MSc Data Science (with Advanced Practice)

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 post doctorate e 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.

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.

The one-year programme is a great option if you want to gain a traditional MSc qualification. The two-year master’s degree with advanced practice enhances your qualification by adding a vocational or research based internship to the one-year master’s programme. A vocational internship is a great way to gain work experience and give your CV a competitive edge. A research internship provides you with the opportunity to develop your analytical, team-working, research and academic skills by working alongside a research team in an academic setting. We guarantee a research internship, but cannot guarantee a vocational internship. We will, however, provide you with practical support and advice on how to find and secure your own vocational internship position should you prefer this type of internship.

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Modules

  • Compulsory modules
  • Big Data and Business Intelligence
  • Computing Masters Project
  • Data Visualisation
  • Interactive Visualisation
  • Machine Learning
  • Research Methods
  • Statistical Methods for Data Analytics
  • Internship
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    £17,000 Per Year

    International student tuition fee

    2 Years

    Duration

    Nov 2024

    Start Month

    Oct 2024

    Application Deadline

    Upcoming Intakes

    • November 2024
    • January 2025
    • September 2025
    • September 2026

    Mode of Study

    • Full Time