SE - Systems Engineering

This course will provide students with the knowledge and skills to apply a top down approach to the engineering of complex systems. Topics covered in this course include all activities involved in engineering complex systems starting from the inception of the system to its implementation. Specifically, the management, maintenance and quality assurance of the engineering process are covered. Students will learn how to engineer complex systems using the principles of systems engineering. Upon successful completion of this course, students will be able to understand systems requirements and perform requirements analysis using appropriate tools and techniques.

This course will provide students with knowledge and skills of integrated approaches to system analysis, design and implementation. Topics including modern concepts & practices to modeling, requirements definition, specification development, system development, test and quality evaluation. Students will learn detail analysis, design and implementation techniques used in the development of complex systems.

This course will provide students with knowledge and skills on the application of systems engineering principles to the testing and evaluation of complex systems. Topics include adoption of proper testing requirements and parameters, validation and verification, operational testing and evaluation. Student will be able to apply systems engineering concepts to develop corrective actions based on data interpretation and analysis.

This course will provide students with knowledge and skills of fundamental principles of robotics. Topics include the development of computer programs for analyzing the kinetics, dynamics and control of robotic systems. Students will be introduced to the fundamentals of robotics system development.

This course will provide students with knowledge and skills of machine learning based on unified, probabilistic approach. Topics include study of probability, optimization, conditional random fields, regularization and deep learning. Students will learn pattern recognition and machine learning principles relating to robotics systems.

This course will provide students with knowledge and skills of best practices and future development in the field of robotics. Topics include use of robotics in manufacturing, assistive robotics, bioinformatics, human-computer interaction and intelligent mechatronics. Students will learn automation and control of robotics systems.

This course is the first phase of the culminating experience in systems engineering through a practical project spanning the conceptual design, planning, and specification to the implementation, testing, and evaluation of the system. Faculty approval is required for the formally presented proposed project.

This course is the second phase of the culminating experience in systems engineering through a practical project spanning the conceptual design, planning, and specification to the implementation, testing and evaluation of the system. Students will apply learned principles and tools for systems engineering to the design and implementation of a faculty approved project.