Data Mining and Analytics, Graduate Certificate
The Graduate Certificate in Data Mining and Analytics (DataMA) provides marketable data mining and analytics skills grounded in the technology and computing principles and constructs a solid foundation for further education. DataMA is a pathway to the Master of Science in Data Science (MSDS) and Doctor of Information Technology (DIT).
Admission Requirements
City University of Seattle's graduate admission requirements, found under Admissions in the catalog menu, apply to this program.
Total Required Credits (12 - 32 Credits)
Preparatory Courses (6 or 20 Credits)
Preparatory courses may be required for students entering the DataMA Graduate Certificate without sufficient related experience in programming, SQL/NO SQL databases, networking, and operating systems. The breadth-first preparatory courses are recommended for students who want to study a broad spectrum of all topics within 1 quarter. The depth-first preparatory courses are recommended for students who want to study each topic in depth. Please see the program admissions criteria in the City University of Seattle catalog for specific information.
Breadth-First Preparatory Courses (6 Credits)
| CS 11A | Technology & Computing Components I | 3 |
| CS 11B | Technology & Computing Components II | 3 |
Depth-First Preparatory Courses (20 Credits)
| CS 132 | Computer Science I * | 5 |
| (or) | |
| IS 201 | Fundamentals of Computing | 5 |
| CS 330 | Network Communications * | 5 |
| CS 340 | Operating Systems * | 5 |
| IS 360 | Database Technologies * | 5 |
Data Mining and Analytics (12 Credits)
| DS 515 | Data Science Overview | 3 |
| DS 520 | Data Mining | 3 |
| DS 522 | Data Acquisition and Analytics | 3 |
| DS 524 | Data Management and Governance | 3 |