Mastering Model Evaluation in Amazon Bedrock: From Basics to Best Practices

Master Amazon Bedrock model evaluation to choose accurate and reliable AI models

Foundation models have revolutionised AI applications but evaluating them effectively presents unique challenges. While these powerful models can handle diverse tasks, they may produce inconsistent results or exhibit issues like hallucination and toxicity. Even when multiple models perform similarly, determining the optimal choice for specific use cases requires systematic evaluation across multiple dimensions including accuracy, robustness, quality, and responsibility.

This course will explore the fundamentals of model evaluation and why it matters, Amazon Bedrock’s built-in evaluation tools and capabilities, key considerations for evaluating models in different scenarios and best practices for systematic model assessment.

Through hands-on examples and practical guidance, you’ll learn how to leverage Bedrock’s evaluation framework and the right foundation models for your specific needs.

Please note that to access the course content for this AWS course, you will go via an LTI link(s) to the AWS platform; you can then return to the FutureLearn course in order to receive your certificate.

This course is ideal for Architects, Cloud Operators, Data Engineers, Data Scientists, Developers. DevOps Engineers, Infraestructure Engineers, Trainers.

This course is ideal for Architects, Cloud Operators, Data Engineers, Data Scientists, Developers. DevOps Engineers, Infraestructure Engineers, Trainers.

• Explain the fundamentals of model evaluation in Amazon Bedrock
• Practice hands-on experience running evaluations
• Perform practical skills for selecting and implementing models based on evaluation results
• Apply best practices for model evaluation and selection