Graduate Certificate in Data Mining

Program Prerequisites:

Applicants to the Graduate Certificate in Data Mining program are expected to have completed a first semester course in undergraduate or graduate statistics. Students may be admitted on condition that they complete these prerequisite courses with a grade of B or better.

Admission Criteria:

Students must hold a bachelor's degree from a regionally accredited institution of higher education. The undergraduate record must demonstrate clear evidence of ability to undertake and pursue studies successfully in a graduate field.

A minimum undergraduate GPA of 3.00 on a 4.00 point scale (where A is 4.00), or its equivalent, and good standing (3.00 GPA) in all post-baccalaureate course work is required. Conditional admission may be granted to a candidate with an undergraduate GPA as low as 2.40, only if the student receives no grades lower than a B in his/her first three core courses in the program.

The following materials, in addition to those required by the School of Graduate Studies, are required:

  • a formal application essay of 500-1000 words, focusing on (a) academic and work history, (b) reasons for pursuing the Graduate Certificate in Data Mining, (c) future professional aspirations, and (d) where and how the applicant has completed the program prerequisite: a first-semester course in statistics. The essay will also be used to demonstrate a command of the English language; and
  • two letters of recommendation.

The application and all transcripts should be sent to the Graduate Admissions Office. The other materials, including the formal application essay, the prerequisites letter, and the two letters of recommendation, should be sent to:

Dr. Daniel T. Larose

Re: Graduate Certificate in Data Mining Admissions Materials

Department of Mathematical Sciences

Marcus White 118

Central Connecticut State University

New Britain, CT, 06050

Note: Only hard copy materials are acceptable. No attachments to emails or other electronically transmitted material will be considered in admission decisions.

Course Requirements (18-20 credits):
Required Courses (12 credits)
STAT 521 Introduction to Data Mining 4
STAT 522 Clustering and Affinity Analysis 4
STAT 523 Predictive Analytics 4
Elective Courses (6-8 credits)
Choose two of:
STAT 520 Multivariate Analysis for Data Mining 4
STAT 525 Web Mining 3
STAT 526 Data Mining for Genomics and Proteomics 4
STAT 527 Text Mining 4
STAT 529 Current Issues in Data Mining 3

Some other graduate-level data mining or statistics course, with approval of program coordinator.

More information can be found at:

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