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Courses - Spring 2024
ENPM
Engineering, Professional Masters Department Site
Open Seats as of
06/15/2024 at 10:30 AM
ENPM808
(Perm Req)
Advanced Topics in Engineering
Credits: 1 - 3
Grad Meth: Reg, Aud
Independent study project on a topic relevant to their academic program, supervised by a University of Maryland, College Park faculty member. Requires application and approval.
ENPM808E
(Perm Req)
Advanced Topics in Engineering; Underwater Robot Perception
Credits: 3
Grad Meth: Reg, Aud
Prerequisite: ENPM673.

This course addresses the breadth of managing software engineering projects and will help in transforming inspiring software engineers to software project leaders. The course will impart advanced principles, methods and tools for management of software projects in a realistic software engineering context.
ENPM808K
Advanced Topics in Engineering; Advanced Systems Architecting
Credits: 3
Grad Meth: Reg, Aud
This course continues the MSSE systems engineering course progression with a comprehensive focus on system architecture that drives systems and enterprise engineering decision making at many levels. The course introduces students to models for enterprise, business, systems-level, service/component level, discipline-specific architectures. Students will use integrated architecting tools to solve problems of interest to them and that stress the capture, analysis, reconciliation, leverage, and execution of architecture at many levels and the exercise of ANSI/ISO/IEC/IEEE standards for architectural description.
ENPM808V
Advanced Topics in Engineering; Quality Management Systems and Lean Six Sigma
Credits: 3
Grad Meth: Reg, Aud
This course covers Quality Engineering approaches for creating optimal and robust manufacturing and engineering systems. It provides an overview of the important tools for quality analysis and quality management of engineering systems. These tools are commonly used in companies and organizations.
ENPM808Z
Advanced Topics in Engineering; Cognitive Robotics
Credits: 3
Grad Meth: Reg, Aud
Cognitive Robotics explores the application of human cognitive intelligence to the design and development of intelligent robots. The course delves into the fundamental principles of human cognitive intelligence and its integration with robotics and machine learning. Students will learn to develop cognitive robot learning architectures and implement them using simulators like Pybullet, NVIDA Issac-Gym, and Meta Habitat 2.0. Through engaging class projects, students will apply their newly acquired knowledge to solve novel, challenging and practically useful problems, enabling them to make meaningful contributions to the field. This uniqueopportunity to bridge the gap between cognitive science and robot learning that empowers students to develop smarter and more capable robotic systems.