Join us for a new webinar on Artificial Intelligence (AI) applied to battery testing. This session will showcase the potential for test engineers by demonstrating how to effectively explore and how to quickly and easily build an AI-based solution with real battery test data to increase test plan efficiency. Through a live Monolith software demonstration, participants will gain practical insights into the following key aspects:
- Loading and exploring battery data: Learn the essential steps to efficiently load and explore battery data, laying the foundation for insightful analysis.
- Model training from test data: We'll give you step-by-step instructions on training AI models using your test data, empowering you to harness the predictive capabilities of AI.
- Choosing the right AI algorithms: Explore diverse methods to evaluate AI models, enabling you to identify the best-fit models for your unique testing requirements. Understand how to determine the most suitable AI algorithms for your specific battery data, ensuring optimal model performance.
- Predictive battery performance: Discover how AI models can be used to make accurate predictions of battery performance, enhancing the efficiency of testing processes.
- Model sharing for collaborative use: Learn strategies to share your AI models for broader collaboration, fostering a community-driven approach to battery testing innovation.
- Optimising test plans with AI: Uncover the impact of AI models on optimising test plans, maximising efficiency, and ensuring comprehensive testing coverage.
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Who should attend:
- Leaders in R&D and engineering who work with EV batteries for product validation and certification
- Business leaders interested in AI trends in the EV market
- Test engineers looking to use AI for predicting critical and redundant tests