DSCP is a graduate level program centered on the principles of integrating advanced analytic techniques, large and complex data sets, and computer programming. It offers both a theoretical foundation of data science techniques and the pragmatic application of the interdisciplinary skills necessary for effective application of such techniques to real world decisions. Furthermore, students that successfully complete the program will demonstrate the program’s outcomes by developing an operationalized analytic product to address a DoD need.
In order to be considered for admission to the DSCP, candidates must meet the AFIT Graduate School of Engineering and Management requirements for admissions.
Degree Required: A completed bachelor's degree in an appropriate engineering or scientific discipline (mathematics, physical science, engineering, or computer science are highly desirable).
Mathematics Required: Successful completion of undergraduate calculus I, calculus II, and calculus III is required. Moreover, several of the courses offered by the DSCP require candidates to have taken an introductory to probability and statistics class (i.e. STAT 583 Introduction to Probability and Statistics; STAT 587 Applied Probability and Statistical Analysis)
GPA Required: Overall - 3.0; Mathematics - 3.0; Major - 3.0
Waivers to the stated requirements may be granted on an individual basis as approved by the Department of Operational Sciences, through the DSCP Program Manager.
Student Outcomes (SOs)
Dr. Darryl K. Ahner
Degree Type: Certificate
Delivery Method: In-Residence
Degree Requirements
DSCP is designed to support part-time or full-time students looking to specialize in the data science domain. Students will train on open source programming languages and packages that are currently (or projected) supported on DoD systems, thus enabling students to quickly transition with gained data science skills in their immediate follow-on operational assignments. All students are expected to participate in DSCP via in-residence AFIT courses for consecutive quarters until completing the full certificate requirements. Students complete the Analysis Core and then either the Artificial Intelligence, Machine Learning or the Operational Analysis track. Students must attain a grade point average of at least 3.00 for all graded courses comprising the certificate.
Analysis Core
Artificial Intelligence, Machine Learning (Take 2)
Operational Analysis (Take 2)
