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Entry requirements

Degree Subject - Computing, Mathematics or a related subject.

Degree Classification - Good first degree (minimum 2.1 or equivalent).

For more information please see our website

Months of entry

September

Course content

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 will 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

Information for international students

For more information for international students, please go to UEA’s website.

Fees and funding

Find out more about UEA’s fees and funding options.

Qualification, course duration and attendance options

  • MSc
    full time
    12 months
    • Campus-based learningis available for this qualification
    part time
    24 or 36 months
    • Campus-based learningis available for this qualification

Course contact details

Name
Postgraduate Admissions Office
Email
admissions@uea.ac.uk
Phone
+44 (0)1603 591515