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Data Science (with Advanced Practice) MSc

Different course options

Study mode

Full time

Duration

2 years

Start date

SEP-23

Key information
DATA SOURCE : IDP Connect

Qualification type

MSc - Master of Science

Subject areas

Data Science

Course type

Taught

Course Summary

Course overview:

Data scientists use a range of computational and statistical techniques to unlock insight from data and solve complex problems. This emerging profession sits at the cutting-edge of computer science and graduates are increasingly in demand from industry. This innovative data science course equips you with the specialist skills and knowledge to make an immediate and meaningful contribution to a range of industry environments.

You are taught by expert staff from our machine intelligence research group, ensuring that you have access to the very latest thinking from the field of data science. You have the opportunity to contribute to live research and to progress from postgraduate study to postdoctorate research.

The School has a proven record of successful research, consultancy and enterprise projects with industry in the field of data science, which means that staff have relevant real-world case studies to draw upon for teaching materials.

There are three routes you can choose from to gain an MSc Data Science:

  • full-time - 2 years with advanced practice (September and January start)
  • full-time - 1 year (September start) or 16 months (January start)
  • part-time - 2 years.

How you learn

You learn about concepts and methods primarily through keynote lectures and tutorials using case studies and examples. Lectures include presentations from guest speakers from industry. Critical reflection is key to successful problem solving and essential to the creative process. You develop your own reflective practice at an advanced level, then test and assess your solutions against criteria that you develop in the light of your research.

How you are assessed

The programme assessment strategy has been designed to assess your subject specific knowledge, cognitive and intellectual skills and transferable skills applicable to the workplace. The strategy ensures that you are provided with formative assessment opportunities throughout the programme which support your summative assessments. The assessments will include assignments, tests, case studies, presentations, research proposal and literature review, and the production of a dissertation. The assessments may include individual or group essays or reports. The assessment criteria, where appropriate, will include assessment of presentation skills and report writing.

Career opportunities

We prepare you for a career in industry. In addition to your taught classes, we create opportunities for you to meet and network with our industry partners through events such as our ExpoSeries, which showcases student work to industry. ExpoTees is the pinnacle of the ExpoSeries with over 100 businesses from across the UK coming to the campus to meet our exceptional students, with a view to recruitment.

Graduates can expect to find employment in one of the increasing number of sectors needing data science specialists, such as the defence industry, financial industry, telecommunications, and health sector.

Modules

The field of information visualisation has expanded rapidly with many designers generating new forms of charts through which to view quantitative data. This module explores the range of charts available from the traditional such as bar charts and pie charts, to the more novel such as stream graphs, tree maps, sunbursts, and force diagrams, and examines their mathematical properties. By accurately representing quantitative data using appropriate charts, the intended audience can make their own interpretations of the data and identify emerging patterns and themes that are more readily recognisable in chart form than in the form of raw data.

Tuition fees

UK fees
Course fees for UK students

For this course (per year)

£4,770

International fees
Course fees for EU and international students

For this course (per year)

£9,000

Entry requirements

You will normally have a first degree in related discipline (2.2 minimum) or relevant experience or equivalent qualifications. Acceptable subjects include artificial intelligence, computer forensics, computer science, computing, information technology, artificial intelligence, data science, computer forensics and digital forensics.

Department profile

Our School of Computing, Engineering & Digital Technologies is home to a diverse group of courses in the fields of animation, computer games, computer science, concept art, cyber security, engineering and visual effects. Through education enriched by research, innovation, and engagement with business and the professions, we develop the next generation of problem solvers, innovators and leaders that employers and society need....more

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