Program Overview

MSc Autonomous Robotic Intelligent Systems

The MSc Autonomous Robotic Intelligent Systems is designed to equip students with the applied, industry-relevant expertise needed to thrive in the dynamic and fast-growing field of autonomous systems, artificial intelligence, and modern robotics. This course provides a comprehensive understanding of how intelligent systems are designed, built, and deployed, with a focus on real-world applications in robotics, sensor networks, and digital manufacturing.

Course Overview

• The course is delivered through a blended learning approach, combining in-person and online methods to provide a flexible and engaging educational experience.
• Teaching methods include lectures, problem-solving tutorials, and hands-on, project-based laboratory sessions.
• Each module typically includes five hours of direct contact time per week, with at least five additional hours of independent study supported by the University's virtual learning environment, digital research resources, and library facilities.

Course Content

• Compulsory modules:
  • Intelligent Sensing & Reasoning through Machine Learning (10 credits)
  • Neural Networks & Deep Learning (10 credits)
  • Manufacturing Automation (10 credits)
  • Mechatronic Systems Design Techniques (10 credits)
  • Robotics & Control Systems (20 credits)
  • Sensor Technologies (20 credits)
  • Assignment & Professional Studies (20 credits)
• Optional modules (indicative list, subject to change):
  • Strategic Technology Management (10 credits)
  • Product Modelling & Visualisation (10 credits)
  • Design Methods (10 credits)
  • Digital Manufacturing Concepts (10 credits)
  • Systems Thinking & Modelling (10 credits)
  • Embedded Systems Design (20 credits)
  • Design Management (10 credits)
  • Design for Industry 4 & Smart Products (10 credits)
  • Micro & Nano Manufacturing (10 credits)
  • Advanced Forming Technology Systems (10 credits)
  • Advanced Materials & Production Technology (10 credits)
  • Advanced Microcontroller Applications (20 credits)
  • Image & Video Processing (20 credits)
  • Control Principles (20 credits)
  • Advanced Digital Signal Processing (20 credits)
  • Knowledge & Information Management for Engineers (10 credits)

MSc Project

• The MSc Project is a substantive piece of independent work demonstrating mastery of a specialist area.
• The project involves an in-depth investigation on a topic chosen by the student within the field of electronic or electrical engineering.
• Projects may be research-based, aligned with current departmental research themes, or industry-based, conducted as an unpaid internship with one of the department's partner companies.

Learning & Teaching

• The course is designed to equip students with advanced technical expertise, while also developing essential leadership, project management, and professional engineering skills.
• The MSc is delivered through a blended learning approach, combining both in-person and online methods to provide a flexible and engaging educational experience.

Assessment

• Each module employs a variety of assessment methods designed to maximize learning and help students realize their full potential.
• Assessment methods may include coursework, examinations, lab reports, presentations, group projects, and the final MSc Project.
• The project is assessed based on the technical quality and contribution of an interim and final report, a poster presentation, and demonstrated initiative, independent thinking, and project management skills.

Professional Development & Employability

• The course is designed to help students build a strong professional network and enhance their employability.
• The MSc offers access to cutting-edge facilities and state-of-the-art laboratories, guidance from academic experts, and opportunities for industry engagement through internships, guest seminars, careers events, and networking sessions.

Entry Requirements

• Academic requirements: Normally a first-class or second-class honours degree (or international equivalent) in electronic, electrical, communications, or design manufacture engineering, or a science-related subject.
• English language requirements: If English is not the first language, please visit the University's English language requirements page for full details of the requirements in place before making an application.

Fees & Funding

• All fees quoted are for full-time courses and per academic year unless stated otherwise.
• Fees may be subject to updates to maintain accuracy.
• Tuition fees will be notified in your offer letter.
• The University offers a range of scholarships to help with fees and funding.

Careers

• The global robotics and smart machines market is projected to grow significantly over the next decade, driven by advances in AI, automation, and digital transformation.
• Employers are actively seeking graduates who can bridge the gap between theoretical knowledge and practical application—precisely the kind of expertise this MSc delivers.
• Potential career paths include Robotics Engineer, AI & Machine Learning Specialist, Systems Integration Engineer, Smart Manufacturing Consultant, IoT Solutions Architect, and R&D Engineer.