Getting started with AWS Generative AI for Developers

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.

• Build proficiency with Amazon Bedrock, learning how to access and interact with various foundation models through the Bedrock Runtime APIs for tasks such as text generation, language understanding, and summarization
• Develop practical skills in prompt engineering, exploring techniques to write effective prompts that yield desired outputs from AI models, and learn to optimize parameters like temperature and top-k sampling
• Implement responsible AI practices using Amazon Bedrock Guardrails, ensuring your AI applications adhere to ethical guidelines and maintain content safety
• Gain hands-on experience integrating generative AI capabilities into applications, learning to handle streaming responses, manage asynchronous invocations, and implement batch inference for scalable AI solutions