11 courses with the subject MGR, each shown exactly as we captured it from the college's catalog, with every element we hold. Where the wording looks broken, that is our reading of the catalog, not the college's text.
MGR 215Strength of Materials Lec. 3/Credit 3
Concepts of stress and strain; mechanical properties of materials, force, deformation and stress analysis of structural members; stress and strain transformations; principal stresses; failure theories; and concept of buckling.
An introductory course in fluid dynamics stressing both the integral and differential forms of the conservation laws of fluid flow. Engineering applica- tions are made to hydrostatics and to ideal and real fluid flows. Laboratory experiments and problems sessions complement the lectures.
Engineering Lec. 3/Credit 3. Numerical methods applied to engineering analysis with a design/lab studio. Numerical techniques including root finding, linear algebra, ordinary differen- tial equations, curve/parameter fitting, discrete Fourier transforms, optimiza- tion. Method of lines to generate finite element methods for partial differential equations. Structured programming and iterative problem-solving using a high- level environment such as MATLAB. Prerequisites: MAT 152, MAT 260, EGR 102. 332 Course Descriptions – Main Campus
This course provides an in-depth study of Computer Aided Design (CAD) and Digital Manufacturing. Topics include design process, mathematical and graphical demonstration of wireframe/surface/solid models, transformation and manipulation of objects, CAD file formats and data exchange, process planning, cutting tools types and materials, milling process, fundamental of CNC machines, numerical control programming for milling processes, CNC code generation and simulation by CAD/CAM software, and an overview of other digital manufacturing processes such as additive manufacturing, laser cutting and welding, and waterjet cutting. Prerequisites: EGR 102 or ELN 101, MAT 305, EGR 303.
for Engineering Design Lec. 3/Credit 3. Learn how to apply techniques from Artificial Intelligence and Machine Learning to solve engineering problems and design new products or systems. Design and build a personal or research project that demonstrates how computational learning algorithms can solve difficult tasks in areas you are interested in. Master how to interpret and transfer state-of-the-art techniques from computer science to practical engineering situations and make smart implementation decisions. Prerequisites: MAT 305, EGR 102 or ELN 101.
Part two of the two-semester capstone design course sequence. Students continue with concept selection, detail design, prototyping and evaluation of their capstone design projects. Formal presentations and reports are prepared to review and document the designs. Prerequisites: MGR 443.
This course covers basic concepts and principles of instrumentation and measurement systems, analog and digital devices, basic electronics, sensors and transducers, introduction to the internet of things (IoT) and big data, cybersecurity of IoT devices, wireless digital network and communication, probability and statistics to characterize measurement uncertainty, data acquisition and analysis using software packages, and measurements of physical properties such as temperature, pressure, and strain. Prerequisites: EGR 102 or ELN 101, MAT 305, EGR 303, EGR 226.