Data Science and Analytics MSc

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Course Overview

UK Fees £10,500 *
International Fees £17,000 *
Alumni Discount See details
Duration 1 year

* Price per academic year

Course summary

This course (previously Business Intelligence and Analytics MSc) addresses the need to propel information-gathering and data organisation, and exploit potential information and knowledge hidden in routinely collected data to improve decision-making. The course stretches the artificial intelligence (AI), machine learning (ML) and decision science themes to business intelligence, data science and business analytics.

You'll focus on developing solutions to real-world problems associated with the changing nature of IT infrastructure and increasing volumes of data, using applications and case studies, while gaining a deep appreciation of the underlying models and techniques. You'll also gain a greater understanding of the impact technological advances have on nature and practices adopted within data science, business intelligence and analytics, and how to adapt to these changes.

Embedded into the course are two key themes. The first will help you to develop your skills in the use and application of various technologies, architectures, techniques, tools, and methods for data science. These include data warehousing and mining, distributed data management, and the technologies, architectures, and appropriate AI and ML techniques. The second theme will enhance your knowledge of algorithms and the quantitative techniques including AI, ML, and Operational Research (OR) suitable for analysing and mining data and developing decision models in a broad range of application areas. The project consolidates the taught subjects covered, while giving you the opportunity to pursue in-depth study in your chosen area.

Teaching approaches include lectures, tutorials, seminars, and practical sessions. You will also learn through extensive coursework, class presentations, group research work, and the use of a range of industry-standard software such as R, Python, Simul8, Palisade Decision Tools, Tableau, and Oracle.

Modules are typically assessed through practical coursework, which may also include an in-class test.

Top reasons to study with us

  • Master key data science and analytics skills – You’ll develop your skills in the use and application of various technologies, architectures, techniques, tools, and methods, including data warehousing and mining, distributed data management, and appropriate AI and ML techniques
  • Develop your problem-solving skills – You’ll focus on developing solutions to real-world problems associated with the changing nature of IT infrastructure and increasing volumes of data, and gain a deep appreciation of the underlying models and techniques
  • Gain industry-insider knowledge – You’ll attend presentations from industry professionals and have the opportunity to go on site visits to see the work of data science and analytics teams
  • Get access to the essential software and languages – You’ll use a range of industry-standard software such as R, Python, SQL, Simul8, Palisade Decision Tools, Tableau, and Oracle
  • You'll enhance your knowledge of algorithms and quantitative techniques including Al, ML, Operational Research (OR), and Advanced Analytics suitable for analysing and mining data and developing decision models in a broad range of application areas

Course structure

MSc students take five core modules, including a project and two from the option modules.

The following modules are indicative of what you will study on this course.

Core modules

This is a self-contained module in applied statistics and operational research (OR) for decision making, which lays the foundations for more advanced modules in data mining, optimisation and simulation modelling. It covers the essential of descriptive, predictive and prescriptive analytics in an application-driven manner, and makes use of appropriate software tools such as EXCEL (including add-ins) and R to derive meaningful solutions.

This module will provide an overview of modern techniques in machine learning and data mining that are particularly customised for data science applications. You’ll be introduced to a range of toolkits, such as R and Python, and explore the features and strengths of different machine learning and data mining methodologies using selected data sets related to specific public sector or businesses application domains.

The module consolidates and extends the knowledge students acquired in the taught part course, encourages and rewards individual inventiveness and application of effort. You’ll be required to carry out and bring to fruition a comprehensive piece of individual work on an approved topic (relevant to your course of studies) that involves research, planning, critical evaluation, reflection activities. To provide appropriate foundational knowledge to support the project development, the module includes a series of four blended learning workshops.

This module covers the theoretical and practical aspects of data visualisation including graphical perception, dynamic dashboard visualisations, and static data ‘infographics’. Tools such as R and Tableau are used. The aim is to prepare students for becoming a data visualisation specialist.

Business Intelligence, Data Mining and Analytics are a set of methods and technologies that transform raw data into meaningful and useful information. A Data Warehouse is the architecture or structure that supports these activities. This module teaches students how to build Data Warehouses by understanding their structures and the concept of multi-dimensional modelling. The focus is on Data Warehouse design, multi-dimensional modelling, the integration of multi-source data and analysis, cloud-based data warehousing, NOSQL OLAP, aiming to support better business decision making.

Option modules

This module explores the use of modelling to analyse and measure both online presence and impact using web and social media data. You will learn how to listen to social media conversations taking place, how such data can be transformed into actionable insight for a brand or organisation. You will also study ways in which the effectiveness of modern websites is often judged and how online web metrics can be used to drive performance. The overriding aim of the module is to equip students with the necessary technical skills and industrial knowledge for a career in the area of web or social media marketing.

The module focuses on the choice and use of appropriate simulation modelling approaches to treat real-world problems, developing solution(s) using powerful simulation software and explaining the business and industrial implications thereof. Relevant applications to problems such as stock control, reliability, project management and service redesign will be considered in domains such as healthcare, supply-chain, and transport.

A hands-on module with highly technical content, it covers the underlying technologies and approaches used in capturing, maintaining and modelling persistent data; it addresses practical issues related to data modelling and database design; finally, it provides practical/hands on skills by introducing the features and constructs of SQL.

The module discusses how to manage the volume, velocity and variety of Big Data, SQL and noSQL databases, and it touches on issues related to data governance and data quality.

Professional accreditation

This course has been accredited by BCS, the Chartered Institute for IT, for the purposes of partially meeting the further learning academic requirement for registration as a Chartered IT Professional. The accreditation is a mark of assurance that the course meets the standards set by BCS and it entitles you to professional membership of BCS, which is an important part of the criteria for achieving Chartered IT Professional (CITP) status through the Institute. This course has also been accredited by BCS, on behalf of the Engineering Council, for the purposes of partially meeting the academic requirement for registration as a Chartered Engineer. The accreditation is a mark of assurance that the course meets the standards set by the Engineering Council in the UK Standard for Professional Engineering Competence (UK-SPEC). An accredited degree will provide you with some or all of the underpinning knowledge, understanding and skills for eventual registration as an Incorporated (IEng) or Chartered Engineer (CEng). Accreditation is valid for intakes to this course between September 2022 – August 2028.

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Programme specification

For more details on course structure, modules, teaching and assessment Download the programme specification (PDF).

To request an accessible version please email [email protected]

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Prospectus

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Get in touch

Contact us for general course enquiries:

+44 (0)20 7911 5000 EXT 65511
(Mon-Fri, 10am-3pm GMT)

[email protected]

Live chat with us
(Mon-Fri, 10am-4pm GMT)

Open evenings

Join us at an open evening online or on campus. Get a feel for student life at the University of Westminster and talk to course leaders and our support teams.

Careers

You'll focus on developing solutions to real-world problems associated with the changing nature of IT infrastructure and increasing volumes of data, and gain a deep appreciation of the underlying models and techniques, equipping you with the practical skills needed to become a data science and analytics specialist. 

Typically, graduates of this course will be employed as consultants, data scientists, decision modelling or advanced data analysts, members of technical/analytics teams supporting the decision making of middle and top management in a diverse range of sectors. 

With a growing global network of 3,000 employers, our Careers and Employability Service is here to support you to achieve your full potential.

Industry knowledge

You’ll attend presentations from industry professionals and have the opportunity to go on site visits to see the work of data science and analytics teams

Develop your problem-solving skills

You’ll develop solutions to real-world problems associated with the changing nature of IT infrastructure and increasing volumes of data, while gaining a deep appreciation of the underlying models and techniques.

Master key skills

You’ll develop further your logical, analytical and technical skills to become a data science and analytics specialist.

Job roles

This course will prepare you for roles such as: 

  • Ad Technology Manager
  • Big data architect 
  • Chief data officer
  • Data analyst
  • Data scientist
  • Enterprise data architect
  • Insights manager
  • Lead information analyst
  • Managing consultant
  • Revenue optimisation manager
  • Senior data scientist
  • Senior insight analyst
  • Technical insight analyst

Graduate employers

Graduates from this course have found employment at organisations including:

  • ACCA
  • AIMIA Inc
  • Amobee
  • Barclays
  • British Gas
  • Bumble
  • Cabinet Office
  • Chelsea and Westminster Hospital NHS Foundation Trust
  • Deloitte
  • Digital Contact
  • Emirates
  • EY
  • JATO
  • KPMG
  • Liv-Ex
  • NCR, USA
  • Points
  • PWC
  • Sainsbury's
  • Veolia Water
  • Virgin Media

Our graduates

Yunfei Chen

Data Science and Analytics MSc - 2022

The Business Intelligence and Analytics MSc has enabled me to get up to speed with the latest trends in the data science space. I've also had the opportunity to work with the NHS for my final project. Seeing that what I've learnt can bring real-world impact is more than something to put on your CV.

Vasiliki Tzortzidou

Vasiliki Tzortzidou

Data Science and Analytics MSc - 2021

Project Manager | Selected Interventions

I was overwhelmed with joy to see my dissertation mark. Not having seen code before in my life, graduating from the Business Intelligence and Analytics MSc (Data Science and Analytics MSc from 2022/23) with distinction is a huge accomplishment for me, and shows how effectively the course can guide us.

Olga Prisich

Data Science and Analytics MSc - 2021

My favourite part of the course was learning and applying new knowledge in practice. The assignments were focused on actual business problems, and I was able to not only strengthen my theoretical knowledge, but also to understand the applications of the methods from data analytics and machine learning in the industry.

Westminster Employability Award

Employers value graduates who have invested in their personal and professional development – and our Westminster Employability Award gives you the chance to formally document and demonstrate these activities and achievements.

The award is flexible and can be completed in your own time, allowing you to choose from a set of extracurricular activities. 

Activities might include gaining experience through a part-time job or placement, signing up to a University-run scheme – such as mentoring or teaching in a school – or completing online exercises.

Read more about our Westminster Employability Award.

Westminster Employability Award

Why study this course?

Study in central London

Based in our Cavendish Campus in central London, you’ll enjoy the benefits of studying in a major tech-hub.

Enhance your knowledge

You’ll gain a greater understanding of the impact technological advances have on nature and practices adopted within data science, business intelligence and analytics, and how to adapt to these changes.

Prepare for industry

You’ll use a range of industry-standard software such as R, Python, SQL, Simul8, Palisade Decision Tools, Tableau, and Oracle.

Entry Requirements

A minimum of a lower second class honours degree (2:2) in a scientific or engineering discipline with some exposure to the use of IT, or in an area of computer science or IT with a strong interest in quantitative analysis. If you do not have a formal qualification, but you are already in employment, you may be considered if your role involves the data mining and decision support techniques and technologies deployed in the course.

If your first language is not English, you should have an IELTS 6.5 with at least 6.5 in writing and no element below 6.0.

Applicants are required to submit one academic reference.

Recognition of prior learning and experience

If you have previously studied at university level, or have equivalent work experience, academic credit may be awarded towards your course at Westminster. For more information, visit our Recognition of Prior Learning page.

Application process 

Visit our How to apply page for more information on:

  • the application process
  • what you need to apply
  • deadlines for applications

A minimum of a lower second class honours degree (2:2) in a scientific or engineering discipline with some exposure to the use of IT, or in an area of computer science or IT with a strong interest in quantitative analysis. If you do not have a formal qualification, but you are already in employment, you may be considered if your role involves the data mining and decision support techniques and technologies deployed in the course.

If your first language is not English, you should have an IELTS 6.5 with at least 6.5 in writing and no element below 6.0.

Applicants are required to submit one academic reference.

Recognition of prior learning and experience

If you have previously studied at university level, or have equivalent work experience, academic credit may be awarded towards your course at Westminster. For more information, visit our Recognition of Prior Learning page.

Application process 

Visit our How to apply page for more information on:

  • the application process
  • what you need to apply
  • deadlines for applications

More information

University preparation courses

Our partner college, Kaplan International College London, offers Pre-Master’s courses that may help you gain a place on a postgraduate degree at Westminster.

To find out more, visit University preparation courses.

What our graduates say

Liza Layne

Lisa Layne

Data Science and Analytics MSc

Lead Business System Manager Enterprise Services Team (Business Intelligence, Content, Analytics and Data) | Eurostar

The programme I chose allowed me to refresh my data warehousing knowledge, extend my understanding in using statistics for forecasting and to learn new technologies and techniques.

By completing the MSc at Westminster, I gained clarity in my chosen career path, which helped me to secure a role at Eurostar. I recommend the programme to any professional interested in pursuing a career a business intelligence and analytics arena.

Kostas Kokkas

Kostas Kokkas

Data Science and Analytics MSc

Business Intelligence Analyst | Liberty Global

The MSc Business Intelligence and Analytics helped me massively to develop my career and find a very good job in a very prestigious organisation and improve my personal financial earnings. However, I think that the most beneficial was that I was able to discover the direction I wanted to take in my career and develop these skills while I was attending all these modules so that I can gain more practical experience in my job.

Colin Ridley's default avatar image

Colin Ridley

Data Science and Analytics MSc

Manager Revenue Optimisation | Emirates

The course did not just challenge and stretch me, but exposed me to such a variety of tools, concepts and systems that I have walked away, more prepared to face the challenges of an ever changing and complex business world.  In some respects it's like putting on 3D glasses for the first time and seeing angles, dimensions and views you would never have seen otherwise.

What our graduates say

Miryam Ben-chaim's default avatar image

Miryam Ben-chaim

Data Science and Analytics MSc - 2015

Data Architect | Equifax

I have been approached by numerous companies including MI5 and consulting firms since I added my masters to my CV. I have received a 40% increase in my salary from when I started the course to now, therefore pursuing the MSc has had a significant impact to my earning potential and opportunities.

Gabriel Averia

Data Science and Analytics MSc

The academic support was excellent. The course leaders were very approachable and always willing to go the extra mile to help us out. Whether it was providing further explanation on the topics that were covered during a lecture or suggestions on how to handle issues on a particular assignment, they were always happy to provide guidance to students.

Learn new skills

Volunteer and gain new skills

We offer a number of different volunteering opportunities for you to learn new skills, create connections, and make a difference in the community.

Develop your entrepreneurial skills

Our award-winning Westminster Enterprise Network offers industry networking events, workshops, one-to-one business advice and support for your start-up projects.

Get extra qualifications

We provide access to free online courses in Adobe and Microsoft Office applications, as well as thousands of specialist courses on LinkedIn Learning.

Fees and Funding

UK tuition fee: £10,500 (Price per academic year)

When you have enrolled with us, your annual tuition fees will remain the same throughout your studies with us. We do not increase your tuition fees each year.

Find out how we set our tuition fees.

Paying your fees

If you don't wish to pay the whole amount of your fees at once, you may be able to pay by instalments. This opportunity is available if you have a personal tuition fee liability of £2,000 or more and if you are self-funded or funded by the Student Loans Company.

Find out more about paying your fees.

Alumni discount

This course is eligible for an alumni discount. Find out if you are eligible and how to apply by visiting our Alumni discounts page.

Funding

There is a range of funding available that may help you fund your studies, including Student Finance England (SFE).

Find out more about postgraduate student funding options.

Scholarships

The University is dedicated to supporting ambitious and outstanding students and we offer a variety of scholarships to eligible postgraduate students.

Find out if you qualify for one of our scholarships.

Additional costs

See what you may need to pay for separately and what you tuition fees cover.

International tuition fee: £17,000 (Price per academic year)

When you have enrolled with us, your annual tuition fees will remain the same throughout your studies with us. We do not increase your tuition fees each year.

Find out how we set our tuition fees.

Paying your fees

If you don't wish to pay the whole amount of your fees at once, you may be able to pay by instalments. This opportunity is available if you have a personal tuition fee liability of £2,000 or more and if you are self-funded or funded by the Student Loans Company.

Find out more about paying your fees.

Alumni discount

This course is eligible for an alumni discount. Find out if you are eligible and how to apply by visiting our Alumni discounts page.

Funding

There are a number of funding schemes available to help you fund your studies with us.

Find out more about funding for international students.

Scholarships

The University is dedicated to supporting ambitious and outstanding students and we offer a variety of scholarships to eligible postgraduate students.

Find out if you qualify for one of our scholarships.

Additional costs

See what you may need to pay for separately and what you tuition fees cover.

Teaching and Assessment

Below you will find how learning time and assessment types are distributed on this course. The graphs below give an indication of what you can expect through approximate percentages, taken either from the experience of previous cohorts, or based on the standard module diet where historic course data is unavailable.  Changes to the division of learning time and assessment may be made in response to feedback and in accordance with our terms and conditions.

How you’ll be taught

Teaching methods across all our postgraduate courses focus on active student learning through lectures, seminars, workshops, problem-based and blended learning, and where appropriate practical application. Learning typically falls into two broad categories:

  • Scheduled hours: examples include lectures, seminars, practical classes, workshops, supervised time in a studio
  • Independent study: non-scheduled time in which students are expected to study independently. This may include preparation for scheduled sessions, dissertation/final project research, follow-up work, wider reading or practice, completion of assessment tasks, or revision
Year
1
13%87%
Scheduled hoursIndependent study

How you’ll be assessed

Our postgraduate courses include a variety of assessments, which typically fall into two broad categories:

  • Practical: examples include presentations, podcasts, blogs
  • Coursework: examples include essays, in-class tests, portfolios, dissertation
Year
2
4%96%
PracticalCoursework

Data from the academic year 2022/23

Research groups

Our research achieves real-world impact and we are proud to claim a rich and diverse profile of high-quality research and knowledge exchange in a wide range of disciplines.

Find out more about the following research group related to this course:

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Supporting you

Our Student Hub is where you’ll find out about the services and support we offer, helping you get the best out of your time with us.

  • Study support — workshops, 1-2-1 support and online resources to help improve your academic and research skills
  • Personal tutors — support you in fulfilling your academic and personal potential
  • Student advice team — provide specialist advice on a range of issues including funding, benefits and visas
  • Extra-curricular activities — volunteering opportunities, sports and fitness activities, student events and more

Visit our student hub

Course location

With state-of-the-art science and psychology labs and refurbished computer suites, our Cavendish Campus offers our science and technology students a range of learning spaces that are both dynamic and inspiring,

Located in central London, our Cavendish Campus is just a five-minute walk from Oxford Street and Tottenham Court Road.

For more details, visit our Cavendish Campus page.

Contact us

Call our dedicated team on:

+44 (0)20 7911 5000 ext 65511

Opening hours (GMT): 10am–4pm Monday to Friday

[email protected]

Start live chat

Opening hours (GMT): 10am–4pm Monday to Friday

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