Agent Orchestration

What you'll learn
- Understand retrieval-augmented generation (RAG) concepts.
- Create and query Amazon Bedrock knowledge bases.
- Design workflows using prompts and flows.
- Configure Bedrock agents with custom tasks.

Requirements
- AWS experience

Description
e.g. This is primarily aimed at first- and second-year undergraduates interested in engineering or science, along with high school students and professionals with an interest in programming.Step up your generative AI skills with this course focused on building generative AI applications using Amazon Bedrock. Building on the fundamentals, you'll dive deep into advanced features and services that enable more complex solutions.

The course begins with a deep dive of Amazon Bedrock Knowledge Bases, teaching you how to enhance AI responses using Retrieval-Augmented Generation (RAG). You'll learn to create and manage knowledge bases, integrating them into your applications to provide context-aware, domain-specific AI interactions.

Next, you'll learn Amazon Bedrock Prompt Management and Flows, enabling you to design intricate workflows that chain multiple AI operations. This section empowers you to create more sophisticated generative AI behaviors in your applications.The latter part of the course focuses on generative AI-driven agents for task automation. You'll learn to configure and deploy Bedrock Agents, integrating them with various AWS services to create smart, autonomous systems. You'll also explore the Converse API, enabling more natural, context-aware conversations in your AI applications.

Throughout the course, hands-on labs and real-world scenarios will help you apply these concepts. By the course's end, you'll be designing and implementing advanced generative AI applications with Amazon Bedrock.

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.

Who this course is for:
- Participants should be comfortable with basic AI implementation in AWS and have hands-on experience with foundation models.
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