Master of Science in Industrial Data Analytics (MScIDA)
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10 th
10
10 th
10 -100
100 st
Becoming Competitive Candidates in the Job Market
Nurturing graduates with expertise spanning embodied artificial intelligence, data science, automatic control, industrial engineering, artificial intelligence, business analytics, and more.
Forward-looking Vision
Among the first in Hong Kong to integrate data science and industrial analytics, this programme will equip students with knowledge in industrial data analytics, data visualization, artificial intelligence, statistics, operations management, control systems, and the Industrial Internet of Things (IIoT).
Data Analytics with Purpose
Fostering students to gain an in-depth understanding of the data generation process, to effectively communicate with various stakeholders, and conduct data analytics guided by two key questions: 1. Where do data come from? 2. Where will data analytics be applied?
Engaging with Real-World Industries
Guiding students to address real-world industrial challenges systematically and comprehensively in various industries such as manufacturing, energy, transportation, logistics, and healthcare through industrial data analytics project.
Break Boundaries, Expand Horizons: Diverse Electives for Limitless Career Opportunities in Data
In line with Lingnan University's holistic education philosophy, the programme goes beyond developing technically proficient industrial data professionals. Students are empowered to customise their learning pathways based on their career goals, broaden their horizons beyond a single industry, and meet the evolving digitalisation needs across diverse sectors.
Alumni Voices
Ms. NI
“The IDA programme helped me understand how data connects with the physical world, where data comes from and how it creates value. Through coursework and projects, I learned to start from the data source and application context rather than simply applying models. This experience enabled me to transit from writing code to solving real industrial problems with data.”
Mr. GENG
“The IDA programme helped me understand how data connects with the physical world, where data comes from and how it creates value. Through coursework and projects, I learned to start from the data source and application context rather than simply applying models. This experience enabled me to transit from writing code to solving real industrial problems with data.”
Mr. Wen
“The programme helped me develop practical data analytics skills. What impressed me most was the process of applying models to real-world problems — from data collection and cleaning to feature understanding, model training, and performance evaluation. Each step required careful consideration of the relationship between the data and the problem. While I was initially more focused on coding, through coursework, research projects, and competitions, I gradually learned how to connect technical tools with real-world applications.”
Q & A
How does the MScIDA curriculum enable “one set of skills to fit multiple industries”?
The programme adopts a customised, cross-industry learning structure comprising 5 core courses and 5 elective courses. The core courses build transferable skills in data analytics and intelligent decision-making, while the electives allow students to develop tailored career pathways in specific industry applications, such as smart logistics, healthcare analytics and ESG. This enables students to apply their skills across different industries.
Does MScIDA have any language requirements?
The language requirements are flexible. Applicants whose previous degree was not taught in English may meet any one of the following requirements: a minimum TOEFL iBT score of 79; an IELTS (Academic) score of 6.0 or above; a minimum 450 in the College English Test Band 6 (CET-6); or an equivalent qualification.
What undergraduate backgrounds are suitable for MScIDA?
The programme values an interdisciplinary perspective and welcomes applicants without an engineering or science background. Applicants with no or limited background in computer science or statistics are required to complete the relevant preparatory courses (Introduction to Computing / Statistics) before the programme commences.