Effectively manage AI costs with Amazon Bedrock. This course will teach you how to analyze cost drivers, optimize workloads for cost-effectiveness, and implement strategies to reduce costs while maintaining high performance in AI operations.
In today's technology landscape, AI is here to stay, and organizations that fail to embrace it risk losing competitiveness. Amazon Bedrock provides powerful tools to help achieve these goals. But the real challenge is riding the wave without breaking the budget along the way. In this course, Managing Costs for Amazon Bedrock, you'll learn how to identify cost components and optimize workloads by implementing cost effective strategies without sacrificing performance. First, you'll explore Amazon Bedrock's key cost drivers, breaking down how token-based charges, model invocations, and request frequency impact costs. Next, you'll discover how different workload configurations impact costs and identify key areas for optimization, such as data transfer, API calls, and AWS integrations. Finally, you'll learn how to implement cost-saving strategies, including prompt engineering, response caching, and efficient resource allocation. When you're finished with this course, you'll have the skills and knowledge to manage costs for Amazon Bedrock to ensure high-performance AI solutions while maintaining cost efficiency.
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