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MSc by Research Data Science MSc by Research Data Science Middlesex University

Middlesex University

Masters Degree , Data Management

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Course Description

Data science is positioned to be the major new arena of scientific discovery in the 21st century. As Eric Schimdt, CEO of Google, has pointed out, we now generate as much information every two days as we did from the dawn of human civilisation up until the year 2003.

To cope with this vast amount of data, there is an urgent requirement to derive meaningful insights from very large and diverse data sources: the so-called 'big data challenge'. Secure identification of individuals, accurate financial prediction and reliable cancer diagnosis are all examples of area in which the technologies underpinning data science are marketing revolutionary contributions, enriching our lives, and making our future healthier, more efficient and more secure.

Why study MSc Data Science by Research at Middlesex University?

The MSc by Research (Data Science) provides an opportunity for students who wish undertake an individual real-world big-data research project; you can choose a project area from a wide variety of interdisciplinary domains, including business information systems, e-health, social media, cloud computing, smart homes, intelligent vehicles and ambient assisted living.

We currently have supervisors available in:

  • Machine learning
  • Visual analytics
  • Mathematics and statistics
  • Smart sensors (for ambient assisted living and smart homes)
  • Numerical algorithms (especially computational geometry)
  • Artificial intelligence
  • Ethics of technology
  • Psychology
  • Business information systems and business informatics
  • Robust software/system development
  • Networking
  • Ethics
  • Marketing
  • Operations management
  • Enterprise and economic development
  • Education
  • Design

Course Content

The MSc by Research (Data Science) aims to bring together, in an interdisciplinary fashion, data science-related activities from across the University, centring on the core activities of machine-learning, visual analytics and data storage. These will work together to support applications-driven data scenarios.

To support the interdisciplinary nature of this programme, you will have a core activity supervisor (machine learning, visual analytics), as well as a supervisor specialising in your chosen application area.

This degree is an entirely research-based master's programme. The majority of your time will be spent working on your research project in the library, laboratories or elsewhere, under the direction of your supervisors.

Alongside your independent study, you will also have tutorial lectures in the key areas of machine learning and visual analytics. You will have regular meetings with your supervisor to review progress and plan future activities. You may also spend brief periods at partner sites, for example where your project involves collaboration with industry.

Full-time students are expected to attend for an average of 35 hours per week and part-time students for an average of 12 hours per week.

 

Entry Requirements

Qualifications

  • We normally require a second class honours degree 2:2 or above in a science-based discipline
  • Entry is subject to the proposed project being acceptable
  • Each application will be considered on its individual merits

Eligibility

UK/EU and international students are eligible to apply for this course.

Academic credit for previous study or experience

If you have relevant qualifications or work experience, academic credit may be awarded towards your Middlesex University programme of study. For further information please visit our Accreditation of Prior Learning page.

Interviews, entrance tests, portfolios and auditions

Each application will be considered on its individual merits and suitably qualified candidates will be invited for interview. Successful applicants may enrol to begin their studies at the start of any of the three terms during the academic year.

Assessment Methods

Assessment will be based on a final dissertation of approximately 30,000 words. Two independent examiners will be appointed who will read and evaluate the dissertation, following which you will be invited to make an oral defence of your work.

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Similar Subjects

Bioinformatics Data Management Databases Health Informatics Information Modelling Information Systems Intelligent Systems Knowledge and Information Systems

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