Skip navigation
Search
Search
Data Science at Queen Mary University of London - UCAS

Course options

2024 - 20252025 - 2026
Apply

There are other course options available which may have a different vacancy status or entry requirements – view the full list of options

Course summary

This programme is designed to address the growing demand for highly skilled data scientists and engineers capable of combining advanced computer science techniques with modern statistical methods to extract insights and create data-driven services. We offer world-leading expertise and industry partnerships to equip students with essential skills in statistical data modeling, visualisation, machine learning, and domain-specific applications like computer vision and natural language processing. Programme Highlights:

  • Create new business services that are based on insights learnt from data.
  • Learn to create automated prediction, recommendation and classification systems.
  • Gain advanced mathematical and technical skills including machine learning and deep learning.
  • Benefit from our world-leading research as well as our strategic partnerships with leading technological companies.
You will cover fundamental statistical and analytical concepts (such as machine learning) and technological tools (such as cloud platforms, Spark) for large-scale data analysis. Through your taught modules, you will examine:
  • Statistical data modelling, data visualisation and prediction.
  • Machine learning techniques for cluster detection, and automated classification.
  • Techniques for processing massive amounts of data.
  • Domain-specific techniques for applying data science, including: computer vision, social media analysis, intelligent sensing and internet of things.
  • Case study-based projects that show the practical application of key skills in real industrial and research scenarios.
You will also undertake a large project where you will demonstrate the application of data science skills in a complex scenario. This degree is accredited by BCS, The Chartered Institute for IT, for the purposes of partially meeting the academic requirement for registration as a Chartered IT Professional. This degree is also accredited by BCS on behalf of the Engineering Council, for the purposes of partially meeting the academic requirement for registration as a Chartered Engineer.

Modules

Please refer to our website

Assessment method

Please refer to our website

How to apply

International applicants

Please see: www.qmul.ac.uk/international-students

Entry requirements

An upper second class degree is normally required, usually in electronic engineering, computer science, maths or a related discipline. Students with a good lower second class degree may be considered on an individual basis. Applicants with unrelated degrees will be considered if there is evidence of equivalent industrial experience.

English language requirements

All applicants to Queen Mary must show they meet a minimum academic English language standard for admission and to be successful on the course. Please refer to the website below for details on our English Language requirements by course and acceptable alternative qualifications. You will also find important information regarding UKVI's English requirements if you are applying as an international student and will require Tier 4 immigration permission to enter the UK.

Queen Mary University of London: English Language Requirements

http://www.qmul.ac.uk/international/englishlanguagerequirements

Fees and funding

Tuition fees

No fee information has been provided for this course

Tuition fee status depends on a number of criteria and varies according to where in the UK you will study. For further guidance on the criteria for home or overseas tuition fees, please refer to the UKCISA website .

Additional fee information

Students enrolling on a postgraduate degree programme are charged tuition fees each year by Queen Mary. The rate you will be charged depends on whether you are assessed as a Home/EU or Overseas student. You can find tuition fees for each course on the course finder pages on our website: https://www.qmul.ac.uk/postgraduate/ Further details about postgraduate taught tuition fees can also be found on our website: https://www.qmul.ac.uk/postgraduate/taught/tuitionfees/

Sponsorship information

Please see: www.qmul.ac.uk/scholarships

Data Science at Queen Mary University of London - UCAS