Combining computer science, statistics, artificial intelligence and technology with liberal arts
Designed by a group of experts with diverse academic backgrounds, this programme trains students in the fundamental principles and practical applications of data science. They learn about the scientific process and computational, mathematical and statistical methods of data collection, along with the essentials of analysis and presentation. This enables them to solve problems that arise in the fields of science, social sciences, the arts and business.
The programme is managed by the Department of Computing and Decision Sciences, which is part of the Faculty of Business. There is also significant assistance from the University’s Science Unit and the Faculties of Arts and Social Sciences. Unlike other Data Science programmes in Hong Kong, the emphasis is on providing a balanced coverage of computer science, statistics/mathematics and artificial intelligence, with a strong liberal arts foundation. The programme also focuses on applications in the fields of science, social sciences, arts and business. This helps students to develop technical skill sets in big data analytics, artificial intelligence, and data visualisation, as well as the ability to hypothesise, experiment, and tells stories with data.
Besides offering lectures and tutorials delivered by outstanding academics at Lingnan, the programme regularly invites practitioners from the worlds of science, social sciences, arts and business to share their experience and know-how. This ensures students acquire practical skills and a wide range of new insights. To enhance their employability, students also take electives that are either application-oriented or advanced-level courses, according to their interests and future career plans.
In addition, the liberal arts training offered by Lingnan helps to hone students’ critical thinking, creativity, and communication skills. The ability to communicate effectively makes it easier for graduates to work in interdisciplinary and cross-cultural teams and organisations other than information technology (IT) companies, which are increasingly aware of the importance of data science.
Graduates are also well-equipped to take on positions as analysts for business enterprises, banks and financial institutions, public utilities, educational institutes, and management consulting firms. Typically, they find starting roles as data scientists, business analysts, database administrators, application developers, and project managers.