Course Structure
Upon completing the foundation module, students will choose one of seven tracks to delve deeper into the effects of AI and data science on society and innovation. The course includes group study, PBL method, and a group project.
I. Foundation Module
Students will choose the Machine Learning or Data Science module to build a foundation for subsequent studies.
II. Application Track
Students will choose from one of the subjects to start their PBL research journey.
III. Academic Literacy Module
A well-established research literacy programme will provide students with effective guidance at every key point.
AI & Society
Understand what AI is and consider how it will affect society.
Learning Algorithms
Become familiar with a variety of learning algorithms.
AI & the Physical World
Discuss applications of AI where AI techniques are applicable.
Choose One of the Seven Tracks
Deep Learning & Neural Networks
Artificial neural networks (ANNs) are algorithms that mimic the human brain. They consist of four main components: inputs, weights, a bias or threshold, and an output. They are used to cluster and classify data, and to solve a wide variety of problems such as machine vision and speech recognition. Deep Learning is a term used for neural networks with multiple layers.
Advanced Machine Learning & Machine Intelligence
This track covers advanced machine learning topics with a focus on probabilistic approaches, including probabilistic models, approximate inference methods, Gaussian processes, Bayesian neural networks, and Bayesian optimisation algorithms. The module will explore the available methods for approximate inference and their application in widely used probabilistic models for efficient optimisation of expensive black-box functions.
Biotechnology Engineering & Healthcare Technology
Artificial intelligence in healthcare can help improve diagnoses, identify at-risk populations, manage resources, forecast research potential, and understand patient responses to medicine. It also allows for more efficient treatment, even remotely. Additionally, it may enable developing countries to surpass developed countries in healthcare delivery.
Digital Construction & Management
Construction professionals use AI and digital technology to improve asset delivery and operation. This track encourages students to take a holistic approach to identifying and utilising new technology opportunities throughout the asset lifecycle. While digital techniques and AI are already being used in the industry, their potential is vast and opportunities for young professionals entering the field are exciting.
Sustainable Energy & Battery Technology
New materials drive society's technological advances, from batteries to quantum computers. Computational materials discovery provides a faster, systematic, and cheaper way to develop new materials and accelerate technological progress. This track explores how computational methods, with a focus on machine learning, can be used to speed up materials discovery. It will include applications in energy materials for sustainability.
Quantum Computing
This track covers what quantum technologies are, their history, and their current and potential uses. It examines the foundations of quantum mechanics, their impact on our understanding of the world, and how they led to novel devices in computing, data storage, information processing, and other fields. It will provide an understanding of this often-misunderstood branch of science.
Electronic & Information Engineering
Electrical and electronic engineers use technology to improve electronic equipment, power distribution, and communication. They overlap with AI applications in machine learning and optimisation systems, and provide AI with new data inputs. This track explores the latest engineering applications of AI, which may lead to career advancement in the field.
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