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Data Analytics MSc (PGCert PGDip)

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  • Course
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Intro

Developed to meet the demand for data science professionals, our postgraduate Data Analytics course enables you to effectively structure, analyse and gain insight from a wide range of complex data across different industries.

Your learning is informed by current business developments through case studies looking at real-world data sets, research questions and scenarios. You have the opportunity to collaborate on projects with our industry partners, and can also use your own data, project ideas and industry links.

You will develop a skill set in specialist data analytics and associated software, quantitative methods and techniques, and business intelligence. Our staff are experts in their field and you have the chance to develop your knowledge in specialist areas where we have ongoing research and expertise, such as sequential forecasting, natural language processing and image processing.

Whether you are a recent graduate or an experienced professional wanting to gain data analysis skills, this course is available on a full or part-time basis to help you manage your studies around other commitments. 

Key facts

Location Brighton: Moulsecoomb

Full-time 1 year
Part-time 2–6 years

Join an online event

Apply online

Please review the entry requirements carefully and if you have any questions do get in touch with us.

Apply now for your place

Course content

How this course is delivered

We've made some changes to the way our courses are taught to keep everyone safe, connected and involved in university life.

At the moment, students have a blend of on-campus and digitally enabled remote learning that provides lots of opportunities to interact and engage with lecturers and other students.

Find out what these changes mean for this course

Course structure

The course covers three main areas:

  • data management – structuring and manipulating data for analysis purposes
  • data interpretation – statistical analysis using advanced features of industry-standard software such as SAS, SPSS and R
  • project management – the business-specific and strategic aspects of analytics.

You will learn how to assess project viability, propose sound business cases and strategies for analysis, perform and oversee analysis and manage large data projects successfully as well as developing your critical appraisal and presenting techniques. 

SAS logo

Our mathematics department has SAS Academy status. SAS is one of the largest providers of business analytics software in the world. Academy status gives our students the opportunity to meet SAS customers and their industry partners at careers fairs, to train in skills needed by a wide range of companies and organisations, and to be prepared for SAS certification exams. 

Syllabus

You will study five core modules. One of these involves a major project, potentially in collaboration with industry. You will also choose option modules allowing you to focus on particular areas of interest.

Core modules

  • Data Management – provides an understanding of contemporary database management systems. Explores a methodology for database design and development, and develops skills in searching, reporting and analysing the data. Topics covered include database implementation and administration, data modelling and business intelligence.
  • Programming for Analytics – provides competencies in computer programming and algorithm design with emphasis on statistical programming and data analysis. The module covers both general issues of algorithm design and data structures and implementation issues in R and SAS.
  • Data Visualisation and Analysis – covers principles of data visualisation and specialised tools for data visualisation and analysis such as SAS Visual Analytics and Qlikview. The module also explores the mathematical and statistical theory behind data analysis.
  • Business Analytics Strategy and Practice – develops analytics-specific project planning concepts within this context, enabling students to design and manage analytics projects and present the business case to senior management.
  • Industry project – substantial, independent project undertaken with the supervision of a member of the teaching team. Projects are normally industry-based using real data sets.

Option modules*

  • Multivariate Analysis and Statistical Modelling – design statistical experiments, analyse multivariate data and apply classical and modern statistical modelling techniques. Enhances skills in the use of specialist software such as R, SPSS or SAS.
  • Stochastic Methods and Forecasting – an understanding of stochastic models and their applications in a business context. The module also covers forecasting methods with the emphasis on selecting the best forecasting method for a business problem and correct application of that method.
  • Data Mining and Knowledge Discovery in Data – find useful and relevant patterns, trends and anomalies in data sets, and summarise them in a form which may be used to support enterprise decisions – one of the great challenges of the information age. Emphasis is on the big, real-world picture rather than inside-the-box systems design engineering details. 
  • Risk Analysis and Retail Finance – introduction to the statistical methods used to estimate risk and reward in retail credit. The focus is on retail finance especially the provision of credit and lending services.
  • Medical Statistics – introduction to the methods originally designed for clinical trials and now being used in other contexts including sociology and marketing research. Topics include assessment of risk factors, comparing treatments and assessing survival data.

*Option modules are indicative and may change, depending on timetabling and staff availability.

Student projects 

Examples of student projects include:

  • Predicting patterns in relation to data involved in mobile gaming
  • Factors affecting visitor behaviour and visitor numbers to the Royal Pavilion, Brighton
  • The effects of Tommy John surgery on major league baseball pitchers
  • Automatic classification of students’ free-text responses in NSS and BSS surveys
Students on computer working

Staff profile

Dr Alexey Chernov

Dr Alexey Chernov, is a Senior Lecturer in the Division of Mathematical Sciences, School of Computing, Engineering and Mathematics. He has been the course leader for the MSc Data Analytics since October 2017.

Being a mathematician by education, Dr Chernov researches mathematical foundations of machine learning and artificial intelligence and teaches a wide range of mathematical and statistical courses.

He also collaborates with academic and non-academic partners on data analysis applied to practical problems. Dr Chernov is a member of Centre for Secure, Intelligent and Usable Systems, Mathematics, Statistics and Operations Group and Applied Data Analytics Research and Enterprise Group at the University of Brighton.

Dr Alexey Chernov's full profile

Alexey Chernov

Associate Professor Anya Belz

Associate Professor Anya Belz researches in natural language processing, specialising in language generation, evaluation, and most recently image description and text analytics for pharmacovigilance. 

She is the head of the Applied Data Analytics Research and Enterprise Group, which develops methods for turning the vast quantities of data we now generate daily into information, and ultimately knowledge, that can be used to help people lead healthier lives at all ages, enrich user experiences, add value to businesses, and optimise manufacturing processes.

Associate Professor Anya Belz's full profile

Anya Belz

Dr Anestis Touloumis, senior lecturer in statistics

Dr Anestis Touloumis's research focuses on the development of novel statistical methods and R software. His work is often motivated from multidisciplinary collaborations, mainly with scientists from medical, biological, and computer science disciplines. In particular, he applied his methods to glioblastoma studies and empirical studies in diagrammatic logic.

Dr Anestis Touloumis's full profile

Dr Anestis Touloumis

Careers

Prepare for your career 

In your career you need a combination of knowledge, skills, personal qualities and relevant experiences – and you’ll get all of this from your degree. 

  • With a flexible timetable to suit full-time or part-time students and commuters, and lecturers available to support you in your module choices, there are different study routes available to you.
  • Build advanced research, analytical and communication skills through working on your dissertation.
  • You will have access to computer and research labs equipped with specialist, sophisticated software including SAS, SPSS Statistics, SPSS Modeller, R, RStudio, Minitab, Maple and Matlab. 
Students presenting their ideas to industry

Industry links 

  • The course is designed in close consultation with industry partners including the NHS Business Services Authority, Teradata, BT, SAS, the Pensions Regulator and local Brighton companies.
  • Guest lecturers will share their knowledge and expertise with you, such as Tom Khabaza who is a founding chairman of the Society of Data Miners, author of 9 Laws of Data Mining and was involved in designing the course.

Graduate destinations 

A wide variety of organisations rely on data analytics specialists to produce valuable information for decision-making, for example commodity price forecasting, customer intelligence, clinical trials, R&D and many other areas utilising large amounts of data.

Graduate destinations include:

  • government bodies such as the Pensions Regulator and local councils
  • transnational corporations such as Capgemini
  • local companies such as iCrossing.

Entry criteria

Entry requirements

Degree and experience
Normally a 2:2 degree in a subject area with a substantial quantitative element (for example, maths, statistics, computer science, engineering, economics). Alternatively a 2:1 degree in any subject area will be considered if the applicant can demonstrate some familiarity with and aptitude for mathematics and statistics concepts and methods.

Claims for the accreditation of prior (experiential) learning will also be considered.

English language requirements
IELTS 6.5 overall with a minimum of 5.5 in each element. Find out more about the other English qualifications that we accept.

International students whose language skills do not match the IELTS scores set out here should consider applying for this course through the Extended Masters programme at the university's Language Institute.

International requirements and visas

International requirements by country
Country name
Albania
Algeria
Argentina
Australia
Austria
Bahrain
Bangladesh
Belarus
Belgium
Bermuda
Bosnia and Herzegovina
Botswana
Brazil
Bulgaria
Burma (Myanmar)
Cameroon
Canada
Chile
China
Colombia
Croatia
Cyprus
Czech Republic
Denmark
Ecuador
Egypt
Estonia
Finland
France
Germany
Ghana
Greece
Guyana
Hong Kong
Hungary
Iceland
India
Indonesia
Iran
Iraq
Ireland
Israel
Italy
Jamaica
Japan
Jordan
Kazakhstan
Kenya
Kosovo
Kuwait
Latvia
Lebanon
Liechtenstein
Libya
Lithuania
Luxembourg
Macedonia
Malaysia
Malawi
Malta
Mexico
Moldova
Montenegro
Morocco
Namibia
Nepal
Netherlands
New Zealand
Nigeria
Norway
Oman
Pakistan
Palestinian National Authority
Philippines
Poland
Portugal
Qatar
Romania
Russian Federation
Saudi Arabia
Serbia
Sierra Leone
Singapore
Slovakia
Slovenia
South Africa
South Korea
Spain
Sri Lanka
Syria
Sweden
Switzerland
Taiwan
Tanzania
Thailand
Tunisia
Turkey
Uganda
Ukraine
United Arab Emirates
United States
Uzbekistan
Venezuela
Vietnam
Yemen
Zambia
Zimbabwe

We can help you meet our English language or academic entry requirements.

Visit our language centre

For English language preparation courses.

Visit our International College

For degree preparation courses.

Visas and immigration advice

Applying for a student visa

Check out our step-by-step guidance.

Fees

Course fees

UK (full-time) 8,676 GBP

International (full-time)15,300 GBP


Scholarships, bursaries and loans

We offer a range of scholarships for postgraduate students. Bursaries and loans may also be available to you.

Find out more about postgraduate fees and funding.

What's included

You may have to pay additional costs during your studies. The cost of optional activities is not included in your tuition fee and you will need to meet this cost in addition to your fees. A summary of the costs that you may be expected to pay, and what is included, while studying a course in the School of Computing, Engineering and Mathematics are listed here.

  • You will have access to computers and necessary software, however many students choose to buy their own hardware, software and accessories. The amount spent will depend on your individual choices but this expenditure is not essential to pass any of our courses.
  • In most cases coursework submissions are electronic but students may wish to print notes which would involve an extra cost.
  • Costs of up to £50 are included in the fees for students on engineering courses to pay for materials for their final year projects. On rare occasions where material costs exceed £50, they will need to be paid for by the student.

You can chat with our enquiries team through the Stay in touch panel at the end of this page if you require further information. Or check our finance pages for advice about funding and scholarships as well as more information about fees and advice on international and island fee-paying status.

Info

The fees listed here are for full-time courses beginning in the academic year 2021–22.

Further tuition fees are payable for each subsequent year of study and are subject to an annual increase of no more than 5% or RPI (whichever is the greater). The annual increase for UK students, who are subject to regulated fees, will increase no more than the statutory maximum fee.

You can find out more about our fees in the university's student contract and tuition fee policy (pdf).

The tuition fee you have to pay depends on a number of factors including the kind of course you take, and whether you study full-time or part-time. If you are studying part-time you will normally be charged on a pro rata basis depending on the number of modules you take.

Location

Local area

About Brighton

The city of Brighton & Hove is a forward-thinking place which leads the way in the arts, technology, sustainability and creativity. You'll find living here plays a key role in your learning experience.

Brighton is a leading centre for creative media technology, recently named the startup capital of the UK.

The city is home to a national 5G testbed and over 1,000 tech businesses. The digital sector is worth over £1bn a year to the local economy - as much as tourism.

All of our full-time undergraduate courses involve work-based learning - this could be through placements, live briefs and guest lectures. Many of these opportunities are provided by local businesses and organisations.

It's only 50 minutes by train from Brighton to central London and less than 40 minutes to Eastbourne. There are also daily direct trains to Bristol, Bedford, Cambridge, Gatwick Airport, Portsmouth and Southampton.

Map showing distance to London from Brighton
Brighton Beach sunset

Campus where this course is taught

Moulsecoomb campus

Two miles north of Brighton seafront, Moulsecoomb is our largest campus. Subjects taught here include architecture, business, computing, construction, engineering, geography, product design, law and pharmacy.

On campus you will find professional-standard facilities including a flight simulator, trading room, design and digital media suites and specialist research laboratories, alongside the library, student centre, a nursery, fitness facilities and Students’ Union. There are excellent public transport links.

The Big Build
A major transformation of our Moulsecoomb campus began in summer 2018. By the time the Big Build is complete, there’ll be new halls of residence, academic building, and Students’ Union and fitness facilities – all created with sustainability, inclusivity and community in mind.

As the development grows it will provide many exciting learning opportunities for our students, ranging from live projects, placements and internships with the companies involved to guest lectures and site visits. Find out more...

The Big Build

Accommodation

Brighton: Moulsecoomb

We guarantee an offer of a place in halls of residence to all eligible students.

Halls of residence
We have halls of residence across Brighton in the city centre, Moulsecoomb, Varley Park and Falmer.

  • You'll be prioritised for accommodation in the halls that are linked to your teaching base, subject to availability.
  • Moulsecoomb campus is linked to Varley Park and Moulsecoomb Place halls. All halls are self catered, but if you prefer you can add in a food and drink plan.
    • Varley Park offers a mix of rooms. It is around two miles from Moulsecoomb campus and four miles from the city centre. Public transport in the city is excellent, and there’s a shuttle bus between our Brighton campuses during term time.
    • Moulsecoomb Place halls are all self-catered and are located right on campus.

Want to live independently or in a university-managed house? We can help – find out more about unihomes and unilets or private renting.

Modern accommodation at nearby Varley Halls

Modern accommodation at nearby Varley Park

Relaxing in halls near the campus

Relaxing in halls near the campus

Students eating at the Hub

Students eating at the Hub

Maps

Moulsecoomb campus map

Stay in touch

Join an online event

Ask a question about this course

If you have a question about this course, our enquiries team will be happy to help.

01273 644644

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