Artificial Intelligence (AI) is a rapidly evolving field changing how we approach engineering across various industries, including automotive, aerospace, manufacturing, healthcare, and many more. With AI, organizations can streamline complex systems, automate decision-making, and improve efficiency. However, for engineers, successfully leveraging AI goes beyond the training stage of the model, especially in complex systems where numerous actions are automated, and multiple components must fit seamlessly together. To incorporate AI efficiently into these systems, engineers must follow a robust work methodology that involves careful data preparation, model creation, system design, and deployment.
In this talk, learn about the key challenges and fundamental principles of AI for engineers. Discover AI tools (for Machine Learning, Deep Learning, and Reinforcement Learning) available in MATLAB® and Simulink® that enable you to quickly explore your data, evaluate models, compare results, and apply the best techniques. Learn also how to refine, reduce the size of your AI models and deploy them in various production-ready formats. By doing so, you will be able to verify the behavior of your AI models under different conditions and make the best design choice for your requirements.