Data Mining









NEW!   Graduate Certificate in Data Mining (18 Credits)

Required Courses (12 Credits)
  • Stat 521 Introduction to Data Mining (4 credits)
  • Stat 522 Data Mining Methods and Models (4 credits)
  • Stat 523 Applied Data Mining (4 credits)

Elective Courses (6 Credits)  
Choose two of:

  • Stat 525 Web Mining

  • Stat 526 Data Mining for Genomics and Proteomics
  • Stat 527 Text Mining
  • Stat 529 Current Issues in Data Mining
  • Some other graduate-level data mining or statistics course, with approval of program coordinator.

Current Students
All students who have been admitted (not conditionally admitted) to the Graduate Certificate in Data Mining should download the 2007 Planned Program of Study, complete as much of it as you can, and email to Dr. Larose at

Students who have been conditionally admitted, and have completed their conditions, should notify Dr. Larose at, so that you may be fully and officially admitted.

Important: Please click here and read this document for important information before applying.

All data mining majors are classified for business purposes as part-time students, with a premium rate, see here.

Program Prerequisites
Applicants to the Graduate Certificate program in Data Mining program are expected to have completed, or be in the process of completing, a second 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 in a graduate field successfully.  A minimum undergraduate GPA of 3.00 on a 4.00 point scale (where A is 4.0), or its equivalent, and good standing (3.0 GPA) in all post-baccalaureate course work is required.  Conditional admission may be granted to candidates with undergraduate GPA�s as low as 2.4, conditioned on the students getting no grades lower than a B in their first three core courses in the program.  

The following materials are required, in addition to the materials required by the School of Graduate Studies.  (1) A formal application essay of 500 � 1000 words that focuses on (a) academic and work history, (b) reasons for pursuing the Graduate Certificate in Data Mining, and (c) future professional aspirations.  The essay will also be used to demonstrate a command of the English language.  (2) A detailed, itemized letter explaining whether and how the candidate has fulfilled the program prerequisites that applicants to the Graduate Certificate in Data Mining program are expected to have completed, or be in the process of completing:  a second semester course in undergraduate or graduate statistics.  In their letter, candidates are asked to show which courses on which transcripts are being used to fulfill each of these prerequisites.  If a candidate has not had courses that would fulfill certain program prerequisites, the candidate should so indicate.  The candidate is reminded that conditional admission may be granted for students needing to complete any or all of the program prerequisites.  (3) 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 that only hard copy materials are acceptable.  No attachments to emails or other electronically transmitted material will be considered in admissions decisions.  

Can I start out with the Certificate program, and then transfer those courses to the Master of Science program?
Yes.  However, the student will need to apply for the MS program separately.  The mathematical and statistical requirements for the MS program are more stringent than for the Certificate program.

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