Certificate Programme in Data Mining and Machine Learning
資料探勘及機器學習證書

1. Introduction to Data Mining (30hr)
Data are collected everywhere now with advancement in technology, and how to effectively identify patterns and useful information in such data is essential for learning, forecasting and knowledge discovery purposes. The course will provide opportunities for students to learn the basic concepts of data mining and how to discover useful information in daily-life context.


2. Machine Learning Algorithms (30hr)
Machine learning is one of the fastest-growing and exciting areas with wide range of possible applications. In this course, the participants will develop a clear understanding of the motivation for machine learning, and design small-scale intelligent systems that can learn from complex and or large-scale datasets.


3. Applications of Data Mining and Machine Learning (30hr)
This course will help participants to apply data mining and machine learning techniques to practical applications such as stock forecasting, social media marketing and scientific applications.

Assignment, Case Studies, Project and Final Exam.

To qualify for the award of 'Certificate Programme in Data Mining and Machine Learning', students are required to have an attendance rate of 70% or above in each course and have passed the assessments of each course.

This course has been included in the list of reimbursable courses under the Continuing Education Fund. This course is recognised under the Qualifications Framework (QF Level 3).

Course Code: 34C121177
CEF Course Name : Certificate in Data Mining and Machine Learning

A. Online enrollment:

Please submit your application via online enrollment system (click "Online Enrolment" button at programme webpage). Upon the completion of online enrollment (including "Computer Knowledge and Other Skills" field), please email copies of the supporting documents to scs-it@cuhk.edu.hk:
• Copies of academic qualifications (e.g. award certificate / final transcript);
• Copies of proof of working experience, if applicable (e.g. reference letter or employment letter).


B. Enrollment by paper form:

Applicants are required to submit the following documents:
• A duly completed "Enrolment Form for Certificate and Diploma/Professional Programmes" (please include the "Computer Knowledge and Other Skills" field);
• Copies of academic qualifications (e.g. award certificate / final transcript);
• Copies of proof of working experience, if applicable (e.g. reference letter or employment letter);
• Application Fee of $150 (Please click here for payment methods).

Please submit to the enrolment form and supporting documents to any one of our School's Enrolment Centres in-person; OR post to the Programme Team at:

17/F, Oriental Centre, 67 Chatham Road South,
Tsim Sha Tsui, Kowloon, Hong Kong
(Attn: Information Technology Programme Team - Application of Certificate Programme in Data Mining and Machine Learning)

Admission will be assessed on a first-come-first served basis for qualified applicants. Thus, early enrollment is encouraged.

1. Who is this Certificate Programme in Data Mining and Machine Learning suitable for? Can I join without a data science background?
Yes. The programme is designed for working professionals, aspiring data analysts, IT practitioners, business professionals, and career switchers who want to develop practical skills in data mining and machine learning.

While a formal background in data science is not required, applicants should have basic knowledge of programming and databases. The curriculum begins with the fundamentals of data mining before progressing to machine learning algorithms and real-world applications, making it suitable for learners who are new to data science but have some technical foundation and an interest in data-driven decision-making.

2. What will I learn in the programme?
This 90-hour programme combines practical training with foundational knowledge in data mining and machine learning. Students will gain hands-on experience using Python, one of the most widely used programming languages in data analytics, machine learning, and artificial intelligence.

The curriculum is organised into three modules:
1. Introduction to Data Mining - Pattern recognition and knowledge discovery, Identifying meaningful insights from everyday data, Core concepts and techniques in data mining.
2. Machine Learning Algorithms - Fundamental machine learning concepts and methodologies, Designing simple intelligent systems, Learning from complex and large datasets.
3. Applications of Data Mining and Machine Learning - Predictive analytics and forecasting, Marketing analytics, Business and scientific applications, Ethical and privacy considerations in data use.

Rather than focusing heavily on advanced mathematics, the programme emphasises practical applications that can be applied directly in professional and business environments.

3. How is this programme different from a general data science course?
Many introductory data science courses cover a broad range of topics, including statistics, programming, and data visualisation. This programme takes a more focused approach by concentrating on how data mining and machine learning techniques can be used to uncover patterns, generate insights, and support better decision-making.

Key features include:
- Practical application of machine learning techniques using Python
- Hands-on assignments, case studies, and project-based learning
- Real-world applications such as forecasting, marketing analytics, and business intelligence
- Coverage of data ethics, privacy, and responsible use of AI

For professionals working in business, finance, marketing, operations, technology, or related fields, the programme provides a practical foundation for applying machine learning and data-driven approaches within their own organisations.

4. Why choose to study Certificate Programme in Data Mining and Machine Learning?
As organisations increasingly rely on data to guide decisions, skills in data mining and machine learning have become valuable across a wide range of industries, including finance, marketing, healthcare, logistics, technology, and business operations.

This programme helps participants develop the ability to analyse data, identify meaningful patterns, and apply predictive techniques to real-world problems. Through hands-on learning and practical case studies, students can strengthen their data literacy and gain a better understanding of how machine learning is being used in today's business and technology environments.

Whether you are looking to enhance your current role, broaden your analytical capabilities, or build a foundation for further studies in data science and artificial intelligence, the programme offers practical and immediately applicable knowledge.