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Different course options

Study mode

Full time

Duration

1 year

Start date

SEP-25

Key information
DATA SOURCE : IDP Connect

Qualification type

MSc - Master of Science

Subject areas

Computer Cybernetics

Course type

Taught

Course Summary

Course description

Robotics is increasingly important to a variety of sectors, including manufacturing, healthcare and aerospace. Autonomous systems and robotics, the Internet of Things, smart grids and cloud computing are also being used more widely.

This course helps you develop your knowledge and skills in the key areas of robotics and autonomous systems. You'll learn about machine and artificial intelligence (AI), robotic sensing and perception, control and planning and robotic devices and systems.

You’ll be able to apply your skills across many engineering disciplines and you’ll use industry-standard CAD and hardware tools to design and analyse mechatronic systems.

You can choose optional modules, including working with companies on real opportunities and problems experienced by industry.

You'll also complete a research-level dissertation project where you will take the lead to advance your knowledge and skills in robotics.

Accreditation

Accredited by the Engineering Council UK, Institution of Engineering and Technology and the Institute of Measurement and Control.

Modules

All of our lives are affected by machine intelligence and data models - Google is a very visible example; but if you are a victim of identity theft, if you want a loan to buy a house or if you want to pass through immigration at an airport, a model derived from data using some form of machine learning technique will be involved. Engineers increasingly look to machine intelligence techniques such as neural networks and other machine learning methods to solve problems that are not amenable to conventional analysis e.g. by application of Newton's and Kirchhoff's laws, and other physical principles. Instead, they use measurements of system variables to compute a model of the process that can then be used in design, analysis and forecasting. System identification is a specific example of data modelling. We will look at the underlying principles of machine learning, the advantages and limitations of the various approaches and effective ways of applying them with the aim of making you a competent practitioner.

Tuition fees

UK fees
Course fees for UK students

For this course (per year)

£13,000

International fees
Course fees for EU and international students

For this course (per year)

£29,700

Entry requirements

Minimum 2:1 undergraduate honours degree in an engineering or mathematics subject. We may also consider science subjects with a significant amount of programming modules.