Online course details

Study options

Part-time: 2-3 years

UK fee

£8,775 (2023/24)

International fee

£8,775 (2023/24)

Course level

Postgraduate

Qualification

MSc

Start dates

September, January

Location

Online

Online course description

Big data is all around us. It is the vast amount of data that continues to be generated in line with our growing use of IT products and services. This constant growth creates exciting new career opportunities for big data specialists. Professionals who can identify and obtain intelligence from big data are in demand like never before.

Our online Big Data Analytics programme gives you an in-depth knowledge and critical understanding of the key issues and concepts in today’s data-driven business and science landscapes. You will develop powerful skills in the extraction, analysis and management of information from big data using a variety of scientific techniques and software tools.

As an online student, you will be able to draw on the extensive industrial links of our academic staff and share knowledge of best practice with fellow students, all while navigating your course materials in our virtual learning environment.

Real-world understanding

During your studies, you will address real-world industry-based problems. This intellectually demanding process requires not only specialist knowledge of big data analytics but also the ability to apply multi-disciplinary concepts to today’s dynamic business and scientific areas.

Natural language processing and text mining

Gain insight into industry relevant approaches to natural language processing (NLP) and text mining, developing the ability to extract and analyse various data sets. Relevant software tools will be used to enable a critical appreciation of computational, ethical and governance issues in this field, using the Vs of Big Data (volume, velocity, variety, veracity and value) as a critical framework.

Build your skill set around your career aspirations

This is a flexible programme which enables you to choose from highly relevant optional modules to tailor your programme of study to meet your particular interests or professional needs.

On this programme, you’ll develop a comprehensive skill set in computing and information technology, particularly in the areas of data analytics, business intelligence and information management, visualisation and assurance, as well as people analytics in HR. This will prepare you for a career in a rapidly growing industry more widely applicable and relevant than ever.

Gain valuable experience working on real world projects at our Data Research Centre

The Data Science Research Centre is run by a team of computer and data science specialists.

You will have the opportunity to work with employers across the industry on a number of exciting projects remotely online with the Data Research Centre. This will help you gain valuable work experience. We can also support you in gaining an internship with our industry contacts.

You will be able to draw on the latest innovations in data analytics, the Internet of Things, complex networks, machine learning and artificial intelligence.

You can also study the Big Data Analytics MSc full-time or part-time on campus.

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Giving back to her local community

Not only is Adebanke using her skills to improve her career but she is also helping her local community.

Read Adebanke's storyRead Adebanke's story
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Data Science Research Centre (DSRC)

Our team of computer and data science specialists are using their expertise to explore new ways of processing large sets of data to solve real-life problems.

Learn more about the centreLearn more about the centre

What you will study

By completing this programme, you will:

We will advise you of your study plan - the running order and availability of the modules - when you are invited to enrol. If we have insufficient numbers of students interested in an optional module, this may not be offered. In addition, where demand is high, some modules may be subject to a cap.

What you can achieve

The online Big Data Analytics MSc comprises three progressive stages: postgraduate certificate (PG Cert), postgraduate diploma (PG Dip) and masters (MSc). You will be required to achieve 60 credits to complete each award within the programme, totalling to 180 credits to achieve the masters.

You will be awarded a Postgraduate Certificate in Big Data Analytics if you pass the 20-credit core module Emerging Computer Technologies and Research Methods and two other 20-credit modules (adding up to 60 credits) from either the core modules or the optional modules.

A Postgraduate Diploma in Big Data Analytics can be obtained by passing the four 20-credit core modules and two of the 20-credit optional modules (adding up 120 credits).

A Master of Science in Big Data Analytics can be obtained by achieving the PG Dip and completing the independent study module worth 60 credits (180 credits).

We would encourage you to complete the full MSc but, if you prefer, you can still gain an exit award at each stage: a PG Cert or a PG Dip.

Students who do not complete the full Masters programme of study (180 credits), may be awarded a Postgraduate Certificate in Big Data Analytics with 60 credits if they pass three modules, including Emerging Computing Technologies and Research Methods.

Please note that our modules are subject to change - we review the content of our courses regularly, making changes where necessary to improve your experience and graduate prospects.

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Discovering Online Learning Webinar: April 2023

Wednesday, 5 April 2023 13.00 - 14.00

During this hour-long webinar, we'll take you through how online learning works and what you can expect as an online learner with the University of Derby Online Learning.

Book your webinarBook your webinar

How you will learn

Pace of study

The academic year is made up of three 10-week terms, known as trimesters. We recommend about 20 hours of study per week to complete one 20-credit module over a 10-week trimester.

If you opt to undertake the accelerated study plan whereby you will study two modules in one trimester, we recommend 40 hours of study per week.

Should you decide to study on the accelerated rate you should ensure that you have the capacity to fully engage with your studies and achieve the best grades and final award. If you choose to study on the accelerated rate, you will need to balance approximately 40 hours of study per week alongside your professional and personal life and commitments.

It may be useful to consider studying one module at the standard rate of study before deciding whether to then increase to the accelerated rate of study.

Assessment method

This course is assessed through 100% coursework with a range of methods, such as essays, research reports, presentations, group work and practical reports.

Student support and guidance

Whilst we encourage our students to become independent, life-long learners, we also recognise that offering the right support and guidance will help you to achieve your goals. There is a wealth of support available to you at the University, from your dedicated Personal Tutor and Online Learner Advisor, through to our:

All these services, and more, are available to you as an online student at the University of Derby.

Who will teach you

Harry Yu

Dr Harry (Hongqing) Yu
Programme leader

Dr Hongqing Yu also known as Harry is a Senior Lecturer in Computer Science and Programme Leader of MSc Big Data Analytics. He mainly teaches on the topics involved in Data Science, Machine learning and AI technologies. 

View full staff profileView full staff profile

Get a taste of the course content

Our Big Data Analytics MSc course taster will give you an idea of how online learning works. It includes a selection of content from a course module so you can see some of the learning material.

You will need to complete a short form to access the course taster.

Try our course tasterTry our course taster

Entry requirements

You will require a 2.2 or higher bachelors degree in a Science, Technology, Engineering, Mathematics (STEM) or a closely related discipline with significant mathematical content at an appropriate level, or an equivalent international degree.

If you don’t have a degree or an accredited degree, we can consider your application if supported by significant industrial experience. Please include evidence of all experience you have in your application. While the University guidelines on recognition of prior learning (RPL) will be followed, RPL will only be recommended where applicants can present a portfolio of professional work that is deemed to be of an appropriate level.

English language qualifications

If English is not your first language, or you have not successfully completed your highest level of qualification in English, you will need an English language qualification*. For this course you will need at least one of the following:

*If you have a minimum of IELTS level 4.5 you can study our Certificate of Credit in English for Academic Purposes which we will accept as evidence that you are able to perform at a suitable level of IELTS 6.0. We will also accept the Certificate of Credit as evidence that you can perform at GCSE level.

Find out more about our English language requirements

Fees and funding

2023/24 for new entrants

Starting between September 2023 and August 2024.

 Per 20 creditsModulesCost
UK/EU/International £975 7 (six 20-credit modules and one 60-credit module) £8,775

About your fees

This figure would be the total cost of this course in the current academic year. However, please note that fees normally increase in line with inflation and the University's strategic approach to fees, which is reviewed on an annual basis. The total fee you pay may therefore increase if your course lasts longer than one year.

However, please also note that you can receive a 5% discount if you either:

Flexible payment plans available

Choose from three payment plan options:

Masters funding options

Depending on where you are from in the UK or EU, and on your pace of study, you may be eligible for a postgraduate student loan. Accessible through Student Finance, this is a non-income based loan to help with living costs and tuition fees whilst studying your masters programme.

Alumni discount for Derby graduates

We offer a discount on postgraduate course fees for all Derby alumni.

Find out more about the Alumni discount

How to apply

Please look at our application deadlines before you apply.


Students should apply directly to the University.

Apply now

For support with completing your application, view our guide to the application process.

Documents to support your application

In order for your application to be assessed, you will need to provide the following documents when you apply:

*Documents not in English or Welsh must be accompanied by a certified translation by a professional translator/translation company. Each translation must contain:

A list of approved translators can be found on the UK Government website.

Please note: failure to submit any documentation when requested, may result in your application being withdrawn.

Application deadlines

All of our online courses have set start dates throughout the year. We require time to review your application and get back to you with a response before your course starts. Take a look at information regarding applying for an online course to see full details of deadlines and term dates.

Careers

The job market around Big Data is rapidly increasing and is trending to be in constant demand as our use of computer data is ever expanding. After completing the Big Data Analytics MSc, you will be able to pursue a career in many areas of computing and information technology, particularly in the areas of data analytics, business intelligence and information management, visualisation and assurance, as well as people analytics in HR.

You could also consider further study and research towards a PhD qualification.

Contact us

Contact the University of Derby Online Learning:

Contact usContact usFrequently asked questionsFrequently asked questions

† Additional information about your studies

Start dates are subject to programme reaching minimum numbers

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