Data Analytics MSc
Queen Mary University of London, United Kingdom
Master of Science in Data Analytics
Queen Mary, University of London
Data Analytics
Program Overview: MSc Data Analytics at Queen Mary
The MSc Data Analytics at Queen Mary University of London is a dynamic, industry-focused programme housed within the School of Mathematical Sciences. It teaches 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 with applications in finance, business, and science.
In the first semester, you will complete compulsory modules that provide a foundation in data analytics, machine learning, and the statistics of data analysis. In the second semester, you choose from one of three specialisation streams — Applied Machine Learning, Pattern Recognition and Deep Learning, or Statistical Inference — tailoring your education to your career aspirations.
The programme culminates in a summer research project where you work alongside researchers to consolidate your learning and apply your skills in a practical setting. You will be taught by experienced educators, including former industry practitioners, Fellows of the Alan Turing Institute, and members of Queen Mary's Institute of Applied Data Science.
Key Program Highlights
- Three specialisation streams allowing you to tailor your studies toward Applied Machine Learning, Pattern Recognition and Deep Learning, or Statistical Inference
- Hands-on programming skills in Python, R, and C++ using industry-standard tools and Bloomberg terminals in dedicated MSc computer labs
- Taught by Fellows of the Alan Turing Institute for Data Science and AI, alongside former industry practitioners from investment banking and consultancy
- Summer research dissertation project (60 credits) applying data analytics skills to a real-world research challenge
Curriculum and Modules
The MSc Data Analytics programme is structured across three semesters. Semester A covers compulsory foundation modules, Semester B offers compulsory and elective modules based on your chosen stream, and Semester C is devoted to your final research project dissertation.
Probability and Statistics for Data Analytics
15 UK CreditsCovers the probabilistic and statistical foundations underpinning the MSc Data Analytics, including probability theory, distributions of random variables, and statistical hypothesis testing for applications in science, business, and economics.
Machine Learning with Python
15 UK CreditsIntroduces core machine learning concepts and algorithms, with practical implementation using Python. You will explore supervised and unsupervised learning techniques applied to real-world datasets.
Data Analytics and Visualisation
15 UK CreditsDevelops your ability to manipulate, analyse, and visualise large datasets using industry-standard tools. Emphasises extracting clear insights and communicating findings effectively.
Statistical Data Modelling
15 UK CreditsCovers advanced statistical modelling techniques essential for data analysis, including regression methods, model selection, and inference for structured and unstructured data.
Deep Learning and Neural Networks
15 UK CreditsIntroduces state-of-the-art methodologies for machine learning with neural networks, including recurrent NNs, autoencoders, and transformers, with practical implementation in Python and PyTorch on real datasets.
MSc Data Analytics Research Project
60 UK CreditsA substantial independent research dissertation spanning the summer semester. You select a research-level topic in data analytics and produce a 30-50 page dissertation, which may involve programming, computation, and analysis of real datasets.
Elective Modules (Stream-Dependent)
Admission Requirements
The MSc Data Analytics programme welcomes numerate students with an interest in problem solving and some understanding of probability or statistics. No prior programming expertise is required, as you will develop these skills during the programme. All applications are processed through Uni4Edu.
Academic Requirements
- Minimum Degree ClassificationA good 2:2 (55% or above) or above at undergraduate level
- Subject BackgroundDegree in a subject with substantial mathematical content, including Mathematics, Statistics, Physics, or related disciplines
- International EquivalencyInternational qualifications assessed on a case-by-case basis; contact Uni4Edu for guidance on equivalency
- Work ExperienceNot required, but relevant professional experience may strengthen your application
- Programming SkillsNo prior programming expertise required; skills are developed during the programme
English Language Requirements
- IELTSOverall 6.5, with a minimum of 6.0 in Writing and 5.5 in Reading, Listening, and Speaking
- TOEFL iBTContact Uni4Edu for accepted scores and equivalencies
- PTE AcademicOverall 71, with minimum component scores as specified by the university
Required Documents
Application Deadlines
For personalized admission guidance, document verification, and application support, please contact Uni4Edu
Scholarships and Funding
Queen Mary University of London offers a range of scholarships for international postgraduate students. These merit-based awards can significantly reduce the cost of your studies. Uni4Edu can help you identify and apply for the funding opportunities most relevant to your profile.
President's Global Scholarship
GBP 10,000Available to highly qualified international postgraduate taught offer holders with a UK first-class honours degree or equivalent. Up to 20 awards are offered for the September 2026 intake, with a deadline of 17 April 2026. Contact Uni4Edu to check your eligibility.
Global Talent Scholarship (Postgraduate)
GBP 5,000Open to all international students with an offer for an eligible postgraduate taught programme. This merit-based award is available on a first-come, first-served basis for high-achieving students. Contact Uni4Edu for application details.
Global Excellence Scholarship (Postgraduate)
GBP 7,000Designed to recognise outstanding international students joining Masters programmes. Available to high-achieving offer holders for eligible postgraduate taught programmes in September 2026/27. Contact Uni4Edu for eligibility criteria.
For detailed tuition fee information, please contact Uni4Edu — we will guide you through the costs and available funding options for this program.
Career Prospects
Graduates of the MSc Data Analytics programme are well-positioned for high-demand roles across multiple sectors. In today's data-driven economy, organisations actively seek professionals who can extract clear insights from complex datasets. Queen Mary graduates benefit from strong employer connections in London's thriving financial and technology sectors.
Typical Graduate Roles
Top Employers of Graduates
Rankings and Recognition
Queen Mary University of London is a member of the prestigious Russell Group of research-intensive UK universities and has demonstrated strong upward momentum in global rankings. The university is recognised for its research quality and commitment to academic excellence across multiple disciplines.
| Subject | Ranking Body | Rank |
|---|---|---|
| Data Science and AI | QS World University Rankings by Subject | Top 100 |
| Mathematics | QS World University Rankings by Subject | Top 100 |
| Research Quality (UK) | REF 2021 | Joint 7th in UK (92% internationally excellent or world-leading) |
| Engineering and Computer Science | THE Subject Rankings | 126-150 globally |
How to Apply
Applying for this program is easy with Uni4Edu. Our team will guide you through every step of the process — from document preparation to final enrolment.
Contact Uni4Edu
Reach out to our team via email or phone. We will assess your profile and confirm your eligibility for this program.
Prepare Your Documents
Our advisors will provide you with a personalised checklist of required documents and help you prepare your application package.
Submit Your Application
Uni4Edu will submit your application on your behalf and keep you updated on its progress throughout the review period.
Receive Your Offer
Once accepted, we will help you understand your offer, arrange visa support if needed, and guide you through the enrolment process.
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