Új Agentic AI Foundations

In this course, you'll explore the core principles and strategies for designing Agentic AI systems using AWS services. You'll learn how Agentic AI differs from traditional conversational systems, and how to use tools like Amazon Q, Kiro, Amazon Bedrock Agents, and Amazon Bedrock AgentCore to build autonomous, goal-driven solutions that solve real-world problems.

• Software developers
• Development teams
• IT professionals who want to learn more about Agentic AI and its applications in software development and IT

• Summarize the evolution of Agentic AI and define what makes something "agentic".
• Identify the core components of agentic systems: goals, memory, tools, and environment.
• Distinguish between workflow, autonomous, and hybrid agents.
• Compare AWS service options for Agentic AI, including specialized, managed, and DIY approaches.
• Describe the capabilities and use cases of Amazon Q Developer, Amazon Q Business, and Kiro.
• Explain the core functionalities of Amazon AgentCore and Amazon Bedrock Agents.
• Identify basic implementation patterns for Agentic AI.
• Describe observability and interoperability patterns for production agentic AI systems.

Day 1

• Module 1: From LLMs to Agents
  • Understanding Large Language Models (LLMs)
  • Innovations powering agents
  • Evolution timeline from LLMs to Agents
• Module 2: Exploring Agentic AI
  • Understanding Agentic AI
  • Types of AI agents
  • Agentic AI applications
• Module 3: Understanding Agentic AI Workflows
  • Workflow patterns
  • Amazon Bedrock Flows overview
  • Demo: Amazon Bedrock Flows
• Module 4: Introducing Autonomous Agents
  • How Autonomous Agents work
  • ReAct
  • ReWoo
  • Multi-agent collaboration
  • AWS Agentic AI solutions
• Module 5: Amazon Q and Agentic Development Tools
  • Amazon Q Developer
  • Amazon Q Business
  • Amazon Q in AWS Services
  • Kiro: AI-powered IDE with spec-driven development
  • Demo: Amazon Q
• Module 6: Agentic AI with Amazon Bedrock
  • Hands-on lab: Explore Amazon Bedrock Agents integrated with Amazon Bedrock Knowledge Bases and Amazon Bedrock Guardrails
  • Amazon Bedrock Agents
  • Amazon Bedrock AgentCore
  • Demo: Amazon Bedrock Agents
• Module 7: Building DIY Solutions
  • DIY solutions
  • Observability and Monitoring
  • Agent Interoperability
• Module 8: Course Wrap-up
  • Next steps and additional resources
  • Course summary

We recommend that attendees of this course have:

• Generative AI Essentials or equivalent work experience
• Basic AWS knowledge and software development experience