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Data Science and Analytics MSc

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Subject area: Computer Science
Mode of study

1-year full-time; 2-year part-time

PG code

I200PDATA

Start date

September

Location of study

Brunel University London campus

Data Science and Analytics MSc

Overview

From social networks, ecommerce and government through to sensors, smart meters and mobile networks, data is being collected at an unprecedented speed and scale. But big data is of little use without 'big insight'. The skills required to develop such insight are in short supply and the shortage of skilled workers in the data analytics market is cited as a key barrier to unlocking everything that data has to offer.

The Data Science and Analytics MSc programme provides these skills, combining a strong academic degree course with hands-on experience of leading commercial technology, and the chance to gain industry certification. You will develop both your critical awareness of the very latest developments in data science and the practical skills that help you apply data science more effectively in a wide variety of sectors including finance, retail and government.

You’ll gain knowledge of key concepts and the nuances of effective data analysis. You’ll gain confidence in your own critical understanding of the challenges and issues arising from taking heterogeneous data at volume and scale, understanding what it represents, and turning that understanding into insight for business, scientific or social innovation. You’ll develop a practical understanding of the skills, tools and techniques necessary for the effective application of data science.

The course is run in conjunction with SAS, a market leader in business analytics software and services, and the largest independent vendor in the business intelligence market.

Brunel's course is unique in being the only current MSc programme that is fully integrated with SAS, providing the SAS base certification.

The practical aspects of many of the modules will allow you to gain hands-on experience of several commercial SAS tools (e.g. SAS BASE, Enterprise Guide, Enterprise Miner and Visual Analytics). This experience is designed, in part, to develop skills in preparation for the SAS certification part of the programme. You will have the opportunity to obtain an SAS certificate such as SAS Base Programming, which is a recognised industry qualification, following a two-week SAS certification ‘boot camp’.

The roles that our graduates are typically recruited to within these organisations include analytics consultant, big data engineer/scientist, business analyst, clinical data scientist, data design specialist, data scientists, developer/development engineer, enterprise/technical architect, forecast analyst, marketing/customer and/or insight analyst, quantitative analyst and web analyst.

Brunel’s Women in Engineering and Computing mentoring scheme provides our female students with invaluable help and support from their industry mentors.

Enquiries

Contact our Enquiries team.
Course Enquiries: +44 (0)1895 265599 (before you submit an application)
Admissions Office: +44 (0)1895 265265 (after you submit an application)


Course content

This incredibly relevant and current course will equip you with all the skills you need to venture out into the world of analytics and big data.

Compulsory modules

Digital Innovation

Learn about the implementation of digital business models and technologies intended to realign an organisation with the changing demands of its business environment (or to capitalise on business opportunities). Example topics of study include: understanding and justifying change, change management, digital business models, managing technology risks, ethical issues in change. 

Quantitative Data Analysis

Gain an understanding of the quantitative data analysis methods that underpin data science. You’ll learn compulsory methods in data science application and research like bi-variate and multi-variate methods, as well as regression. You will also learn to evaluate the strengths and weaknesses of methods alongside an understanding of how and when to use or combine methods.

High Performance Computational Infrastructures

Work effectively with large-scale data storage and processing infrastructures, developing both practical skills and an ability to reflect critically on concepts, theory and appropriate use of infrastructure. Content covers, highly-scalable data-storage paradigms (e.g. NoSQL data stores) alongside cloud computing tools (e.g. Amazon EC2) and in-memory approaches.

Systems Project Management

Explore the challenges in information systems project management. Example topics of study include traditional project management techniques and approaches, the relationship between projects and business strategy, the role and assumptions underpinning traditional approaches, and the ways in which the state-of-the-art can be improved.

Big Data Analytics

Develop the reflective and practical approaches necessary to extract value and insight from large heterogeneous data sets. Focus is placed on the analytic methods, techniques, and algorithms for generating value and insight from real-time processing of heterogeneous data. Content will cover approaches to data mining alongside machine learning techniques (e.g. clustering, regression, support vector machines, boosting, decision trees and neural networks).

Research Methods

An introduction to methods of data collection and analysis when conducting empirical research. You can choose to carry out this research in an organisational setting, both in the private or the public sector. This module is essential preparation for your dissertation.

Data Visualisation

Understand how to visually present insight drawn from large heterogeneous data sets (e.g. to decision-makers). Content will provide an understanding of human visual perception, data visualisation methods and techniques, dashboard and infographic design, and augmented reality. An emphasis is also placed on visual storytelling and narrative development.

Learning Development Project

Research and develop a team-based integrative solution to a challenge drawn from the business, scientific and/or social domain. Working together, you’ll refine a coherent set of stakeholder requirements from an open-ended problem. You’ll then develop a solution addressing those requirements that draws upon the knowledge and skills of the other modules within the programme, and effectively evaluate the solution (with stakeholders where appropriate).

Dissertation

Your dissertation is an opportunity to showcase subject specific skills and project management to potential employers. It also serves as valuable experience and a solid building block if you wish to pursue a PhD after the MSc. You will be encouraged to critically examine the academic and industrial contexts of your research, identify problems, and think originally when proposing potential solutions that serve to demonstrate and reflect your ideas.

As preparation for the dissertation, you’ll be given a grounding in both quantitative and qualitative methods of data collection and analysis appropriate to conducting empirical and/or experimental research.

Read more about the structure of postgraduate degrees at Brunel and what you will learn on the course.

Entry criteria 2019/20

  • A 2:2 or above UK Honours degree or equivalent internationally recognised qualification from a scientific, engineering, or a numerate subject.
  • Applicants with other qualifications and industrial experience (relevant to the subject area) may be considered, and will assessed on an individual basis. Industrial certifications may be taken into account (those provided by organisations such as Microsoft and Sun). Such applicants may be required to attend an interview.

Entry criteria are subject to review and change each academic year.


International and EU entry requirements

If your country or institution is not listed or if you are not sure whether your institution is eligible, please contact Admissions

This information is for guidance only by Brunel University London and by meeting the academic requirements does not guarantee entry for our courses as applications are assessed on case-by-case basis.

English language requirements

  • IELTS: 6.5 (min 6 in all areas)
  • Pearson: 58 (51 in all subscores)
  • BrunELT: 65% (min 60% in all areas)

You can find out more about the qualifications we accept on our English Language Requirements page.

If you require a Tier 4 visa to study in the UK, you must prove knowledge of the English language so that we can issue you a Certificate of Acceptance for Study (CAS). To do this, you will need an IELTS for UKVI or Trinity SELT test pass gained from a test centre approved by UK Visas and Immigration (UKVI) and on the Secure English Language Testing (SELT) list. This must have been taken and passed within two years from the date the CAS is made.

Should you wish to take a pre-sessional English course to improve your English prior to starting your degree course, you must sit the test at an approved SELT provider for the same reason.

We offer our own BrunELT English Test and have pre-sessional English language courses for students who do not meet requirements or who wish to improve their English. You can find out more information on English courses and test options at the Brunel Language Centre.

Teaching and learning

Our Data Science and Analytics master's programme aims to equip you with the qualities and transferable skills necessary for employment. The course is developed with industry in mind and has one or more industrial advisers who are involved in course development and delivery.

Modules are typically taught via lectures and seminars with some lab work. Where appropriate other teaching methods will also be incorporated. All learning is supported by the market leader in Virtual Learning Environments (VLE), the Blackboard Learn system.

Should you need any non-academic support during your time at Brunel, the Student Support and Welfare Team are here to help.

Assessment and feedback

Your progress will be evaluated through a combination of in module assessments and exams. There will also be module specific assessments, for example presentations within the Learning Development Project.

Read our guide on how to avoid plagiarism in your assessments at Brunel.

Fees and funding

Fees for 2019/20 entry

UK/EU students: £10,140 full-time; £5,070 part-time

International students: £18,720 full-time; £9,360 part-time

Some courses incur additional course related costs. You can also check our on-campus accommodation costs for more information on living expenses.

Read about funding opportunities available to postgraduate students

UK/EU students can opt to pay in six equal monthly instalments: the first instalment is payable on enrolment and the remaining five by Direct Debit or credit/debit card.

Overseas students can opt to pay in two instalments: 60% on enrolment, and 40% in January for students who commence their course in September (or the remaining 40% in March for selected courses that start in January).

Fees quoted are per year and may be subject to an annual increase. Home/EU undergraduate student fees are regulated and are currently capped at £9,250 per year; any changes will be subject to changes in government policy. International and postgraduate fees will increase annually in line with RPI, or 5%, whichever is the lesser.

There is a range of financial support available to help you fund your studies. Find out about postgraduate student funding options.