香港城市大學專業進修學院

CERTIFICATE IN DATA MINING AND MACHINE LEARNING 資料探勘及機器學習證書

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課程資料

課程級別
學習模式
地點
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課程簡介

Assessment Methods / 評核方式
(A) Assessment Items and Their Weighting: (1) Module 1 to Module 2: - Final Exam: 40% - Assignment: 40% - Case Studies: 20% (2) Module 3: - Final Project: 50% - Assignment: 50% (B) Completion Requirements and CEF Reimbursement Requirements: (1) At least 70% of the total contact hours of the CEF course (2) obtain overall pass grade D (which is equivalent to 50%) for each module.

Entry Requirement / 入學要求
APPLICANTS SHALL HAVE BASIC KNOWLEDGE OF DATABASE* AND COMPUTER PROGRAMMING+, AND 1. COMPLETION OF SECONDARY EDUCATION, OR EQUIVALENT; OR 2. AGED 21 OR ABOVE. REMARKS: * DATABASE SUCH AS ACCESS, MYSQL, ETC + COMPUTER PROGRAMMING SUCH AS PYTHON, JAVA, ETC.

Instructor's Qualifications / 導師資歷
QUALIFIED TEACHING STAFF WILL BE DRAWN FROM LOCAL UNIVERSITIES AND THE INDUSTRIES WITH A MINIMUM OF TWO YEARS' TEACHING EXPERIENCE IN RELEVANT DISCIPLINES OR EQUIVALENT PROFESSIONAL EXPERIENCE, AND EITHER WITH: A) MASTER DEGREE IN RELATED FIELDS; OR B) BACHELOR DEGREE WITH RELEVANT PROFESSIONAL CERTIFICATION / WORKING EXPERIENCE

QR Number / 資歷名冊登記號碼
18/000239/L3

QF Level / 資歷架構級別
3

CEF Registration Invalid From / 基金課程登記失效日期
23-SEP-27

課程內容

Module 1: Introduction to Data Mining (28 Hrs + 2 Hrs Exam) Module 2 Machine Learning Algorithms (28 Hrs + 2 Hrs Exam) Module 3: Applications of Data Mining and Machine Learning (30 Hrs) *The sequence of delivery may vary in different intakes. [CUSCS exemption policy: A module taken at CUSCS or elsewhere will be recognized as equivalent to a CUSCS module if it is comparable in objectives and learning outcomes as well as QF Level or academic standard, and provides the student with sufficient knowledge to pursue his/her study at CUSCS. The total no. of hours* exempted should not exceed 50% of the total amount of CUSCS programme studied. *Applicable for part-time programmes.]


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