Overview
In the second semester, you will decide on your specialism. This part of the Data Analytics MSc programme offered at Queen Mary University of London has been designed to prepare you for specific career paths, so what you study will depend on what you wish to do in the future.
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.
- Build a solid foundation in mathematics and statistics, setting you up for long-term career success.
- Develop sought-after programming skills, working with Python, R and C++.
- Apply what you learn to real-world datasets from a wide variety of sectors.
- Learn from experienced educators, including industry practitioners and Fellows of the Alan Turing Institute for Data Science and AI.
- Choose your own specialism to develop the professional skills you need for the job you want.
What you'll study
In the first semester, you will complete the compulsory modules that provide a foundation in data analytics, machine learning, and the statistics of data analysis. You will build upon this knowledge working with industry-standard tools and software.
Our specialisms, also known as streams, can be found below. We've highlighted the skills you will develop and the potential career paths for each stream.
Get more details
Visit programme websiteProgramme Structure
Courses included:- Financial Data Analytics
- Storing, Manipulating and Visualising Data
- Machine Learning with Python
- Probability and Statistics for Data Analytics
- Project Dissertation
Check out the full curriculum
Visit programme websiteKey information
Duration
- Full-time
- 12 months
- Part-time
- 24 months
Start dates & application deadlines
- Starting
- Apply before , International
- Apply before , National
-
Language
Prepare for Your English Test
AI-powered IELTS feedback. Clear, actionable, and tailored to boost your writing & speaking score. No credit card or upfront payment required.
- Trusted by 300k learners
- 98 accuracy using real exam data
- 4.9/5 student rating
Credits
Delivered
Campus Location
- London, United Kingdom
Disciplines
Data Analytics View 240 other Masters in Data Analytics in United KingdomExplore more key information
Visit programme websiteWhat students do after studying
Academic requirements
English requirements
Prepare for Your English Test
AI-powered IELTS feedback. Clear, actionable, and tailored to boost your writing & speaking score. No credit card or upfront payment required.
- Trusted by 300k learners
- 98 accuracy using real exam data
- 4.9/5 student rating
Other requirements
General requirements
- A good 2:2 (55% or above) or above at undergraduate level in a subject with substantial mathematical content, including Mathematics, Statistics, Physics, Engineering, Economics and Computer Science.
Make sure you meet all requirements
Visit programme websiteTuition Fees
-
International Applies to you
Applies to youNon-residents35250 GBP / year≈ 35250 GBP / year -
Domestic Applies to you
Applies to youCitizens or residents13250 GBP / year≈ 13250 GBP / year
Living costs
London
The living costs include the total expenses per month, covering accommodation, public transportation, utilities (electricity, internet), books and groceries.
Funding
Check for any work restrictions
Visit programme websiteIn order for us to give you accurate scholarship information, we ask that you please confirm a few details and create an account with us.
Scholarships Information
Below you will find Master's scholarship opportunities for Data Analytics.
Available Scholarships
You are eligible to apply for these scholarships but a selection process will still be applied by the provider.
Read more about eligibility
Read more about eligibility
Read more about eligibility
Read more about eligibility
Read more about eligibility
Read more about eligibility
Read more about eligibility
Read more about eligibility
Read more about eligibility
Read more about eligibility
Read more about eligibility
Read more about eligibility
Read more about eligibility
Read more about eligibility
Read more about eligibility
Read more about eligibility
Read more about eligibility
Read more about eligibility
Read more about eligibility
Read more about eligibility
Read more about eligibility
Read more about eligibility
Read more about eligibility
Read more about eligibility
Read more about eligibility
Read more about eligibility
Read more about eligibility
Read more about eligibility
Read more about eligibility
Read more about eligibility
Read more about eligibility
Read more about eligibility
Read more about eligibility
Read more about eligibility
Read more about eligibility
Read more about eligibility
Read more about eligibility
Read more about eligibility
Read more about eligibility
Read more about eligibility
Read more about eligibility
Read more about eligibility
Read more about eligibility
Read more about eligibility
Read more about eligibility
Read more about eligibility
Read more about eligibility
Read more about eligibility
Read more about eligibility
Read more about eligibility
Read more about eligibility
Read more about eligibility
Read more about eligibility
Read more about eligibility
Read more about eligibility
Read more about eligibility
Read more about eligibility
Read more about eligibility
Read more about eligibility
Read more about eligibility
Read more about eligibility
Read more about eligibility
Read more about eligibility
Read more about eligibility
Read more about eligibility
Read more about eligibility
Read more about eligibility