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  • 3.00 Credits

    An introduction to modeling mechanical, fluid and electrical systems using differential equations. Methods include transfer-function and state-space methods, and time-domain and frequency-domain analysis of modeled systems. (Fall) [Graded (Standard Letter)]Prerequisite(s): ENGR 2170 and MATH 2250 and ME 2030 - Prerequisite Min. Grade: D-Registration Restriction(s): None Prerequisite:    ENGR 2170 A MATH 2250 ( A ME 2030 O ENGR 2030 )
  • 3.00 Credits

    Introduction to the principles of engineering design and product development, including planning, concept generation, concept selection, system-level design, detail design, prototyping, and product testing. (Spring) [Graded (Standard Letter)]Prerequisite(s): (ENGR 1030?and ME 2030?and ME 2130)?or?(ENGR 1050 and EE 2250 and EE 2290) - Prerequisite Min. Grade: D- Prerequisite:    ( ENGR 1030 A ME 2030 A ME 2130 ) ( O ENGR 1050 A EE 2250 A EE 2290 )
  • 3.00 Credits

    Internal atomic, molecular, crystalline, organic, amorphous structures, and dependence of physical properties upon these structures. Properties, requirements, and uses of modem engineering materials. (Fall) [Graded (Standard Letter)]Prerequisite(s): CHEM 1210 and CHEM 1215 and MATH 1210 - Prerequisite Min. Grade: D-Registration Restriction(s): None Prerequisite:    CHEM 1210 A CHEM 1215 A MATH 1210
  • 3.00 Credits

    Introduction to the principles of design and analysis of machines and machine components including synthesis of mechanisms, mechanical linkages, cams, and gears. Design for functionality, motion, force, strength, and reliability. (Fall) [Graded (Standard Letter)]Prerequisite(s): ENGR 1030 and ENGR 2140 and ENGR 2145 and ME 2030 and ME 3100 - Prerequisite Min. Grade: D-Prerequisite Can Be Concurrent? Yes (ME 3100)Registration Restriction(s): None Prerequisite:    ENGR 1030 A ENGR 2140 A ENGR 2145 ( A ME 2030 O ENGR 2030 ) ( A ME 3100 O ENGR 3010 )
  • 3.00 Credits

    Fundamental principles of thermodynamics. Thermodynamic properties of fluids. First law and second law of thermodynamics and their application to closed systems. Energy relationships involving heat, work, and various other forms of energy. Introduction to thermodynamic cycles. (Spring) [Graded (Standard Letter)]Prerequisite(s): PHYS 2220 - Prerequisite Min. Grade: D-Registration Restriction(s): None Prerequisite:    PHYS 2220
  • 3.00 Credits

    Fundamental principles of fluid mechanics. Properties of fluids. Fluid statics. Control volume and transport theorem. Continuity and motion equations. Inviscid and viscous flows. Laminar and turbulent flows. Incompressible and compressible flows. Internal, external, and free surface flows. Bernoulli?s equation. (Spring) [Graded (Standard Letter)]Co-requisite(s): ME 3305 Prerequisite(s): MATH 1220 and PHYS 2210 - Prerequisite Min. Grade: D- Prerequisite:    MATH 1220 A PHYS 2210 Corequisite:    ME 3305
  • 1.00 Credits

    This lab accompanies ME 3300. Emphasis is on analysis and reporting of results. (Spring) [Graded (Standard Letter)]Co-requisite(s): ME 3300 Corequisite:    ME 3300
  • 3.00 Credits

    An interdisciplinary systems approach to dynamics and control involving the integration of mechanical, electrical, and electronics engineering using microprocessor control. Involves computer modeling and designing of mechanical, electrical, fluid, and thermal systems. (Spring) [Graded (Standard Letter)]Co-requisite(s): ME 3325 Prerequisite(s): ME 2030 - Prerequisite Min. Grade: D-Registration Restriction(s): None Prerequisite:    ME 2030 O ENGR 2030 Corequisite:    ME 3325
  • 1.00 Credits

    This lab accompanies ME 3320. Lab activities include the analysis, computer simulation, design, implementation, and measurement of electromechanical systems. (Spring) [Graded (Standard Letter)]Co-requisite(s): ME 3320 Registration Restriction(s): None Corequisite:    ME 3320
  • 3.00 Credits

    In this course, students will explore?the world of Machine Learning (ML), a fundamental branch of Artificial Intelligence (AI), and explore its real-world applications.?This undergraduate course welcomes students from diverse backgrounds, including, but not limited to, engineering, computer science, and mathematics,?providing hands-on experience and practical skills. Students will be introduced to ML's core principles and terminology?and learn to apply ML techniques to engineering and technology challenges. Additionally, students will have the opportunity to collaborate on projects that make a meaningful difference. This course will help students?unlock the potential of Machine Learning and become a leader in this dynamic field. (Fall) [Graded (Standard Letter)]Prerequisite(s): (MATH 1210 or MATH 1040) and (ENGR 2170 or CS 1400) - Prerequisite Min Grade: D- Prerequisite:    ( MATH 1210 O MATH 1040 ) ( A ENGR 2170 O CS 1400 )