Core and Capstone Courses

This course focuses on the applications of artificial intelligence (AI) in business. Students will learn how various AI techniques can be applied to solve real-world problems in business and economics, such as market analysis, customer relationship management, human resources management, robo-advisors, algorithmic trading, risk management, and economic predictions. Multiple case studies will be used to illustrate how AI can be used to create value in business and solve real world problems. The challenges and concerns in using AI will also be discussed.  

This course offers an introduction to the fundamentals of artificial intelligence. It aims to provide students with foundational knowledge in artificial intelligence models and technologies, including the definition of artificial intelligence, theoretical foundations of artificial intelligence, artificial intelligence models and techniques, and their limitations. Students will acquire hands-on experience in designing and developing models using artificial intelligence and machine learning.

This course aims to equip students with a solid understanding of the important role of artificial intelligence (AI) revolution in today’s global business environment. As AI and digital platforms transform the nature of business and organizational structure across a wide range of industries, mastering the concepts and practices of AI transformation is crucial for managers, entrepreneurs as well as investors. Through disciplined analyses of successful and unsuccessful cases across industry and national borders, this course will provide students with the sophistication to identify, evaluate, and act upon new business opportunities successfully in the global business environment in the AI era.

This course focuses on the responsible use of artificial intelligence (AI). It discusses issues such asethics, fairness, transparency, accountability, and safety associated with the use of AI. It also covers the laws and regulations governing the use of AI both locally and globally and the relevant compliance considerations. Some frameworks and best practices will be introduced. Students are expected to analyze various business cases and business applications and discuss the legal, risk, and ethical issues involved.

The course builds on top of the Fundamentals of AI course and studies some more advanced concepts and knowledge of machine learning and deep learning. Besides basic machine learning models, it will cover ensemble learning and deep neural networks such as convolutional neural networks, recurrent neural networks, transformers and attention mechanisms, generative adversarial networks, and deep reinforcement learning. Students can learn the theory and practical skills involved in the design and implementation of these machine learning and deep learning models. The strengths and weaknesses of each method will be discussed. In addition, students will learn how to evaluate the performance of different types of models and choose the appropriate models in different scenarios.

This course focuses on the intersection of AI, business, and creativity to develop entrepreneurial skills and strategies for creating and launching innovative AI-based ventures. Students will learn how to identify market opportunities, develop business models, secure funding, and navigate the challenges of starting and growing a AI-focused business. The course covers topics such as idea generation, product development, market research, intellectual property protection, marketing strategies, financial management, and pitching to investors. Students will have the opportunity to integrate and apply what they have learned in the programme in a project. They will develop a business plan which will be presented to potential investors.