Amazon Bedrock AgentCore: Build & Deploy AI Agents (Python)

About this course

What you'll learn:

• Set up a professional Python development environment for Amazon Bedrock AgentCore with PyCharm and Python virtual environments
• Run AI agents locally while connecting to large language models (LLMs) in the cloud
• Deploy single agents and multi-agent systems to AgentCore on AWSCompare agent architectures across different frameworks and deployment patterns
• Use the core AgentCore APIs hands-on through guided Python demos
• Use the AgentCore runtime for observability, agent evaluation, and reusable prompts
• Design multi-agent systems in which agents communicate and coordinate with each other
• Work through Jupyter notebooks cell by cell, running code and interpreting the output
• Package and deploy agents with Docker and AWS CloudFormationNavigate the AWS console to monitor deployed agents
• Analyze traces and spans to find performance bottlenecks and optimize agent-based systems
• Use Claude Code to troubleshoot and fix issues in your Python notebooks
• Reinforce your AgentCore knowledge with Q&A generated by custom Claude Code skills

Who this is for:

Python developers who want to build, deploy, and scale AI agents on AWSSoftware engineers moving from experimental agent prototypes to production-ready systemsAI/ML engineers who want hands-on experience with Amazon Bedrock AgentCore and its core APIsCloud and DevOps engineers responsible for deploying and monitoring agent-based applications with Docker and CloudFormationSolutions architects comparing agent architectures, frameworks, and deployment options on AWSDevelopers building multi-agent systems that need observability, evaluation, and coordination between agents

Read the full description on Udemy on Udemy (opens in a new tab)

Prices, discounts and availability are set by Udemy. We may earn a commission when you purchase through links on this site.