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Courses List
List of Courses of the Big Data Analytics Program
(available for students apply for enrollment as of academic year 2018)
(available for students apply for enrollment as of academic year 2018)
R: Required course
E: Elective course
E: Elective course
Course Name |
Course Type |
Semester | Credit |
Calculus/ Linear Algebra | R | 1 | 3-4 |
Statistics/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 |
Required Courses Credits:14 Elective Courses Credits:12 |
Total Credits: 26 |
※Minimum course credits needed for completion: 26 credits
※Electives (12 credits)
1. In addition to the required courses, students must select at least four electives.
2. If a course is a required course of the student’s original department, the credits of this course will be excluded from the program. If a course is an elective the student’s original department, only two will be recognized.
※Programming or Related Courses: Except for courses offered by the Department of Statistics, Department of Information Science, Department of MIS, and Department of Applied Mathematics which will be directly recognized by the program, students must submit the syllabus to the program committee for approval before they can substitute the Programming or Related Courses offered by other departments. Students cannot substitute the Programming or Related Courses of this program with the Programming or Related Courses offered by General Education.
※Description: When selecting electives in the program not from the departments listed above, students must substitute them with electives of the same name or containing similar contents. Students should also submit the syllabus of the course to the program committee for approval before selection.
※Electives (12 credits)
1. In addition to the required courses, students must select at least four electives.
2. If a course is a required course of the student’s original department, the credits of this course will be excluded from the program. If a course is an elective the student’s original department, only two will be recognized.
※Programming or Related Courses: Except for courses offered by the Department of Statistics, Department of Information Science, Department of MIS, and Department of Applied Mathematics which will be directly recognized by the program, students must submit the syllabus to the program committee for approval before they can substitute the Programming or Related Courses offered by other departments. Students cannot substitute the Programming or Related Courses of this program with the Programming or Related Courses offered by General Education.
※Description: When selecting electives in the program not from the departments listed above, students must substitute them with electives of the same name or containing similar contents. Students should also submit the syllabus of the course to the program committee for approval before selection.