Aims and Fit of Module

This module aims to equip students with AI-centric technology fundamentals specifically tailored for intelligent robotics, alongside an understanding of industrial applications and future trends. Key topics include fundamental data processing and core AI techniques such as machine learning, computer vision, natural language processing, and reinforcement learning.

Beyond technical theory, students will explore the commercial landscape, including state-of-the-art robotic applications and the ethical implications of autonomous systems. Equipped with the knowledge and skills taught in this module, students will obtain a clear picture of how AI empowers physical agents. They will learn to apply code-based LLMs and deploy embedded AI algorithms to solve real-world problems in the context of embodied intelligence.

Learning outcomes

A. Identify the state-of-the art industrial and commercial applications of AI.
B. Demonstrate how basic concepts of AI models and techniques may be applied in real-world applications.
C. Discuss the AI-centric Technology Perspectives and their impact on industries

Method of teaching and learning

The teaching philosophy of the module follows very much the philosophy of Syntegrative Education. This has meant that the teaching delivery pattern, which follows more intensive block teaching, allows more meaningful contribution from industry partners. This philosophy is carried through also in terms of assessment, with reduction on the use of exams and increase in coursework, especially problem-based assessments that are project focused.

The delivery pattern provides space in the semester for students to concentrate on completing the assessments. This module will be delivered by a combination of formal lectures, seminars, and computer labs. The lectures cover the content outlined in the syllabus, introducing technology fundamental topics and market analysis and industry trends. Labs are designed to equip students with essential programming and hands on skills in module-related areas. Through individual project, students gain practical experience in implementing and experimenting with technology fundamentals and undertaking independent study and research on industry focused real-world problems. The lecture component of this module will provide students with a comprehensive overview of the core concepts and theories of AI-centric technology fundamentals. Case studies will be used to provide students with real-world examples of how the concepts and techniques covered in this module can be applied. Lab/Practical sessions will allow students to apply the techniques, data analytics tools to solve real-world industry focused problems and conduct market and industry analysis.