Taught course

Internet of Things (Data)

Queen Mary, University of London · Computer Science

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Entry requirements

A 2:1 or above at undergraduate level in Computer Science, Electronic Engineering, Mathematics or a related discipline.

Good knowledge of computer programming is highly recommended.

Months of entry


Course content

We live in an ever-more connected world. The range of ‘things’ (sensors, tags, cards, phones, actuator, wearables) we interact with expands daily. This innovative Internet of Things (IoT) MSc programme will help you adapt to become a highly skilled and in-demand engineer who can exploit the potential that these technologies offer.

The course will enable you to:

  • Learn to engineer new interactive products, acquire and process the data they collect
  • Interact with and interconnect things as part of larger, more diverse, systems
  • Work with the most up-to-date technologies - each topic is backed up by our world-leading research centres and groups
  • Fulfil the educational requirements for registration as a Chartered Engineer, accredited by The Institution of Engineering and Technology (IET)

You will gain a strong foundational understanding of the internet of things, as well as enabling communication technologies. You will learn skills in statistics, data mining and analytics, mobile services, and security and authentication.

You will gain from interaction with our research centres, specifically Networks, Cognitive Science and Antennas, as well as interdisciplinary centres such as the Centre for Intelligent Sensing (CIS) and the Centre for Digital Music (C4DM).

We also have connections with a variety of organisations, including Vodafone, Google, IBM, BT, NASA, BBC and Microsoft.

Qualification, course duration and attendance options

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

Course contact details

School of Electronic Engineering and Computer Science
+44 (0)20 7882 7333