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Data Science (International) MSc

This is a joint degree between UCL and UniSA and students that successfully complete the Programme will be issued a single certificate containing the names of both institutions. The Programme is built around a combination of Data Science programmes offered separately by both UCL and UniSA. Modules delivered by UCL for the Programme focus on theory, whilst the UniSA modules are comparatively more practical.

Covid-19 programme updates

Due to COVID-19, there may have been updates to this programme for the 2020 academic year. Where there has been an update, these are indicated with a red alert and a link which will provide further information.

Key information

Programme starts

September 2020

Modes and duration

Full time: 2 years

This programme commences in London. Students will complete their studies in Adelaide.

Application dates

All applicants
Open: 1 November 2019
Close: 11 August 2020
Notification
Due to the large number of applications received, this programme is no longer accepting applications for 2020/21 entry. We apologise for any inconvenience caused. Applications for 2021/22 entry will open later in the year.

Tuition fees (2020/21)

UK/EU:
See Fees Note (FT)
Overseas:
See Fees Note (FT)


Note on fees: The tuition fees shown are for the year indicated above. Fees for subsequent years may increase or otherwise vary. Further information on fee status, fee increases and the fee schedule can be viewed on the UCL Students website. The fees for this programme are set in AUD and payable to UniSA.

Location: London, Bloomsbury and Adelaide, Mawson Lakes

Entry requirements

A minimum of an upper second-class Bachelor's degree in a quantitative discipline from a recognised UK university or a non-UK qualification of an equivalent standard in a relevant discipline typically in the fields of mathematics or computer science. Students should be comfotable with a high level of programming in a language such as Python.

English language requirements

If your education has not been conducted in the English language, you will be expected to demonstrate evidence of an adequate level of English proficiency.

The English language level for this programme is: Good

Pre-Master's and Pre-sessional English

Further information can be found on our English language requirements page.

International students

Country-specific information, including details of when UCL representatives are visiting your part of the world, can be obtained from the International Students website.

International applicants can find out the equivalent qualification for their country by selecting from the list below.

Select your country:

About this degree

The aim of this programme is to produce graduates with the analytic and technical skills to effectively use Python, Hadoop, R and SAS to analyse Big Data and extract useful information to support the management and operations of an organisation.

You will undertake modules across a broad range of data science topics, which will provide you with hands-on experience in data analytic techniques for real-world challenges.

Taught by leading researchers in data science, you will learn to analyse and visualise rich data sources, spot data trends and to generate data driven insights.

Students undertake modules to the value of 240 UCL Credits (72 UniSa Units).

First year (UCL)120 UCL credits/36 UniSA units, comprising 4 compulsory modules (60 credits), 4 optional modules (60 credits) (UCL system). Second year (UniSA) 120 UCL credits/36 UniSA units, comprising 4 compulsory modules (2 x 4.5 units, 2 x 9 units (thesis), 2 optional modules (2 x 4.5 units) (UniSA system).

Upon successful completion of 180 credits, you will be awarded a MSc in Data Science (International).

Please note that the list of modules given here is indicative. This information is published a long time in advance of enrolment and module content and availability is subject to change.

Compulsory modules

  • Introduction to Deep Learning (15 credits / 4.5 units) UCL
  • Introduction to Machine Learning (15 credits / 4.5 units) UCL
  • Applied Machine Learning (15 credits / 4.5 units) UCL
  • Data Analytics (15 credits / 4.5 units) UCL
  • Statistical Programming for Data Science (15 credits / 4.5 units) UniSA
  • Unsupervised Methods in Analytics (15 credits / 4.5 units) UniSA
  • ITMS Masters Minor Thesis 1 (30 credits / 9 units) UniSA
  • ITMS Masters Minor Thesis 2 (30 credits / 9 units) UniSA

Optional modules

  • Advanced Analytic Techniques 1 (15 credits / 4.5 units) UniSA
  • Advanced Analytic Techniques 2 (15 credits / 4.5 units) UniSA
  • Data Visualisation (15 credits / 4.5 units) UniSA
  • Graphical Models (15 credits / 4.5 units) UCL
  • Information Retrieval and Data Mining (15 credits / 4.5 units) UCL
  • Machine Vision (15 credits / 4.5 units) UCL
  • Reinforcement Learning (15 credits / 4.5 units) UCL
  • Research Methods (15 credits / 4.5 units) UniSA
  • Statistical Natural Language Processing (15 credits / 4.5 units) UCL
  • Web Economics (15 credits / 4.5 units) UniSA

Students who have not previously studied research methods should include the course Research Methods as one of their choices.

Subject to Programme Director approval, and the availability of an appropriate project and supervisor, students may elect to undertake their project over two semesters by enrolling in COMP 5005 in their first semester in Adelaide. In this case, they should also seek advice from the Programme Director on their choice of electives.

Covid-19 module updates
Due to COVID-19, there may be updates to the modules for your chosen programme of study this year. Some modules may not be available or may need to be moved to a later term or year of study. These updates are relevant for 2020-21 academic year only.  The full list of modules will be available in the module catalogue from late August.  From the first week of September, you will be invited to complete module selection from Portico, our student record system. There may need to be additional updates or changes to modules during the academic year to allow for new guidance from the UK Government and Public Health England. Your department shall keep you updated of these changes as they become available.

Dissertation/report

There will be two minor theses as part of this programme, each thesis comprising one 2 hour lecture and 13 weeks of directed study. Students are then expected to present a 20-minute research seminar and submit a research report as a minor thesis, of approximately 9000 words. The proportion of total assessment of these last two components is as follows: Seminar – 10%; Research report – 90%; the two courses are ITMS Masters Minor Thesis 1 and ITMS Masters Minor Thesis 2. 

Teaching and learning

Covid-19 contact hours on campus
In Term One, while campus will be open, all the learning activity for the core content of your modules will take place online – including lectures, tutorials, seminars and assessments. By “core content” we mean everything you need to learn to complete the module successfully. In addition to these online contact hours, we will be offering some face-to-face educational activities for students on campus, and we will provide alternative online activities for those students unable to join us on campus. These activities, which will include contact with academic staff, will be relevant to your programme of study may include seminars, academic and employability skills workshops, small-group or individual tutorials, lab and practice-based teaching. UK Government safety guidelines will limit the amount of ‘in person’ activity we can offer and while it will vary from programme to programme, is likely to be no more than 1-2 hours per week. This will vary across departments, particularly if your programme includes laboratory/practical/studio/workshop sessions. You will be updated with more specific details as they are available and your timetable will indicate which sessions will be on campus and which will be available online.
Covid-19 assessment updates
There may be changes to the format of assessments for modules in this programme due to COVID-19. These will be summarised for each module on the module catalogue from 17 August 2020.   If any changes to assessments need to be made during the academic year due to updates in government guidance, these will be communicated to you as soon as possible from your department.    
Communicating further Covid-19 mitigation plans
We are continuing to follow UK Government guidance, as well as the expertise of our researchers, including specialists in health, education, human behaviour and infection prevention, to make sure UCL is as safe as possible during the COVID-19 pandemic. If it becomes necessary to make further changes to your programme as a result of new guidance/regulations, UCL and your department will communicate these as soon as this becomes clear. We will keep you up-to-date with our plans throughout term one, so you have the information you need to be able to take decisions that are right for your circumstances. Please ensure that you keep in touch with your department by regularly checking your UCL emails, Moodle courses, the Coronavirus FAQs for Students page and any UCL online groups or social media you follow.

Additional costs

For more information on additional costs for prospective students please go to our estimated cost of essential expenditure at Accommodation and living costs.

Accessibility

Details of the accessibility of UCL buildings can be obtained from AccessAble. Further information can also be obtained from the UCL Student Support & Wellbeing team.

Funding

Every year, over 2,500 UniSA students are supported in their studies through scholarships and grants worth millions of dollars. Check out the scholarships below. One of them may be perfect for you. Visit their scholarship search page for more.

Scholarships relevant to this department are displayed below.

Brown Family Bursary

Note:
This scheme is now closed for 2020/21
Value:
£15,000 (1 year)
Eligibility:
UK
Criteria:
Based on both academic merit and financial need

For a comprehensive list of the funding opportunities available at UCL, including funding relevant to your nationality, please visit the Scholarships and Funding website.

Careers

Enter the revolutionary area of big data where there is an acute shortage of data scientists. A McKinsey Global Institute report forecasts a 50 per cent gap between projected demand and supply by 2018.

In the UK, the big data and artificial intelligence boom is expected to generate 56,000 data science positions from 2016-2020.

While the demand for analytic skills crosses multiple industries, fields such as marketing, health care, IT, government and finance are expected to experience a particularly strong need for analytics professionals.

Employability

The field of data science field is evolving at a rapid rate. It will continue to grow as savvy business leaders integrate analytics into every facet of their organisation.

The demand for analytic skills is supported by research from IBM in a recent report - 'The Quant Crunch: How the demand for data science skills is disrupting the job market', which predicts that by 2020, the number of jobs for all US data professionals will increase by 364,000 openings to 2,720,000.

Why study this degree at UCL?

Vast volumes of data are generated every day around the globe. The need to make sense of it has given rise to the concept of ‘Big Data’, and to a new career - ‘data scientist’.

Data science brings together the best of data management and analytic methods, and the presentation of results - all in a closed loop cycle for continuous learning and improvement within the organisation.

This rapidly expanding area has applications in search and information retrieval, e-commerce, finance, health, natural language modelling and artificial intelligence.

UniSA and UCL – under a new agreement – are working together to advance IT excellence globally through joint education to deliver innovative outcomes for industry and graduates.

The partnership brings UCL’s world-leading research to Australia and interconnects with UniSA’s interdisciplinary and real-world experience approach.

UCL is one of the world’s leading multidisciplinary universities. It operates in a global context and is committed to excellence, innovation and the promotion of global understanding in all its activities: research, teaching, learning, enterprise and community engagement.

UCL has been ranked as the number one UK university for research strength and is ranked 10th in the QS World University Rankings 2018.

Data science brings together computational and statistical skills for data-driven problem solving, which is in increasing demand in fields such as marketing, pharmaceutics, finance and management. Offered in a dual-hemisphere mode this unique programme gives you the opportunity to study in both the UK and in Australia whist providing different perspectives and expertise in data science.

Department: Computer Science

Application and next steps

Applications

Applications are processed by the University of South Australia (UniSA). Please note you are not required to submit an application to UCL for this programme. Citizens of countries other than Australia and New Zealand please apply via the blue Apply now button below.

Australian and New Zealand citizens please apply here.

Who can apply?

This programme is best suited to those with an interest in big data and artificial intelligence, and those employed in fields such as marketing, healthcare, IT, government and finance, with an ever-increasing need for analytics professionals.

Application deadlines

All applicants
11 August 2020

Admissions are handled by UniSA, not by UCL, so please contact UniSA in the first instance with any queries.  See also http://study.unisa.edu.au/degrees/master-of-science-in-data-science-international


For more information see our Applications page.

Apply now

What are we looking for?

When we assess your application we would like to learn:

  • why you want to study Data Science (International) at graduate level
  • why you want to study Data Science (International) at UCL
  • what particularly attracts you to this programme
  • how your academic, professional and personal background meets the demands of this programme
  • where you would like to go professionally with your degree.

Together with essential academic requirements, the personal statement is your opportunity to illustrate whether your reasons for applying to this programme match what the programme will deliver.

UCL is regulated by the Office for Students. UniSA is regulated by Tertiary Education Quality and Standards Agency .

Page last modified on 18 August 2020


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