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

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Data Science

MSc, PGDip and PGCert Data Science

Available to study anywhere in the world

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.

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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.

Study this course at a teaching institution near you

You can receive local support from a local teaching centre, use the dropdown to find your nearest centre.

Programme 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

April 2020 intake
Applications open04 November 2019
Application deadline02 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 other 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.
  • The Online Library provides access to over 100 million academic electronic items comprising E-books, E-journals, conference proceedings, etc. In addition, students can request items which are not held in the library via the library's Inter-Library loans service with the British Library.
  • Senate House Library provides free reference access for all registered distance and flexible learning students.
  • 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 (MSc/PGDip/PGCert)

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

In this exciting yet challenging programme, you will learn how to solve real world data science problems. The programme is mainly based on Python. If you do not have previous experience of programming in Python, we advise you to take our MOOC, Foundations of Data Science: K-means Clustering in Python, before you start the programme.

Entry Route 2 (MSc/PGDip/PGCert)

  • 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: K-Means Clustering in Python, 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

The fee depends on two factors:

MSc programme fee (indicative totals*)2019-20
10 x 15 credit modules, and 1 x 30 credit core module
Band A countries:
Independent web-supported student£8000
Recognised Teaching Centre supported student£4080 + teaching centre fee
Band B countries:
Independent web-supported student£12000
Recognised Teaching Centre supported student£6800 + teaching centre fee

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Pay per module2019-20
Independent web-supported learners:
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
Recognised Teaching Centre supported learners:
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
See details below for costs you may incur with parties which are external to the University of London, for example, examination centre charges and locally imposed taxes. You should budget for these accordingly.

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*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 time (one year, subject to module availability), 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.

How fees work

Your fees include study materials and entry into assessments.

The indicative programme fee includes all module and continuation fees for the duration of your study, as well as online tutor support.

With pay per module, you pay for each module as you register for it. The 'web-supported learning' fee includes support from a University of London online tutor. Alternatively, if you prefer face-to-face tuition, you can pay a smaller fee to us and a separate fee to a teaching centre which supports the programme.

The module continuation fee is the cost per module if you defer an examination or need to retake assessments. It includes all study materials, entry into assessments, and online tutor support.

Additional costs

You will also need to budget for:

  • Exams: our approved examination centres around the world charge a fee when you sit an exam. Contact your chosen examination centre for details about costs.
  • Tuition: as described, teaching centres charge face-to-face tuition if you choose to take modules with institution-supported learning.
  • Recognition of prior learning applications: these are not included with the course fees.

How to pay your fees.

Some fees are non-refundable. Please see the?refund and compensation?policy?for?further details.

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.

In some countries, qualifications earned by distance and flexible learning may not be recognised by certain authorities or regulators for the purposes of public sector employment or further study. We advise you to explore the local recognition status before you register, even if you plan to receive support from a local teaching centre.

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.

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