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Overview

Our MSc Big Data course addresses the growing importance of big data in business, and society at large.

International Data Corporation (IDC: a market research firm) forecast that the Big Data technology market will grow at a 26.4% compound annual growth rate (CAGR) to £28.79 billion by 2018 – approximately six times the growth rate of the overall information technology market; with 30% organizations collecting big data and/or the market of data driven services.

Our modules will prepare you to make notable contributions in modern day organizations with Big Data technologies. Equipped with necessary knowledge and hand-on experience you will enhance your employability within UK and internationally.

Unique and challenging modules are introduced, including Mobile networks and smartphone applications, Data mining and visualisation in addition to Ethics for IT professionals and Object oriented analysis and design that provide the foundation for Big Data.

Entry Requirements

What qualifications do you need?

We welcome Scottish, UK and international students and consider all applicants on an individual basis.

Don’t worry if your qualifications are not listed here, we take a range of factors into account when assessing your application and are happy to consider other alternative combinations of qualifications and experience

If you are applying with an EU or non-EU qualification, please check our Postgraduate Entry Requirements page which gives more information about country-specific entry requirements.

English Language Requirements

English language requirements for most courses

For applicants whose first language is not English, the University sets a minimum English Language proficiency level. The qualifications below must have been gained within two years of the start of your course.

General English language requirements at UWS: International English Language Testing System (IELTS) Academic module (not General Training)

  • overall score 6.0
  • no sub-test less than 5.5

Common equivalent English language qualifications

All stated English tests are acceptable for admission for both home/EU and international students for this programme:

  • CAE (Cambridge Certificate of Advanced English): 176 overall; no sub-test less than 169
  • CPE (Cambridge Certificate of Proficiency in English): 176 overall; no sub-test less than 169
  • Trinity College London Integrated Skills in English: ISEII with the minimum of a Pass in all sub-tests

 

IELTS Score Exceptions (DBA, Certificate of Higher Education, PhD, etc.)

For our research degrees (MRes, MPhil, PhD, DBA, DProf), applicants are required to have an IELTS score as follows:

  • overall score of 6.5
  • no sub-test less than 6.0


For Health, Nursing & Midwifery courses that lead to professional registration with the Nursing & Midwifery Council, applicants are required to have an IELTS score as follows:

  • overall score of 7.0
  • no sub-test less than 7.0


For our Certificate of Higher Education courses, applicants are required to have an IELTS score as follows:

  • overall score of 5.0
  • no sub-test less than 4.5

 

Pre-sessional courses

Applicants who do not meet the minimum English language requirements have the option to study one of our preparatory and pre-sessional English courses. The UWS courses available are:

  • 10 week pre-sessional - entry criteria UKVI IELTS 5.0 with no element below 4.5.
  • 5 week pre-sessional - entry criteria UKVI IELTS 5.5 with no element below 5.5.
  • English Language for University Study - entry criteria UKVI IELTS with score of 4.0 in all elements (10 month course), or 4.5 with no score below 4.0 (7 month course).

Course details

You will study the latest trends and technologies in Big Data in the following modules together with a Master's dissertation to obtain the MSc degree:

  • Mobile Networks and Smartphone Application
  • Data Mining and Visualization
  • Ethics for IT professionals
  • Object Oriented Analysis & Design
  • Research Design and Methods
  • Emerging Topics in Smart Networks
  • Advanced Data Science*
  • Intelligent Systems*

 

*Specialist modules

Teaching and Assessment

All modules are designed to respect the themes of Big Data, delivering research informed teaching via:

  • Lectures
  • Tutorials
  • Laboratory sessions

 

Our assessment methodology is influenced by the learning outcomes to be tested and employs a range of methods including:

  • essays
  • reports
  • strategic planning proposals
  • critical incident analysis
  • projects
  • research proposal
  • dissertation

Course Structure

Find out more about the structure, learning outcomes, compulsory and optional modules in this course.

Course Structure (17/18)

Career Prospects

Jobs

Examples of jobs available to you upon graduation include:

  • Data analysts
  • Data scientists
  • Data mining analysts
  • Technical developer
  • Project manager in Big Data

 

Salaries in these roles range from £30,000 to £75,000.

Further Study

Successful completion of our course prepares you for advanced research studies in related technology areas. You will have the priority to be admitted to the MPhil/PhD degree courses.

HOW TO APPLY

You should apply for all UWS postgraduate courses using our online application form.

APPLY ONLINE

The first stage of the process is to create an profile; you don't have to complete the application in one session - you can complete it in stages by saving what you do each session and return to complete it at a later date.

Most courses don't have a formal closing date, but they will close when they are full; apply early to avoid disappointment. There may also be funding deadlines that apply to you.

You will need to upload documents with your applications, which may include transcripts and degree certificates.

You can find out more here in our Postgraduate Application Guide.


An ATAS certificate is not required for overseas students applying for this course.

Enquiries

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Course Leader

Dr Naeem Ramzan & Dr Zeeshan Pervez

Computing

Research at UWS

With cutting edge facilities, specialist knowledge and world-leading and internationally excellent expertise, we aim to develop research outputs that have a tangible, early and positive impact on society across the globe.

Discover

We will always try to make sure that we publish accurate course information but we do not accept responsibility for any mistakes or omissions. We will also try to make sure that we deliver our courses in line with our published information. However, we may not always be able to do so and you can find further information about this in our enrolment terms and conditions.