GenAI and LLMs on AWS
About this course
This course will teach you how to deploy and manage large language models (LLMs) in production using AWS services like Amazon Bedrock. By the end of the course, you will know how to: Choose the right LLM architecture and model for your application using services. Optimize cost, performance and scalability of LLMs on AWS using auto-scaling groups, spot instances and container orchestration Monitor and log metrics from your LLM to detect issues and continuously improve quality Build reliable and secure pipelines to train, deploy and update models using AWS services Comply with regulations when deploying LLMs in production through techniques like differential privacy and controlled rollouts This course is unique in its focus on real-world operationalization of large language models using AWS. You will work through hands-on labs to put concepts into practice as you learn. Whether you are a machine learning engineer, data scientist or technical leader, you will gain practical skills to run LLMs in production.
83/100
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- What the provider tells you
- 32/45
- Who stands behind it
- 35/35
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- 16/20
Scores how much the provider publishes and who stands behind it — not how well it is taught.
What you'll learn
- Choose the right LLM architecture and model for specific applications
- Optimize LLM cost and performance with AWS services
- Monitor and log LLM metrics for quality enhancement
- Build reliable and secure pipelines for model lifecycle management
- Implement compliance techniques when deploying LLMs in production
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