Study this course anywhere in the world and receive a fully accredited University of London degree

University of London

Small Navigation Menu

Primary Menu

Data Science

MSc, PGDip and PGCert Data Science

Learn how to apply technology to real world data science problems and gain an in depth understanding of emerging technologies, statistical analysis and computational techniques.

Thumbnail
Study based on your interests: specialise in AI or Fin Tech and acquire transferable skills to advance your career aspirations.

By studying this degree you will:

  • have the option to study one of the specialist pathways in Artificial Intelligence or Financial Technology
  • address skills required by data scientists to drive improvements in organisational performance
  • have the opportunity to create your own data analysis projects
  • earn a prestigious qualification that is valued across the globe.

Course details

MSc: Four core modules, two compulsory modules, four optional modules, plus a final project. (180 credits)
Postgraduate Diploma: Four core modules, two compulsory modules and two optional modules. (120 credits)
Post Graduate Certificate: Two core modules and two optional modules. (60 credits)

View the modules for MSc Data Science

You can also choose from one of two specialist pathways in:

  • Artificial Intelligence

MSc Artificial Intelligence - modules
PGDip Artificial Intelligence - modules

  • Financial Technology

MSc Financial Technology - modules
PGDip Financial Technology - modules

October 2019 intake

Applications open24 June 2019
Application deadline2 September 2019
Registration deadline23 September 2019

April 2020 intake

Applications open16 December 2019
Application deadline09 March 2020
Registration deadline16 March 2020

The MSc Data Science degree can be completed in one year or up to five years, depending on module availability. Each module is studied over 22 weeks and requires an average of five to seven study hours per week.

You can choose whether you want to enrol:

  • as a web supported learner: this means you’ll join an online group, where your tutor will provide support via discussion groups.
    or
  • with a Recognised Teaching Centre (where available). You’ll be able to attend face-to-face classes and meet up with other students on your course.

Study materials

Once you register, you will be able to access a range of resources and study materials on computers, tablets and other mobile devices through a Virtual Learning Environment (VLE).

Online support

When you register, we will give you access to your Student Portal. You can then access your University of London email account and two key resources:

  • On the VLE you can access electronic copies of all printed study materials, resources including audio-visual, and forums to discuss course material and work collaboratively with others.
  • Access to academic support and feedback from London-based support teams. Tutors introduce the modules, respond to queries, monitor discussions and provide guidance on assessments.

If you register for support at one of our recognised teaching centres you can attend lectures and benefit from, and receive tutor support.

Assessment

For all programmes, each core, compulsory and optional module (apart from the Final Project) is summatively assessed by a coursework element (30%) and a written examination element (70%).

The Final Project is summatively assessed by a series of coursework submissions and an unseen, final exam. (Coursework 70% and examination 30% of the final mark).

All coursework and projects are submitted through the VLE. You can sit exams at any of our exam centres worldwide.

More about exams

What qualifications do you need?

Entry routes

We offer two entry routes into the programmes, so if you do not meet the academic requirements you may still be eligible to apply through an alternative route.

Entry Route 1

To be eligible to register for any of the Data Science programmes, you must have the following:

  • A bachelor’s degree (or an acceptable equivalent) in a relevant subject which is considered at least comparable to a UK second class honours degree, from an institution acceptable to the University.

Relevant subjects include but are not limited to the following:

  • Biomedical Statistics
  • Business Computing
  • Computer Science
  • Creative Computing
  • Data Science
  • Economics
  • Engineering
  • Finance
  • Games Programming
  • Machine Learning and Artificial Intelligence
  • Marketing and Finance
  • Mathematics and statistics
  • Physics.

Entry Route 2

  • A bachelor’s degree (or an acceptable equivalent) in any subject which is considered at least comparable to a UK second class honours degree, from an institution acceptable to the University.

In addition to the above, you will be required to complete an online preparatory course prior to registration. The online preparatory course, Foundations of Data Science, requires approximately 30 hours of study.

Can I transfer credits from other awards?

  • If you have studied material as part of a previous qualification that is comparable in content and standard, you might be exempted from the equivalent course of our degree. This is known as Recognition of Prior Learning (RPL) or Credit Transfer. We recognise qualifications automatically if we have already confirmed that they meet the learning outcomes of a particular module or set of modules.

For qualifications we have not reviewed before, any recognition is classed as discretionary. If you believe a qualification you hold reflects similar learning outcomes to certain MSc modules, you can apply for this to be recognised.

If your prior learning is recognised, you could complete the MSc more quickly by studying fewer modules. For this programme the University of London may recognise your prior learning and award you credit towards the qualification up to the value of 120 UK credits.

More about Recognition of Prior Learning

English Language requirements

You need a high standard of English to study this programme. You will meet our language requirements if you have achieved one of the following within the past three years:

  • IELTS: at least 6.5 overall, with 6.0 in the written test.
  • TOEFL iBT: at least 92 overall, with 22+ in reading and writing and 20+ in speaking and listening.

Alternatively, you may satisfy the language requirements if you have at least 18 months of education or work experience conducted in English.

Computer requirements

As this is a technical degree, you will need regular access to a computer with an internet connection and a minimum screen resolution of 1024x768. You will also need Adobe Flash Player to view video material and a media player (such as VLC) to play video files.

More about computer requirements

Academic year2019-2020
Independant web-supported learners:
Band A countries - MSc total£8000
Band B countries - MSc total£12000
15 credit module fee band A£670
15 credit module fee band B£1000
30 credit module fee band A£1300
30 credit module fee band B£2000
Teaching Centre supported learners:
Band A countries - MSc total£4080
Band B countries - MSc total£6800
15 credit module fee band A£340
15 credit module fee band B£567
30 credit module fee band A£680
30 credit module fee band B£1130
Module continuation fee (per module) bands A and B£375
Other fees 
Application fee for Recognition of Prior Learning [15 credit module]£49
Full MSc programme: 
10 x 15 credit modules, and 1 x 30 credit core module

*The indicative totals given represent the amount you would expect to pay if you were to complete the MSc degree / PGDip / PGCert in the minimum period of the time (three years BSc / one year CertHE), without resits, and with a year-on-year increase of 5%. These totals do not reflect the cost of any additional tuition support you may choose to take or the fee levied by your local examination centre.

Please note: All student fees are net of any local VAT, Goods and Services Tax (GST) or any other sales tax payable by the student in their country of residence. Where the University is required to add VAT, GST or any other sales tax at the local statutory rate, this will be added to the fees shown during the payment process. For students resident in the UK, our fees are exempt from VAT.

Managing and analysing big data has become an essential part of modern finance, retail, marketing, social science, development and research, medicine and government.

The benefits of our programme is flexible to address the skills shortage of data scientists who can use data to drive improvements to organisational performance. You will have the opportunity to gain highly-valued skills through the specialist pathways:

MSc Data Science
These skills will lead to a variety of careers with employers from technology firms, the biomedical research sector, the charitable and voluntary sector, and public research sector.

MSc Data Science and Artificial Intelligence
Embark on a variety of careers with employers from leading technology firms, robotics, military, academia, and public research sector.

MSc Data Science and Financial Technology
For a variety of careers with employers from the financial sector, including financial planning, insurance, marketing, and investment banking.

Certification

The Microsoft Professional Program (MPP) is incorporated into this programme. It is designed to help students gain technical expertise and professional experience.

The inclusion of MPP learning content into the University’s Data Science degree presents a unique opportunity to receive two globally recognised credentials when you complete the programme: a Master’s degree in Data Science from the University of London and an MPP certificate in Data Science from Microsoft.

'The skills needed to become a data scientist will become common across industries and an understanding of data science will become a required skill for many jobs. This MSc Data Science degree provides a solid foundation for professional growth and will help students build a foundation for lifelong learning that’s necessary to compete in this 21st century economy.'

Karen Kocher
General Manager, 21st Century Jobs, Skills & Employability, Microsoft Corporation.

The academic content for the postgraduate Data Science programmes has been developed by the University of London with academic direction by the Department of Computing at Goldsmiths, University of London, one of the UK’s top creative universities.

Goldsmiths' unique hands-on project-based style works for a diverse range of interests - from computer and data science to art and music to social science and journalism.

Programme Director

Dr Larisa Soldatova is an academic in the Department of Computing at Goldsmiths and an internationally recognised expert in AI.

Larisa leads in Goldsmiths the UK project ACTION on cancer (2018-2022) that aims to develop an AI system supporting personalised cancer treatments. She was a Coordinator of the European project AdaLab (2014-2018), and was a principle investigator of several international research projects on the applications of AI to biomedicine. The results of her work are published in high impact journals such as Science, Nature Biotechnology, Journal of the Royal Society Interface.

Studying for your University of London degree from anywhere in the world without the costs of relocating represents excellent value for money. However, there may be additional sources of support depending on where you live and how you choose to study.

More on funding your study

Can I get sponsored?

If you’re working and apply to do this degree, your employer may be willing to help with the cost. Our online programmes are ideal for employers, because they keep you as an employee, while benefiting from the additional skills you bring to the workplace.

More on employer sponsorship

We have a template available to help you present a case to your employer.

Microsoft collaboration logo

Gain a Microsoft Professional Programme Certificate (MPP)

‘This MSc degree provides a solid foundation for professional growth helping students to compete in this 21st century economy.’ Karen Kocher: General Manager, 21st Century Jobs, Skills & Employability Microsoft Corporation.