The graduate certificate program in data mining is a one-year program designed to give students a comprehensive training in basic foundation, advanced knowledge and applications of data mining. It's suitable for students in diverse disciplines who want to extend their knowledge and skills. It is an interdepartmental program involving courses from three departments: mathematics, computer science and geographic information systems.

Admission is dependent upon a student having 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 basic statistics. An international student must satisfy the required minimum TOEFL score as specified in the Graduate Bulletin. The consideration of admission deadline is the same as the University policy as specified in the Graduate Bulletin.
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’s graduate degree program or at the senior level of an undergraduate program, two of the courses listed below can be double counted towards the other degree program. Students must have an earned Bachelor’s degree before receiving the certificate.
Required Courses (15-18 hours)
  • GEO 501 - Principles and Applications of Geographic Information System 3(2-2)
  • STA 575 - Statistical Programming for Data Management and Analysis 3(3-0)
  • STA 580 - Applied Statistical Methods I 3(3-0)
  • 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)
*NOTE 1: GEO 503 can be used to replace GEO 501
**NOTE 2: ITC 510 and 686 can be used to replace STA 575 and 675.

Electives (0-6 hours) Any graduate level quantitative or computational course. 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