This Data Analytics MSc will teach you the core mathematical principles of data analysis and how to apply these to real world scenarios. Building on the statistical foundations of machine learning you’ll then choose from module options which explore the financial, business and scientific applications; such as in trading and risk systems, optimisation of business processes, and relationships across complex systems.
Data science is the driving force behind today’s most successful businesses. In our data-driven economy, companies are seeking highly numerate data experts who can use statistical techniques and the latest technologies to extract clear insights to inform every aspect of their strategy and operations. From financial corporations, to AI start-ups, and across the technology, retail and healthcare industries, highly sought-after Data Scientists can earn over £56k per year on average (according to Indeed.co.uk, UK figures).
Why study with us?
We’re looking for numerate students with an interest in problem solving and some understanding of probability or statistics. You don’t need to be a programming expert before you join us; you’ll get to discover a variety of industry-standard tools (such as R and Python) to allow you to choose which technologies you want to specialise in.
You’ll be taught by our expert academics, who include former industry practitioners with many years’ experience. Many of them are Fellows of the Alan Turing Institute and members of Queen Mary’s Institute of Applied Data Science.
Over the summer you will work on a research project in an area of interest, developing strong applied data science research skills and putting your learning into practice. You may choose to collaborate with one of our industry partners on a real-world data problem.
Choose one from:
Statistical Foundations of Data Science - choose a maximum of three modules from:
Financial Applications of Data Science - choose a maximum of two* modules from:
- Financial Data Analytics
- Optimisation for Business Processes
- SAS for Business Intelligence
- Time Series Analysis for Business
- Trading and Risk Systems Development
(*if you have taken Programming for Business Analytics in Semester A you may choose up to one from the above list in Semester B)
Scientific Applications of Data Science - choose a maximum of two modules from:
Please note that all modules are subject to change.
This programme is highly applied and will feature industry connections to help you put your learning into the context of real-world challenges. You will have the opportunity to develop your knowledge of a variety of industry standard technology tools, such as R and Python.
In the first semester you will learn the core fundamentals of Data Analytics, Machine Learning, and the statistics of data analysis together with some of the relevant technology.
In the second semester you can choose to specialise in your preferred area of interest, across the financial, business and scientific applications of Data Analytics.
The summer semester is the culmination of a year of learning when students will be involved in team projects in areas directly related to industry practice, and in some instances in direct collaboration with our industry partners.
The majority of our applicants will have an undergraduate degree with first class or upper second class honours (or international equivalent). Offers will typically be made at 2.1 level (upper second class) or equivalent. Students with a good lower second class degree may be considered on an individual basis. In some cases your offer may include additional conditions, such as minimum grades in specified modules, in order to ensure that you are sufficiently qualified for our MSc programmes.
Students applying to this programme should have studied a subject with a substantial mathematical component at the undergraduate level. We welcome those from a variety of relevant disciplines, including mathematics, statistics, physics, engineering, economics and computer science.
English language requirements
Students from outside of the UK help form a global community here at QMUL. For detailed country-specific entry requirements please visit the . If your first language is not English, you must provide evidence of your English language proficiency. Non-native English speakers are required to have minimum of IELTS 6.5 or equivalent. Find out more about our English language entry requirements. If you have not achieved the required English language level yet, you may be eligible to take a Pre-sessional English course, or continue to take English language tests in your country to reach the level needed. Visit: www.sllf.qmul.ac.uk/language-centre/presessionals
Learning and teaching
As a student at Queen Mary, you will play an active part in your acquisition of skills and knowledge. Teaching is by a mixture of formal lectures and small group seminars, designed to generate informed discussion around set topics.
We take pride in the close and friendly working relationship we have with our students. You are assigned an Academic Adviser who will guide you in both academic and pastoral matters throughout your time at Queen Mary.
Modules can be assessed by a mixture of coursework and examination. Examinations are held between May and early June on the modules taken. Dissertations are evaluated in September. Successful completion of the MSc programme will result in the award of the degree of MSc Data Analytics.
Tuition fees for Home and EU students2019/20 Academic Year
Full time £10,350
Part time £5,175
Tuition fees for International students2019/20 Academic Year
Full time £21,250
Part time £10,625
Part time fees are charged per annum over two years for a two year programme and per annum over three years for a three year programme. A percentage increase may be applied to the fees in years two and three.
This increase is defined each year and published on the intranet and in the Tuition Fee Regulations. A 3% increase was applied to the unregulated university fees in 2019/20. Further information can be viewed on our University Fees webpage, including details about annual increases.
There are a number of sources of funding available for Masters students.
These include a significant package of competitive Queen Mary University of London (QMUL) bursaries and scholarships in a range of subject areas, as well as external sources of funding.
Queen Mary bursaries and scholarships
We offer a range of bursaries and scholarships for Masters students including competitive scholarships, bursaries and awards, some of which are for applicants studying specific subjects.
Find out more about QMUL bursaries and scholarships.
Alternative sources of funding
Home/EU students can apply for a range of other funding, such as Professional and Career Development Loans, and Employer Sponsorship, depending on their circumstances and the specific programme of study.
Overseas students may be eligible to apply for a range of external scholarships and we also provide information about relevant funding providers in your home country on our country web pages.
Download our Postgraduate Funding Guide for detailed information about postgraduate funding options for Home/EU students.
Tel: +44 (0)20 7882 5079
Other financial help on offer at Queen Mary
We offer one to one specialist support on all financial and welfare issues through our Advice and Counselling Service, which you can access as soon as you have applied for a place at Queen Mary.
Our Advice and Counselling Service also has lots of Student Advice Guides on all aspects of finance including:
Tel: +44 (0)20 7882 8717