
Explore Amazon Bedrock's serverless API access to foundation models for generative AI in applications, including LLMs, prompts, and inference for chatbots and code generation.
Use Bedrock guardrails to filter harmful inputs and model responses. Configure guardrails for prompts, denied topics, and personally identifying information, with options to block or mask.
Craft prompts iteratively to guide models, detailing the task, context, and model instructions, and control style, formatting, and outputs with examples, system prompts, and Bedrock-based retrieval-augmented generation (rag).
Use the Amazon Q Developer agent in Visual Studio Code to generate CloudFormation templates and deployment scripts for deploying an EC2 in a private VPC.
Get introduced to generative AI with this foundational course designed for developers looking to use AWS' generative AI services. This course serves as your gateway to understanding and implementing generative AI solutions using Amazon Bedrock.
You'll begin by exploring the fundamentals of generative AI, understanding its place within the broader AI landscape, and learning key concepts such as foundation models, prompts, and inference. Through hands-on labs and demos, you'll gain practical experience invoking foundation models and interpreting their responses.
The course then dives into Amazon Bedrock Runtime APIs, covering operations like InvokeModel and asynchronous invocations. You'll learn to implement streaming responses, manage provisioned throughput, and apply guardrails to ensure responsible AI use.
A significant portion of the course focuses on working effectively with foundation models. You'll explore model selection criteria, learn the art of prompt engineering, and understand how to optimize your interactions with generative AI tools.
By the end of this course, you'll have an understanding of generative AI concepts and hands-on experience with Amazon Bedrock. You'll be ready to start integrating AI capabilities into your applications, setting the stage for more generative AI development in subsequent courses.
Please note: The hands-on exercises are optional and require access to your own AWS account. Completing these activities may result in minimal usage charges.