Machine Learning and automated systems have gained wide popularity over the last few years and are becoming mainstream tools in several technologies. In order to be successful in the modern world, everyone should have a basic understanding of how these automated systems work. The goal of this project is to create an automated system that can identify face in a photograph. Such a system can be deployed on the smartphone for detecting and identifying faces. Students will study how to collect and curate high-quality data, how to test and analyze which machine learning algorithms to use, and how to develop an end-to-end automated system.

This case study research project is focusing on China’s three listed stated owned oil and gas companies in Hong Kong Market: PetroChina (HKG: 0857), China Petroleum & Chemical Corp (HKG: 0386), and CNOOC Ltd: (HKG:0883). By analyzing the three company’s IPOs, the project is designed to seek key findings and summaries of the IPO cases, and conduct lessons learnt for future IPOs for similar stated owned energy companies. Students are required to write an academic paper and make a presentation by groups talking about what they have achieved during the project.

In this project-based learning program, students are going to grasp the knowledge of data science through remote online teaching. Its framework contains: optimization of taxi cabs assignment in New York City, classification of Higgs boson, deep neural network and etc. The course integrates many of the key facets of an investigation using data throughout the session: data collection – data wrangling, cleaning, and sampling to get a suitable data set; data management – accessing data quickly and reliably; exploratory data analysis – generating hypotheses and building intuition; prediction or statistical learning; and communication – summarizing results through visualization, stories, and interpretable summaries. Eventually students will complete an academic paper and make a presentation during which they will receive advice from instructors.

With the availability of cheap and ubiquitous computing, analyzing digital images is fast becoming a highly productive area of engineering. Imaging is by far the fastest mode of communication for human beings. The need to distill relevant information from vast distributed image and video databases available on the web, both public and private, generated by industry and medical facilities will become even more critical in the future. This course introduces the fundamentals of Digital Image Processing in the spatial and frequency domain, compression and most importantly segmentation. Segmentation is the first step towards recognizing objects and other information of interest from a scene and will play a critical role in machine vision and robotics.

An IPO case study: Hypothetical firm – an owner and operator of casual-dining restaurants primarily in the United States specializing in Asian cuisine – is seeking an investment bank(s) that could advise the Management and the Board of Directors of the Company on a potential initial public offering (IPO) of the Company. In this program, students play the role as an investment banker, expected to overcome tasks including analyzing the financial and operational situation, building valuating model, forming unlevered DCF analysis and a balance sheet. Students are required to write an academic paper and make a presentation by groups talking about what they have achieved during the project.