Hong Kong Baptist University

DATA MINING AND KNOWLEDGE DISCOVERY (MODULE FROM MASTER OF SCIENCE IN DATA ANALYTICS AND ARTIFICIAL INTELLIGENCE)

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Course Information

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Course Overview

Assessment Methods / 評核方式
(A) Assessment Items and Their Weightings: (1) Continuous Assessment: 40% (2) Examination: 60% (B) Completion Requirements: (1) Exam passing mark: at least 30% (2) Overall passing mark: at least 35% (C) CEF Reimbursement Requirements: (1) Attendance Requirement: 70% (2) Exam passing mark: at least 30% (3) Overall passing mark: 50%

Entry Requirement / 入學要求
(A) Applicants should normally possess a Bachelor degree in science, engineering or IT relevant fields from a recognized university or equivalent qualification; (B) If applicants did not use English as the medium of learning in their Bachelor’s degree programmes, they should satisfy any one of the following English proficiency requirements: (i) An IELTS overall band score of at least 6.0; (ii) A TOEFL score of at least 537 (paper-based) or 74 (Internet-based); (iii) Other equivalent qualifications

Instructor's Qualifications / 導師資歷
At least a relevant Ph.D. Degree

QR Number / 資歷名冊登記號碼
21/000095/L6

QF Level / 資歷架構級別
6

CEF Registration Invalid From / 基金課程登記失效日期
01-SEP-29

What You’ll Learn

(1) Overview of Knowledge Discovery and Data Mining (2 hours) (2) Foundations of Knowledge Discovery (7 hours) (3) Data Mining Techniques (23 hours) (4) Case Studies of Data Mining in Social Network Analysis (5 hours) (5) Case Studies of Data Mining in Other Areas (2 hours)


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