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APPLY

Masters

Queen Mary University of London

Applied Statistics and Data Science MSc

Name: Applied Statistics and Data Science MSc
Price: £12850 GBP

QUEEN MARY UNIVERSITY OF LONDON

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Different course options
Key information
Course Summary
Modules
Tuition fees
Entry requirements
University information
Location
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Different course options

Full time | Mile End | 12 months | SEP-25

Study mode

Full time

Duration

12 months

Start date

SEP-25

Key information
DATA SOURCE : IDP Connect

Qualification type

MSc - Master of Science

Subject areas

Data Science Applied Statistics

Course Summary

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.

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.

What you'll study

You will learn the core fundamentals of statistics and machine learning, together with the relevant software. You will also learn about applications of these methods in areas such as business, biostatistics, medical statistics and survey sampling. This programme is delivered across three semesters.

During the third semester, over the summer, you will work on a research project which will allow you to develop strong applied data science research skills.

Modules

Applied Statistical Modelling (15 Credits) - Core

The module aims to provide students with a solid understanding of the theory and applications of the General Linear Models as used in modern Statistical Applications. This framework of models consists of a generalisation of linear regression that includes more general response variables such as binary, multinomial, ordinal, Poisson random variables amongst others where the underlying parameters or a function of them depend in linear fashion of the input variables. The module will provide an introduction to the basic techniques in these advanced topics. Including a review of linear and logistic regression and will progress onto how this model can be extended to more general random variables.

Applied Statistics and Data Science Dissertation (60 Credits) - Core

Computational Statistics with R (15 Credits) - Core

Probability and Statistics for Data Analytics (15 Credits) - Core

Advanced Machine Learning (15 Credits)

Machine Learning with Python (15 Credits)

Storing, Manipulating and Visualising Data (15 Credits)

Time Series (15 Credits)

Time Series Analysis for Business (15 Credits)

Tuition fees

UK fees

Course fees for UK students

For this course (per year)

£12,850

International fees

Course fees for EU and international students

For this course (per year)

£33,500

Entry requirements

Degree requirements

A good 2:2 or above at undergraduate level in a Science, Technology, Engineering or Mathematics (STEM) subject.

Applicants with a 2:1 in any other subject can also be considered provided the degree contains satisfactory study in mathematics or statistics.

University information

Queen Mary University of London-Overview

Uni profile Get prospectus

Queen Mary University of London (QMUL) is an internationally regarded public research institution based in London. It has a long history, dating back over 230 years, and is a member of the prestigious Russell Group of universities. Queen Mary has five campuses in the city of London and an international network of satellite campuses in China, Malta, Paris and Singapore. There is a population of around 16,000 students at the London campuses and...more

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