Data Mining, Graduate Certificate
College of Science and Engineering
Minimum Totals for Graduation: 15 - 18 hours
The Data Mining Certificate program is designed to give each student a comprehensive training of basic foundation, advanced knowledge and applications of data mining. The primary goal is to develop a high quality program and a creative learning environment that enable students to acquire advanced data mining knowledge and experience in real world applications, team work and presentations that are essential in work place.
Admission Requirements, Retention & Termination Standards
Admission Requirements
- Applicants must meet all CMU Graduate Studies admission requirements. International students should take note of any special admission considerations required by the College of Graduate Studies, including TOEFL requirements.
- Applicants must have completed at least three years of undergraduate program with a minimum GPA of 3.0 overall, completion of Linear Algebra, Calculus I or Business Mathematics or Discrete Mathematics, and at least 3 credit hours of statistics.
- Applicants must submit a Statement of Purpose of at least 100 words and not to exceed two pages. The Statement of Purpose should explain their relevant academic and professional experiences, discuss motivation for applying to the program, and describe their goals after completing the program.
- The consideration of admission deadline is the same as the University policy as specified in the Graduate Bulletin.
Certificate Requirements
The Data Mining certificate program requires a successful completion of 15 to 18 credit hours of graduate course work. Students must have CMU graduate student status. If a student has taken at least one course (or equivalent course) from the list of required courses, the student is required to have a total of 15 credit hours. If a student has taken more than one of these courses, the student will have to take courses from the electives in order to fulfill the 15 hours requirement. If a student has not taken any of these courses, the student is required to take all the 18 credit hours. If a student is currently in another CMU graduate degree program or at the senior level of an undergraduate program, two of the courses listed below can be double counted toward the other degree program. Students must have an earned Bachelor's degree before receiving the certificate.
Required Prerequisite Courses (0-6 hours)
| STA 575 | Statistical Programming for Data Management and Analysis | 3(3-0) |
| STA 580 | Applied Statistical Methods I | 3(3-0) |
Notes:
- A student without the background equivalent to the above courses are required to take both courses.
- A student with a background equivalent to one of the above two courses should take the other course.
- A student with background equivalent to the above two courses should not retake any of the two courses, but is required to take three hours of elective course.
- ITC 510 can be used to replace STA 575.
Required Courses (12 hours)
| GEO 501 | Principles of Geographic Information Systems | 3(2-2) |
| STA 591 | Data Mining Techniques I | 3(3-0) |
| STA 675 | Advanced Statistical Data Management and Simulation | 3(3-0) |
| STA 691 | Advanced Data Mining Techniques | 3(3-0) |
Electives (0-6 hours)
Any graduate level quantitative or computational course. Secondary electives are to be chosen in consultation with and approval of a data mining program advisor. Some examples include GEO 512, ITC 510, ITC 686, STA 582, STA 583, STA 587, STA 589, STA 590.
Total: 15-18 semester hours