Amazon Bedrock AgentCore: Build & Deploy any AI Agent on AWS

Welcome to “Amazon Bedrock AgentCore: Build AI Agents on AWS [HANDS-ON]” — the most practical, hands-on course to master Agentic AI development and deployment on AWS in just 2 weeks.

This course is designed for developers, data scientists, and AI enthusiasts who want to learn how to build, deploy, and monitor fully functional Serverless AI Agents (any open-source framework) using Amazon Bedrock AgentCore. You’ll work through real-world, hands-on projects that combine Bedrock primitives, runtime orchestration, memory, observability, and deployment with AWS Lambda and API Gateway.

Through step-by-step labs, you’ll:

• Build a Personal Vacation Planner AI Agent from scratch (CrewAI Framework)

• Deploy your agent using Bedrock AgentCore Runtime, AWS Lambda, API Gateway, and optionally Streamlit for interactive apps.

• Enable full Observability with OpenTelemetry and  CloudWatch to monitor agent behavior and performance.

• Implement memory for context-aware, multi-turn conversations.

• Learn about AgentCore  Identity and Gateway for production readiness

By the end of this course, you’ll have a deep, practical understanding of how to create, operate, and scale Agentic AI systems on Amazon Bedrock AgentCore.

• Section 1 - Course Overview – Introduction and learning outcomes

• Section 2 - Amazon Bedrock AgentCore Building Blocks - Primitives and the Problem it is trying to solve

• Section 3 - Build Agentic AI App from Scratch [Hands-On] – Personal Vacation Planner [on CrewAI]

• Section 4 -  Bedrock AgentCore Runtime [Hands-On] – Deploy with AgentCore Runtime + Lambda + API Gateway

• Section 5 - Bedrock AgentCore Observability [Hands-On] – Monitor with OpenTelemetry & CloudWatch

• Section 6 - Amazon Bedrock AgentCore Identity & Gateway [Hands-On]– Setup AgentCore Gateway & invoke Agent Tools

• Section 7 - Amazon Bedrock AgentCore Memory [Hands-On] – Add context and session memory

• Section 8 - Refresher: Agentic AI, CrewAI, and MCP

  
  

IMPORTANT << Learning Path:  GenAI Developer / Architect on AWS  >>

Many learners ask how to switch their career to an AWS Generative AI Developer or Architect and which sequence of my Udemy courses they should follow. Here is some guidance based on my experience working in the IT industry.

My GenAI/Agentic AI courses are divided into two tracks

• Hands-On learning to build real world skills required in the IT industry (Most important)

• Certification preparation to help you pass the certification exam (Good to have)

<< Hands-On Courses >>

1. Hands-On Course 1  (Beginner) - Amazon Bedrock, Amazon Q & AWS Generative AI [Hands-On]

Start here if you’re new to GenAI & Amazon Bedrock.

2. Hands-On Course 2 (Intermediate) - Build Production Ready AI Agents on AWS – Bedrock, CrewAI & MCP

Take this after Course 1 - Focused on Agentic AI but will be easier to understand if you have taken Course 1

3. Hands-On Course 3 (Advanced) - Amazon Bedrock AgentCore : Deploy AI Agents on AWS

This is the advanced course and focused on how to deploy, scale, and operate AI agents in Production.

Recommend to take after Course 1 & Course 2.

<< AWS GenAI Certification Path >>

1. Certification Course 1 : AWS Certified AI Practitioner (AIF-C01) – Beginner to Advanced

· Take after Step 1, or

· In parallel with Step 2

Outcome
You pass AWS Certified AI Practitioner (AIF-C01) and understand GenAI concepts AWS expects.

2. Certification Course 2 : AWS Certified Generative AI Developer Professional (Coming Soon)