Who is this degree for:

This programme is optimised for you to build the skills for long-term career success in the field. You’ll graduate as a highly numerate data expert who can use statistical techniques and the latest technologies to extract clear insights and inform strategy and operations for a wide array of businesses—from financial corporations to AI start-ups, and across the technology, retail, and healthcare industries.

Cohorts and Deadlines:

The next cohort information will be updated soon.

Requirements for admission

You should carefully check the admissions requirements prior to starting your application. If you meet the requirements, you can log on to the QMUL application portal where you will be taken through a series of steps to provide details of your suitability for the programme. You will also upload your supporting documentation. If an unconditional offer is made and accepted, you will be asked to enroll and pay the required fee. At this point, you will become a student of QMUL and be enrolled in the programme on Coursera.

Click here to see if you meet the programme requirements.

Education and work experience

To gain admission to the programme, you must have:

  • A 2.1 degree in a subject with a substantial mathematical component, including, but not limited to: Mathematics, Statistics, Physics, Computer Science, Economics, Finance, Information Technology, and more.


  • A 2.2 degree in a subject with a substantial mathematical component, plus three years of work experience in a role with substantial statistical reporting or data analytics.

English Language requirements

You can be admitted if:

  • You are a native English speaker


  • You meet the IELTS/TOEFL standard requirements for international students. (6.5 overall, including 6.0 in Writing, and 5.5 in Reading, Listening and Speaking)

Evidence required: Your certificate, if the latter.


The programming language of choice in this programme is Python. A working knowledge of Python will be expected.

Evidence required: Self-declared.

MSc Applied Data Analytics events:

August 9, 2022

May 31, 2022

Coursera does not grant credit, and does not represent that any institution other than the degree granting institution will recognise the credit or credential awarded by the institution; the decision to grant, accept, or transfer credit is subject to the sole and absolute discretion of an educational institution.

We encourage you to investigate whether this degree meets your academic and/or professional needs before applying.