Program: Business Analytics and Operations - Decision Sciences Specialization, PhD - University of Pittsburgh

Curriculum

PhD students must take three courses in the core plus 15 credits from the following advanced seminars or other approved electives. With the advisor’s approval, students may substitute any of these courses with appropriate graduate-level courses from statistics, economics, or engineering disciplines.

Advanced Seminars:

BQOM 3014 - NETWORKS
BQOM 3017 - ADV TOPICS OPERATIONS RESEARCH
BQOM 3018 - DECISN MAKING IN COMPLX ENVRN

The Secondary Area of Study Consists of:

BQOM 3011 - LINEAR PROGRAMMING
BQOM 3013 - STOCHASTIC PROCESSES and
one other approved PhD seminar from among those given above or from other approved electives

Note:

The Data Mining and Business Analytics specialization requires a minimum of eight courses, selected by the student in consultation with a faculty advisor, that cover the following core topics: (1) AI programming techniques, (2) mathematical optimization theory, (3) AI theory, (4) problem-solving and modeling techniques, (5) probability and statistics, and (6) networks and graph theory. Advanced seminars and electives should reflect the student’s interests and intended area(s) of application. Students are encouraged to do research in areas of current faculty interest, for the opportunity to develop and use data mining techniques in management.