課程資料
時間表
- 2026年4月14日(週二) 下午 6:45 - 下午 9:45
報名日期
2025年12月29日(週一) - 2026年3月13日(週五)
價錢
CEF可獲發還款項課程
課程級別
學習模式
修業期
90 小時
教學語言
廣東話, 英語
地點
Central Learning Centre
2次瀏覽
課程簡介
Objectives
This programme is targeted for participants who are interested to learn how to extract and analyze data to obtain valuable information and knowledge by using the popular data mining and machine learning algorithms. While theoretical and mathematical knowledge will also be introduced, the programme will focus on real-life applications of readily available data mining and machine learning techniques and algorithms to help participants to apply the knowledge at their own context. Common data mining tools such as R and Python will be used for the students to do hands-on practices. Ethical and privacy issues will also be discussed.
Admission Requirement
Applicants shall have basic knowledge of database* and computer programming+, and
1. completion of secondary education, or equivalent; or
2. aged 21 or above.
Remark:
* database such as Access, MySQL, etc
+ computer programming such as Python, Java, etc.
Assessment
Assignment, Case Studies, Project and Final Exam.
Award of Certificate
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.
Start Date
14 April 2026
Time
6:45pm - 9:45pm (one lesson per week)
Closing Date for Application
13 March 2026
課程內容
Content
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.
