Found 3 relevant results in 1.48s where lecturer="Mark Fuge"
Students develop and build a product from A-Z! They work in teams and independently, learn to structure problems, to identify solutions, system analysis and simulations, as well as presentation and documentation techniques. They build the product with access to a machine shop and state of the art engineering tools (Matlab, Simulink, etc).
This course teaches designing complex multiphysics systems using generative AI tools with hands-on, project-based learning. It covers single physics design, multiphysics integration, and testing. Assessments include reports, team projects, and a final showcase. Students experience advanced software, navigating design trade-offs, and optimizing performance under constraints.
Learn Machine Learning techniques to solve mechanical engineering problems covering: 1) Review of key concepts like cross-validation, linear models, neural networks, and probabilistic inference; 2) Advanced neural methods including transformers, GANs, VAEs, and reinforcement learning; 3) Kernel methods and probabilistic models. Includes hands-on projects and a final exam.