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Mechanics of Materials I: Fundamentals of Stress & Strain and Axial Loading
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Transform from novice to proficient computer vision practitioner through hands-on projects. Gain skills in image processing, motion detection, deep learning, and advanced techniques using MATLAB's user-friendly interface.
Comprehensive overview of systems engineering principles for complex project development, covering architecture, requirements, optimization, and verification techniques.
Learn essential computer vision techniques using MATLAB to detect objects, classify images, track motion, and more. Gain practical skills for engineering and scientific applications in autonomous systems and medical imaging.
Gain insights into modeling and simulating electrified systems using Simulink and Simscape, covering power converters, electric motors, and battery systems to build job-ready skills in model-based design.
Hands-on specialization in deep learning for computer vision, covering image classification, object detection, and advanced techniques. Gain practical skills using MATLAB for real-world applications.
Explore object tracking and motion detection techniques using MATLAB. Learn to apply deep neural networks, optical flow, and advanced algorithms for real-world computer vision applications.
Learn to process and analyze medical images using MATLAB, covering import, visualization, alignment, and segmentation techniques for 2D and 3D data to advance patient care and medical research.
Apply data science skills to real-world problems using MATLAB. Explore, process, analyze, and model data through a hands-on project. Develop expertise in feature engineering, machine learning, and result communication.
Learn to classify images and detect objects using machine learning in MATLAB. Apply the full workflow from data preparation to result evaluation, focusing on street sign classification and material defect detection.
Learn to train and evaluate deep learning models for image classification, from medical analysis to traffic sign recognition, using hands-on projects and MATLAB software.
Discover the fundamentals of electrification engineering, from converting traditional systems to grid-powered models, through modeling and simulation techniques using MATLAB, Simulink, and Simscape with real-world applications.
Train anomaly detectors, generate synthetic images, use AI-assisted labeling, and create custom models for visual inspection and medical imaging applications. Overcome data challenges and explore model deployment options.
Gain foundational knowledge in data science, machine learning, data processing, and cloud computing. Learn practical skills using low-code solutions and integrate multiple tools for effective problem-solving.
Master essential MATLAB skills for data analysis, app development, and AI-powered productivity to advance your engineering and scientific career with hands-on projects.
Discover how to leverage MATLAB Copilot's AI-powered features to enhance coding efficiency, generate explanations, refine drafts, and integrate generative AI into engineering workflows.
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