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  • DeadlineStudy Details: 1 year - 5 years

Masters Degree Description

Advances in digital technology are transforming how we sense, visualise and understand our built and natural environments. This practical Master’s course explores Connected Environment technologies at the intersection of Internet of Things (IoT), Artificial Intelligence (AI), Augmented Reality (AR) and Data Science. You’ll gain hands-on experience in electronics, programming, and design - from idea generation to prototyping and deployment.

Entry Requirements

A minimum of an upper second-class Bachelor's degree in a relevant discipline from a UK university or an overseas qualification of an equivalent standard.

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Fees

For fees and funding options, please visit website to find out more

Programme Funding

UCL offers a range of financial awards aimed at assisting both prospective and current students with their studies.

Student Destinations

Equipped with a distinct skillset, our graduates are highly sought after across the digital built environment. Many become IoT managers at top-tier tech firms, while others drive future innovation through doctoral research at global universities (including staying at UCL CASA). A strong entrepreneurial spirit also sees alumni successfully establishing their own consultancies in the domain of Connected Environments. Our growing LinkedIn Alumni group further connects graduates to a global network of opportunities.

Module Details

Compulsory modules

  • Connected Environments
  • Making, Designing & Building Connected Sensor Systems
  • Web Architecture
  • Sensor Data Visualisation
  • Ethics, Sustainability and Business of the Internet of Things
  • Connected Environments Group Prototype and Pitch
  • Dissertation
  • Remotely Sensing Cities and Environments
  • Mobile Systems & Interactions
  • Urban Simulation
  • Designing Spatial Data Stories
  • Foundations of Spatial Data Science
  • Agent-based Modelling for Spatial Systems
  • Building Spatial Applications with Big Data
  • Smart Cities: Context, Policy and Government
  • Urban Data Visualisation
  • Data Science for Spatial Systems
  • Deep Learning for Sensor Networks

Optional modules

  • Remotely Sensing Cities and Environments
  • Mobile Systems & Interactions
  • Urban Simulation
  • Designing Spatial Data Stories
  • Foundations of Spatial Data Science
  • Agent-based Modelling for Spatial Systems
  • Building Spatial Applications with Big Data
  • Smart Cities: Context, Policy and Government
  • Urban Data Visualisation
  • Data Science for Spatial Systems
  • Deep Learning for Sensor Networks

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