Applied Statistics and Data Science
Entry requirements
A high 2:2 (55% or above) at undergraduate level in a Science, Technology, Engineering or Mathematics (STEM) subject.
Applicants with a high 2:2 (55% or above) in any other subject can also be considered provided the degree contains satisfactory study in mathematics or statistics.
Months of entry
September
Course content
Introduction
This programme moves on from traditional statistics degrees, providing modernised modules that meet the needs of industry today. You will be taught to harness the power of data and statistics in addition to learning analysis tools such as R and Python. The knowledge and skills you learn will provide you with a platform to work across a variety of industries, go into research or undertake a PhD.
Programme Highlights
- Become highly employable in the field of statistics across a variety of industries, including Big Pharma, Big Tech, clinical trials, psychology and Government agencies.
- Learn from academic experts across a number of fields such as statistics, finance and data analytics.
- Learn analysis tools such as R and Python.
- Opportunity to undertake an applied summer dissertation project.
Information for international students
English language requirements
If you got your degree in an English speaking country or if it was taught in English, and you studied within the last five years, you might not need an English language qualification - find out more.
Visas and immigration
Find out how to apply for a student visa.
Fees and funding
There are a number of ways you can fund your postgraduate degree.
- Scholarships and bursaries
- Postgraduate loans (UK students)
- Country-specific scholarships for international students
Scholarships information:
Visit our scholarships database to see what scholarships are available for this programme: https://www.qmul.ac.uk/scholarships/database/
Our Advice and Counselling service offers specialist support on financial issues, which you can access as soon as you apply for a place at Queen Mary. Before you apply, you can access our funding guides and advice on managing your money:
Qualification, course duration and attendance options
- MSc
- full time12 months
- Campus-based learningis available for this qualification
- part time24 months
- Campus-based learningis available for this qualification
Assessment
Assessment | What kind of work will I be doing? (proportionally) |
---|---|
Written/ formal examinations | 67 |
Dissertation | 33 |
Course contact details
- Name
- Kieran Hayde
- maths@qmul.ac.uk