Online course details
Part-time: 3 years
January, September, May †
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.
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.
You can also study the Big Data Analytics MSc full-time or part-time on campus.
By completing this programme, you will:
- Develop high-level skills in business intelligence, data analytics and database technology
- Harness the full power of SAS statistical analysis software, thanks to our partnership with the global leader in business analytics services
- Address real-world industry-based problems and conduct a major research project on a theme of your choice
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 Studying at Masters Level 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.
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.
Pace of study
We recommend about 20 hours of study per week to complete one 20-credit module over a 10-week trimester. If you aim to study two modules in one trimester, we recommend 40 hours of study per week.
This course is assessed through 100% coursework with a range of methods, such as essays, research reports, presentations, group work and practical reports.
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 you will need an English language qualification*. For this course you will need at least one of the following:
- IELTS 6.0 (minimum of 5.5 in any areas)*
- TOEFL 580 (paper based) 237 (computer based) or 92 (internet based)
- Pearson Test of Academic English: 58
- Cambridge Advanced Certificate: Pass
- London Tests of English: we accept level 5 for postgraduate courses
- International GCE O Level English Language: Grade C
- International GCSE English/English as a Second Language: Grade C.*
*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.
Documents to support your application
You'll need to provide:
- Photo ID – this could be your passport or driving licence
- Current CV
- Written reference supplied on headed paper from either a manager, supervisor, tutor or teacher
- Copies of certificates and transcripts or a letter of testimony for previous qualifications*
*Documents not in English or Welsh must be accompanied by a certified translation by a professional translator/translation company. Each translation must contain:
- Confirmation from the translator that it is an accurate translation of the original document
- The date of the translation
- The full name and signature of the translator, or an authorised official of the company
- The translator’s contact details
A list of approved translators can be found on the UK Government website.
| ||Per 20 credits||Modules||Cost|
||7 (six 20-credit modules and one 60-credit module)
† Prices correct for 2019/20 new students. Subject to potential annual increase in September 2020.
Flexible payment plans available
Choose from three options:
Pay monthly and only for the modules you are studying
Pay your full course fees upfront, receive 5% discount and avoid annual increases
Pay for all modules studied in the year and receive a 5% discount (September enrolment only)
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.
Students should apply directly to the University.
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 the University of Derby Online Learning:Contact usFrequently asked questions
† Additional information about your studies
Start dates are subject to programme reaching minimum numbers
Prices correct for 2019/20 new students. Subject to potential annual increase in September 2020.
Download programme specification