Page 65 - Graduate Studies Bulletin

GRADUATE STUDIES BULLETIN

EM 574 Energy Resources Management
Credits: 3(3-0-0)
Examine the four major components of energy management: supply,
demand, regulation and environment; and the concepts and principles
behind successful energy management. Topics include energy auditing
and economic analysis; management control and maintenance systems;
sustainability and high performance green buildings; alternative energy
systems; boilers and fired systems; cogeneration and HVAC systems;
ground source heat pumps; lighting and electrical management; natural
gas purchasing; thermal storage; codes and standards; indoor air quality;
utility deregulation and energy systems outsourcing; energy security risk
analysis methods; and financing energy management projects.

EM 575 Project Scheduling and Planning
Credits: 3(3-0-0)
This course provides advanced techniques in plan and schedule
development and implementation for project management during the
programming or construction phase of a project. Also the course covers
monitoring, updating, and controlling the project schedule; earned value;
analyzing change orders and delays; network models; resource levelling
and equipment movement, and dispute-avoidance and considerations.
Also the course covers a construction project schedule using computer
software applications.

EM 576 Operations Management
Credits: 3(3-0-0)
In this course, you will learn about the role of operations and how
they are connected to other business functions in manufacturing- and
service-focused organizations. You will learn and practice the use of
decision-making frameworks and techniques applicable at all levels, from
management-level strategic decisions such as connecting process to the
needs of various customer segments, to front-line tactical decisions such as
choosing between ordering larger quantities vs. ordering more frequently.

EM 578 Data Mining for Engineering Applications
Credits: 3(3-0-0)
This course introduces data mining concepts and statistics/machine learning
techniques for analyzing and discovering knowledge from large data sets

64 GRADUATE STUDIES BULLETIN