MSc MSc Creative Robotics

The standard minimum entry requirements for this course are:

• An honours degree in a relevant subject such as Computer Science, Data Science, Computing, Mechanical or Electrical Engineering, Joint Computer Science / Arts, Humanities programme.
• OR an honours degree from a creative discipline with substantial computational practice such as interaction design, computer science, digital design, product design, mechanical or electric engineering, design engineering. 
• OR a professional qualification recognised as equivalent to an Honours degree in a design-related or creative engineering discipline. 
• AND typically, at least Grade B/Grade 6 at GCSE Mathematics.

APEL - Accreditation of Prior (Experiential) Learning

Applicants who do not meet these course entry requirements may still be considered in exceptional cases. The course team will consider each application that demonstrates additional strengths and alternative evidence. This might, for example, be demonstrated by:

• Related academic or work experience
• The quality of the personal statement
• A combination of these factors

Each application will be considered on its own merit, but we cannot guarantee an offer in each case.

English language requirements 

• IELTS 6.5 (or equivalent) with a minimum of 5.5 in reading, writing, listening and speaking.

All classes are taught in English. If English isn’t your first language, you will need to show evidence of your English language ability when you enrol. For further guidance, please check our English language requirements.

Developing your skills

Computing graduates are highly sought after across sectors and our degrees facilitate progression to a wide range of careers in both industry and academia. Graduates can join large companies or start their own business using their engineering skills and their knowledge of computational innovation.

Career paths

Graduates can become:

Term 1

Coding for Robotics 

This unit explores the fundamental principles of programming and human-machine communication in creative robotics. Through theoretical study and practical tutorials, students examine how machines interact with the world, learning algorithmic thinking and increasingly complex programming concepts. Following the practice-led approach, students develop skills and gain practical experience in cybernetics, object-oriented programming and real-world data representation in computer systems. 

This unit has the explicit aim of equipping you with an advanced programming foundation to tackle creative robotics programming through the rest of the course.

Critical Robotics: Studies and Research Methods 

This unit introduces the key aspects of the research process and interdisciplinary methodologies for creative robotics research. You will approach qualitative, quantitative, visual and applied methods from the fields of computing and design methodologies, such as critical and speculative design. You will explore the history of robotics and human-robot interaction. Taking a design thinking approach, you will also engage with critical thinking and coherent robotics proposals. During the course you will also encounter practical examples of creative robotics from industry and academia, including applications in performing arts, theatre, dance, and other innovative contexts.

Embedded Systems and Soft Robotics

This unit introduces the foundational principles and practical skills required to design and build interactive physical systems. Students will explore key topics such as embedded systems, machine elements, sensors, actuators, and compliant robotics, learning how these components integrate to create adaptive and responsive systems. Through hands-on projects and practical exercises, students will develop both technical proficiency and creative problem-solving abilities. Emphasis is placed on designing systems that meaningfully engage with their environments while considering their broader social and ethical implications. 

Term 2

Introduction to Machine Learning 

This unit examines application of generative techniques to 3D structures, images, and music, further introducing students to machine learning (ML) and applying it to human recognition tasks. Students explore how machine systems can create synthetic representations of the real-world data introduced in the previous module. Unit then introduces different ML frameworks and their applications in systems for human perception, such as motion capture, facial recognition, and speech processing. Through these frameworks, students develop the understanding of explainability in the human-machine interaction systems. 

Critical Robotics: Studies and Research Methods - Continued

See above