MSc Data Science
Course options
Key Details
- Attendance
- Full Time
- Award
- Degree of Master of Science
- Course Length
- 1 years
- Course Start Date
- September 2023
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Course Overview
This course is designed to train highly qualified data analysts – or data scientists – to embark on careers in a wide range of industries. You’ll be given an excellent practical and theoretical grounding in data mining and statistics with the chance to customise your degree through modules in artificial intelligence, visualisation, programming and database manipulation.
Data Scientists are highly prized for their advanced, practical skill set and their increasing importance to the success of a modern business. Organisations in almost any industry need to source, analyse and utilise vast amounts of data to aid strategic decision-making, so you’ll have great graduate career prospects as well as a wide range of transferrable skills.
We have a large Data Mining, Machine Learning and Statistics research group, which has made significant contributions to the field in the last 10 years, so you’ll be working directly with pioneering experts.
Organisations today have a vast amount of raw data generated from their computerised operational systems. So how will they turn this into high quality information for strategic decision-making? They need a new generation of data analysts who understand effective and efficient data analysis methods and the Knowledge Discovery and Data Mining (KDD) process.
This course – one of the most established in this area with over 15 years of history – offers an excellent platform to help you forge a successful career in data analysis.
As a student, you’ll be part of our vibrant research community and will have very good opportunities to progress to a PhD. You will be part of a research group that has made significant contributions in techniques for data mining and KDD – including KDD Methodologies; use of metaheuristics for rule and tree induction; all-rule induction; clustering techniques; feature subset selection; feature construction; time series classification as well as many applications in the financial services industry, medicine and telecommunications.
The research group has collaborated in research or consultancy projects with a wide range of organisations, including: the Biotechnology and Biological Sciences Research Council (BBSRC), the Engineering and Physical Sciences Research Council (EPSRC), the Institute and Faculty of Actuaries and The Royal Society, Alston Transport, Derbyshire Police, Lanner Group, Master Foods, MET Office, National Air Traffic Services, Aviva, Process Evolution Ltd, Simultec AG Zurich, Virgin Money and the Norwich Football Club.
What’s more, this degree has full Chartered IT Professional (CITP) accreditation (Further Learning Element) as well as partial fulfilment of Chartered Engineer (CEng) status from The Chartered Institute for IT (BCS).
You will graduate with a wealth of knowledge, prestigious connections and research experience – putting you one step ahead of other graduates in your career or further studies.
Study and Modules
Structure
The MSc Data Science course is a full-time, one-year taught programme, designed for advanced students and practitioners. You can also take it part-time over two or three years.
On this course, you’ll take compulsory modules in research techniques, data mining, statistics and artificial intelligence or visualisation.
Alongside this, you’ll take two optional modules from a range – which may include applications programming, database manipulation, human computer interaction, computer vision or a research topic.
A key element of the course is your dissertation, which will give you the chance to explore a topic or work on a problem (which may be with an industry partner) in depth, under the supervision of a member of faculty.
Recent dissertation titles include:
- Classification rule induction for atmospheric circulation patterns
- Keyword-based email classification
- Data analysis of orthopaedic operations
Compulsory Modules
Optional A Modules
(Credits: 20)Optional B Modules
(Credits: 40)Whilst the University will make every effort to offer the modules listed, changes may sometimes be made arising from the annual monitoring, review and update of modules. Where this activity leads to significant (but not minor) changes to programmes and their constituent modules, the University will endeavour to consult with students and others. It is also possible that the University may not be able to offer a module for reasons outside of its control, such as the illness of a member of staff. In some cases optional modules can have limited places available and so you may be asked to make additional module choices in the event you do not gain a place on your first choice. Where this is the case, the University will inform students.
Teaching and Learning
Teaching
You will have an average of 15 hours of contact time per week with teaching staff, depending on your module choices. This will be made up of a mixture of lectures, seminars and lab classes – where the lab and seminar classes reinforce and expand on the lecture material.
The course has both theoretical and practical elements, so you’ll get hands on experience in commercial data mining and statistical software. You’ll even have the opportunity to participate in commercial data mining projects as part of your assessment, gaining experience on all the stages of the KDD process.
Independent study
Your individual study (around 25 hours per week) will complement the formal teaching and will evolve along with your skills and expertise in data analysis. Beginning with an initial focus on the basics of programming and data manipulation, you’ll move on to much deeper study and appreciation of specialist topics such as data mining and statistics.
Your dissertation will also form a key part of your course, which will involve extensive independent study supported by your supervisor.
Assessment
We have a mixture of individual and group assessments. These include written work, presentations or demonstrations, and exams (closed and/or time-limited assessment). They combine theoretical understanding with practical application and are designed to test the range of skills and competencies required for the learning outcomes of each module. The balance of assessment types varies according to the options chosen. Additionally, there is an individual project which is assessed through a combination of written work and demonstration or presentation.
Entry Requirements
- Degree Classification
- Bachelors degree 2.1 or equivalent
- Degree Subject
- Computing, Mathematics or a related subject. Your application should also demonstrate some programming experience either in other qualifications or work experience.
- English Foreign Language
We welcome applications from students whose first language is not English. To ensure such students benefit from postgraduate study, we require evidence of proficiency in English. Our usual entry requirements are as follows:
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IELTS: 6.0 (minimum 5.5 in two components only, with 6.0 in the other two)
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PTE (Pearson): 64 (minimum 59 in two components only with 64 in the other two)
Test dates should be within two years of the course start date.
Other tests, including Cambridge English exams and the Trinity Integrated Skills in English are also accepted by the university. The full list of accepted tests can be found here: Accepted English Language Tests
INTO UEA also run pre-sessional courses which can be taken prior to the start of your course. For further information and to see if you qualify please contact intopre-sessional@uea.ac.uk.
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- Intakes
This course is open to UK, EU and International applicants. The annual intake for this course is in September each year.
Fees and Funding
Tuition fees for the Academic Year 2023/24 are:
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UK Students: £10,500 (full time)
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International Students: £22,100 (full time)
If you choose to study part-time, the fee per annum will be half the annual fee for that year, or a pro-rata fee for the module credit you are taking (only available for Home students).
We estimate living expenses at £1,023 per month.
Further Information on tuition fees can be found here.
Scholarships and Bursaries
The University of East Anglia offers a range of Scholarships; please click the link for eligibility, details of how to apply and closing dates.
Course Related Costs
Please see Additional Course Fees for details of course-related costs.
How to Apply
Applications for Postgraduate Taught programmes at the University of East Anglia should be made directly to the University.
To apply please use our online application form.
The closing date for submission of complete applications from International students is Friday 19 May 2023.
Please note we cannot consider international applications after this date.
FURTHER INFORMATION
If you would like to discuss your individual circumstances prior to applying please do contact us:
Postgraduate Admissions Office
Tel: +44 (0)1603 591515
Email: admissions@uea.ac.uk
International candidates are also encouraged to access the International Students section of our website.
Tel: +44 (0)1603 591515
Email: admissions@uea.ac.uk
International candidates are also encouraged to access the International Students section of our website.
Employability
After the Course
You’ll graduate ready for a career in data analysis or data science – an area of rapid growth at the moment.
You can expect to earn a high salary – the median annual wage for data science in the UK was 60,000 (source http://www.itjobwatch.co.uk/).
Careers
A degree at UEA will prepare you for a wide variety of careers. We've been ranked 1st for Job Prospects by StudentCrowd in 2022.
Examples of careers that you could enter include:
- Data scientist
- Data analyst
- Data miner
- Business intelligence analyst