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Course summary

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. About This Course 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. Disclaimer Course details are subject to change. You should always confirm the details on the provider's website: www.uea.ac.uk

Modules

On this course you will take compulsory modules in research techniques, data mining, statistics and artificial intelligence as well as two optional modules from a range, which may include applications programming, database manipulation, information retrieval and NLP, or a research topic.

Assessment method

Assessment will be conducted using a variety of formats including a dissertation, essays, project reports, presentations, and examinations.

Professional bodies

Professionally accredited courses provide industry-wide recognition of the quality of your qualification.

  • BCS - The Chartered Institute for IT

Entry requirements

Applicants should have a 2.1 Honours degree in computer science or a cognate subject, or equivalent qualifications and experience. All applicants who are not a British national and/or whose 1st language is not English will need to demonstrate a suitable level of English language proficiency. This is equivalent to an IELTS 6.5 overall, with a minimum of 5.5 in all 4 components.


Fees and funding

Tuition fees

England £10500 Whole course
Northern Ireland £10500 Whole course
Scotland £10500 Whole course
Wales £10500 Whole course
International £22100 Whole course

Additional fee information

If you are a postgraduate student on a part-time course please assume a 50% fee of the equivalent full-time course per year, or a pro-rata fee for the module credit you are taking. Module fees are subject to incremental increases for any subsequent years of study. Please enquire within the faculty admissions office to find out whether a part-time option is available for your course.

Sponsorship information

UEA offers a limited number of scholarships for International students of up to 50 per cent of the value of tuition fees; these awards are based on academic merit.

Data Science at University of East Anglia UEA - UCAS