Throughout this course, one learns how to take a transdisciplinary approach to look out for, and capture, the similarities and structures of the dynamics of different systems and processes, how to extract useful information from typically large amounts of data generated by such systems, and how to optimise and control their behaviour. The course will cover the relevant theories, design methodologies and implementation techniques within the areas of system modelling, signal processing, dynamics and systems, automatic control, computer vision, machine learning and computational intelligence. On course completion, these skills and knowledge could be applied across a wide range of professional areas such as system automation, process control, biomedical engineering, manufacturing, transport and robotics, to name but a few.

The Course shall be open to applicants in possession of one of the following qualifications: (a) the degree of Bachelor of Engineering (Honours) with at least Second Class Honours or (b) the degree of Bachelor of Science (Honours) with at least Second Class Honours in appropriate subjects as approved by the Board or (c) the degree of Bachelor of Science in Information Technology (Honours) with at least Second Class Honours or (d) the degree of Bachelor of Science in Information and Communication Technology (Honours) with at least Second Class Honours or (e) any other Honours degree with a suitable mathematical and computer programming component which the Board deems comparable to the qualifications indicated in paragraphs (a), (b), (c) or (d).