and in-depth understanding of the most relevant algorithmic approaches to big data analytics. Big data analytics is a multi-disciplinary field where a variety of theoretical methods and techniques are utilised to identify, classify and extract actionable information from large unstructured datasets. The module will enable you to obtain a strong conceptual and theoretical understanding of the main algorithmic techniques and their practical implementation to address relevant problems in big data analytics. In particular, the module covers the most relevant, cutting edge algorithmic models, methods and theories. The computer language Python will be used to critically evaluate implementation issues in this field. You will also be encouraged and guided to explore innovative solutions and to make a personal contribution within your chosen field of big data analytics.


Assessment: Coursework: 100%.

CIS4120Applications in Big Data (20 credits)

Applications in Big Data provides you with hands-on experience in handling, managing, processing and analysing diverse types of data in large volumes. The module explores analysis methods, data mining algorithms, visualisation techniques and advanced programming skills which will be combined to address real-life big data analysis tasks. You will develop the skill of deciding which tools and methods are suitable for a given big data analysis task and consider how to combine them in a unified system and how to implement them to provide a ready-to-use solution.


Assessment: Coursework: 100%.

Timetables

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. Postgraduate Computing courses are typically taught between 6pm-9pm on weekday evenings.

Disclaimer

Every effort has been made to ensure the accuracy of our published course information, however our programmes are subject to ongoing review and development. Changing circumstances may necessitate alteration to, or the cancellation of, courses.

Changes may be necessary to comply with the requirements of accrediting bodies, revisions to subject benchmarks statements, to keep courses updated and contemporary, or as a result of student feedback. We reserve the right to make variations if we consider such action to be necessary or in the best interests of students.

Entry Criteria

Entry Requirements

To join this MSc you should have a degree equivalent to UK 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 for entry to this programme.

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 lower, either overall or in one or two elements, you may want to consider our Pre-Sessional English course.

Recognition of Prior Learning

Edge Hill University recognises learning gained elsewhere, whether through academic credit and qualifications acquired from other relevant courses of study or through recognition of an individual’s professional and employment experience (also referred to as ‘experiential learning’).

Previous learning that is recognised in this way may be used towards meeting the entry requirements for a programme and/or for exemption from part of a programme. It is your responsibility to make a claim for recognition of prior learning. For guidance, please consult the University’s Recognition of Prior Learning Policy and contact the faculty in which you are interested in studying.

Career Prospects

What are my career prospects?

As organisations become ever more dependent on data, there are increasing opportunities in specialist positions related to obtaining, processing and visualising data.

The MSc Big Data Analytics provides you with the skills and knowledge to develop your interests for a career in data science. You will be ideally placed to progress into roles where you will work as a data scientist or data analyst.

Finance

Tuition Fees

Tuition fees for full-time study on this MSc are:

  • £5,220 for UK and EU students and £13,000 for international students enrolling on the programme in academic year 2019/20;
  • £5,400 for UK and EU students and £13,250 for international students enrolling on the programme in academic year 2020/21.

Tuition fees for part-time study on this MSc are:

  • £29 per credit for UK and EU students enrolling on the programme in academic year 2019/20, i.e. £580 per 20 credit module;
  • £30 per credit for UK and EU students enrolling on the programme in academic year 2020/21, i.e. £600 per 20 credit module.

180 credits are required to complete a Masters degree.

The University may administer a small inflationary rise in part-time postgraduate tuition fees in subsequent academic years as you progress through the course.

Financial Support

For comprehensive information about the financial support available to eligible UK and EU students joining postgraduate courses at Edge Hill University, together with details of how to apply for potential funding, please view our Money Matters guide for your intended academic year of entry.

Financial support information for international students can be found at www.edgehill.ac.uk/international/fees.

Apply

How to Apply

Apply online at www.ucas.com/postgraduate.

Visit www.edgehill.ac.uk/applyucaspostgraduate for more information about the application process.

Further information for international students about how to apply is available at www.edgehill.ac.uk/applyinternational.

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.

Visit Us

If you are considering applying to study at Edge Hill University, the best way to gain an insight into student life is to discover our stunning campus for yourself by attending an open day. You can view dates and book your place at www.edgehill.ac.uk/opendays.

Alternatively, if you are unable to attend an open day, you can find out more about all of our events for prospective students, including monthly campus tours, at www.edgehill.ac.uk/visitus.

Request a Prospectus

If you would like to explore our full range of taught Masters degrees, MBA awards and our Masters by Research (MRes) degree before you apply, you can order a postgraduate prospectus at www.edgehill.ac.uk/postgradprospectus.

Get in Touch

If you have any questions about this programme or what it’s like to study at Edge Hill University, please contact:

If you would like to talk to the programme leader about the course in more detail, please contact:

International students should visit www.edgehill.ac.uk/international or email international@edgehill.ac.uk with any queries about overseas study.

Course Changes

Expand All This page outlines any material changes to course content, programme structure, assessment methods, entry criteria, and modes of study or delivery, implemented in the past two years.

This page outlines any material changes to course content, programme structure, assessment methods, entry criteria, and modes of study or delivery, implemented in the past two years. No material changes have been made to the information for this programme in that time. Any future amends will be tracked here.