MSc Knowledge Discovery and Datamining

Why take this course?

• This course offers an excellent platform to a career in data analysis and is taught by one of the leading groups in Data Mining research in the UK.
• The course has both theoretical and practical elements and students will get hands on experience on commercial data mining and statistical software.
• Students will have the opportunity to participate on commercial data mining projects as part of their assessment, gaining experience on all the stages of the KDD process.
• This programme has full Chartered IT Professional (CITP) accreditation (Further Learning Element) as well as leading to Chartered Engineer (CEng) status from the (BCS - The Chartered Institute for IT)

Career opportunities

As a graduate from this course, you will be prepared for a career in data analysis. Job postings for data analysts, also called data scientists, are increasing rapidly (see graph taken from the LinkedIn Corp).

The average salaries associated with jobs in Data Mining for the UK, during the 2010-2012 are between £44,000 and £52,000 (Source: http://www.itjobwatch.co.uk/)

The degree can also act as a very good platform for a research degree in KDD.

What is KDD?

All organisations depend on high quality information for making strategic decisions. The information is often derived from the rapidly growing mountains of raw data generated from the organisations’ computerised operational systems. This task requires a new generation of analysts with knowledge of effective and efficient data analysis methods and understanding of the process known as Knowledge Discovery and Data Mining (KDD).

The popularity of this area is driven by its tremendous application potential in areas as diverse as finance, medicine, biology and the environment.

The course is a full-time, one-year taught programme, designed for advanced students and practitioners; it can also be taken part-time over two years.

Why study this subject at UEA?

The Data Mining, Machine Learning and Statistics group at UEA comprises eight faculty members, eight research assistants and between 10 and 20 PhD students. As such, it is one of the largest such groups in the UK.

Members of the group have made significant contributions in techniques for data mining and KDD in the last 10 years, in particular: KDD Methodologies; use of metaheuristics for rule and tree induction; all-rule induction; clustering techniques; feature subset selection; feature construction, as well as many applications in the financial services industry, medicine and telecommunications.

Support for this research has been received from BBSRC, EPSRC and The Royal Society as well as numerous companies (including Alston Transport, Derbyshire Police, Lanner Group, Master Foods, MET Office, National Air Traffic Services, Aviva, Process Evolution Ltd., Simultec AG Zurich and Virgin Money).

Master students will be part of our vibrant research community and will have very good opportunities for progression to PhD.

Contact time

Students have on average 15 hours of contact time per week with teaching staff through lectures, laboratory sessions and seminars, though this may vary depending on module choices. Additionally, students should allocate at least 25 hours per week for study, coursework assignments and projects.

Teaching and Assessment

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

Some project work may be done with companies and could involve paid placement at a company. You can either choose from a number of related dissertation topics proposed by faculty or formulate your own project proposal. These projects often address real-world problems.

Recent dissertation titles:

• Classification rule induction for atmospheric circulation patterns
• Keyword-based e-mail classification
• Data analysis of orthopaedic operations

Course Organiser:Dr. Beatriz De La Iglesia

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Entry Requirements Degree Subject: Computing, Mathematics or a related subject. Degree Classification: Good first degree (minimum 2.1 or equivalent). Students for whom English is a 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:

IELTS: 6.5 (minimum 6.0 in all components)
TOEFL: Internet-based score of 88 (minimum 18 in listening, 21 speaking, 19 writing and 20 reading)
PTE (Pearson): 62 (minimum 55 in all components)
Test dates should be within two years of the course start date.

Other tests such as TOEIC and the Cambridge Certificate of Advanced English are also accepted by the university. Please check with the Admissions Office for further details including the scores or grades required.

INTO UEA and INTO UEA London 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 (INTO UEA Norwich) or pseuealondon@into.uk.com (INTO UEA London).

• 95% of research activity is classified as internationally leading, excellent or recognised in the 2008 Research Assessment Exercise.
• Teaching of the highest quality; rated “Commendable” in the most recent Teaching Quality Assessment.
• Our Masters programmes are accredited by the BCS - The Chartered Institute for IT to full Chartered IT Professional (CITP Further Learning Element) as well as leading to Chartered Engineer (CEng) status.
• The School maintains close links with industry and many of our student assignments relate to real world problems.
• The School of Computing Sciences leads the university in utilizing its internationally recognized research commercially, through SYS Consulting, its Consulting company and through Knowledge Transfer Partnerships.
• Our students also use their technical and entrepreneurial skills to play influential roles in the creation of companies such as Travel Republic, Evoke systems, Fyfo and Shoretech systems.

Come and Visit Us

Our Open Days will give you the opportunity to experience the University of East Anglia's unique campus atmosphere.

Fees and Funding Tuition Fees 2013/14

• UK/EU £5,000
• International £12,500

Funding

• International applicants applying to this course can be considered for one Faculty of Science half fees scholarship or one £2000 scholarship. The deadline is 1st April 2013.

Faculty of Science Scholarships
Students wishing to apply should submit an essay answering the following question in 1000 words: 'Is it OK to let the data speak for itself'? Essays should be emailed to the Admissions Office. Please ensure you include your full name, the course you have applied to, and your applicant number in your email.

For more information please contact the Computing Sciences Postgraduate Admissions Office (cmp.pgt.admiss@uea.ac.uk).