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Courses List
List of Courses of the Big Data Analytics Program
※Minimum Program Credit Requirement: 26 credits
※Required Courses minimum 14 credits
※Elective Courses (12 credits)
• At least four elective courses are required in addition to the required courses.
• Required courses from the student’s home department are not counted.
• A maximum of two elective courses from the student’s home department may be counted.
※Programming or related courses:
• Courses offered by Statistics, Information Management, Computer Science, and Applied Mathematics departments are directly recognized.
• Courses from other departments must be checked against the “Compilation Table of Previously Approved Substitutes.”
• If not listed, students must submit a substitution application with the syllabus and transcript, subject to Program Committee approval.
• General education courses cannot be used as substitutes.
Program Committee Resolution (April 21, 2023):
• Course substitution applications must be submitted before enrollment.
• Deadline: two weeks before course selection begins.
• Effective from the 2024–2025 academic year.
• Review process: preliminary approval by Program Committee, then consultation with either the department chair, instructor, or committee representative.
• Course substitution applications must be submitted before enrollment.
• Deadline: two weeks before course selection begins.
• Effective from the 2024–2025 academic year.
• Review process: preliminary approval by Program Committee, then consultation with either the department chair, instructor, or committee representative.
R: Required course
E: Elective course
E: Elective course
| Course Name | Course Type |
Semester | Credit |
| Calculus/ Linear Algebra | R | 1 | 3-4 |
| Statistics I/Statistical Analysis | R | 1 | 3 |
| Regression Analysis I | R | 1 | 3 |
| Data Structure | R | 1 | 3 |
| Business Data Analytics: R Computing / Business Analytics with SAS/R/ Programming and Statistical Software | R | 1 | 2-3 |
| Regression Analysis II | E | 1 | 3 |
| Multivariate Analysis | E | 1 | 3 |
| Time Series Analysis | E | 1 | 3 |
| Categorical Data Analysis | E | 1 | 3 |
| Business Analytics Practice with SAS/R | E | 1 | 3 |
| Statistical Data Analysis | E | 1 | 3 |
| Text Mining and Big Data Analytics Using SAS | E | 1 | 3 |
| Programming or related courses* | E | 1 | 3 |
| Algorithms | E | 1 | 3 |
| Information Management | E | 1 | 3 |
| Database Management Systems | E | 1 | 3 |
| Database System | E | 1 | 3 |
| Optimization / Optimization Theory/ Management Science/ Operations Research | E | 1 | 3 |
| Database Marketing/ Internet Marketing | E | 1 | 3 |
| Business Intelligence | E | 1 | 3 |
| Data Mining | E | 1 | 3 |
| Cloud Application Programming/Community Cloud Computing | E | 1 | 3 |
| Hadoop System Design or related courses | E | 1 | 3 |
| Machine Learning Technology or related courses 【Including: Modern Machine Learning Techniques, Data Science in Practice】 | E | 1 | 3 |
| Internet Search and Mining | E | 1 | 3 |
| Theory of Probability | E | 1 | 3 |
| Numerical Analysis | E | 1 | 3 |
| Practical Issues of Big Data Analytics | E | 1 | 3 |
| User Experience Design | E | 1 | 3 |
|
Required Courses Credits：14 Elective Courses Credits：12 |
Total Credits: 26 | ||
※Minimum Program Credit Requirement: 26 credits
※Required Courses minimum 14 credits
※Elective Courses (12 credits)
• At least four elective courses are required in addition to the required courses.
• Required courses from the student’s home department are not counted.
• A maximum of two elective courses from the student’s home department may be counted.
※Programming or related courses:
• Courses offered by Statistics, Information Management, Computer Science, and Applied Mathematics departments are directly recognized.
• Courses from other departments must be checked against the “Compilation Table of Previously Approved Substitutes.”
• If not listed, students must submit a substitution application with the syllabus and transcript, subject to Program Committee approval.
• General education courses cannot be used as substitutes.
