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Ling U

Ling U

Ling U

Ling U

Ling U

MSc in Artificial Intelligence and Business Analytics (MScAIBA)

Programme Information

Programme Website https://aiba.ln.edu.hk/
Special Features
  • It provides students with knowledge that spans the core disciplines of Artificial Intelligence (AI) and business analytics, and integrates various disciplines to allow students to better understand all aspects of AI and business analytics and how they are used in the real world.
  • It takes into consideration more practical business applications and frontier technologies by combining AI and business analytics with blockchain, marketing, healthcare, geographical information systems, and optimisation. Thereby enhancing the competitiveness of graduates in the job market.
  • It serves a wide range of professionals, decision and policy makers who need to process and analyse big data. It is also ideal for healthcare and public utility sector practitioners who understand the importance of AI and business analytics in enhancing the quality of society and effectiveness of operations.
  • It develops students’ analytical and critical thinking, as well as their problem-solving skills, which enables graduates to pursue careers as business analysts, data analysts, data scientists, and AI consultants/experts across various industries
Mode of Study Full-time
Programme Duration
  • Normal: 1 year
  • Maximum: 3 years
Medium of Instruction English
Credits Required 30
Modules Required 10 (Core courses: 6; Electives courses: 4)
Pre-entry Course Applicants with no or limited background in computer science or statistics will be required to complete non-credit-bearing pre-entry course(s) on, Introduction to Computing or Statistics, prior to the start of the programme.
Tuition Fees (for 2024/25)
  • Local students: HKD278,000 per programme
  • Non-local students: HKD278,000 per programme

The tuition fees above do not cover pre-entry courses.

Programme Coordinator Prof. SEE-TO Wing-kuen, Eric
BEng(CUHK), MBA(HKU), PHD(HKUST)
Offering Unit Department of Computing and Decision Sciences