Agentic AI on AWS - Bedrock Agents, CrewAI, Kiro & MCP

Build AI Agents with Amazon Bedrock, CrewAI, Kiro and AWS MCP — A Complete Hands-On Course :

• Welcome to the most comprehensive guide on AWS Amazon Bedrock Multi-Agent Framework, CrewAI & MCP from a practising AWS Solution Architect and best-selling Udemy Instructor.

• This course will start from absolute basics on what is Agentic AI and core characteristics of AI Agents such as Planning, Memory, Tool Calling and Multi-Agent Communication.

• Then we will deep dive into Amazon Bedrock Agents and Multi-Agent framework.

• Next, we will build Use Case 1 - Hotel Booking Agent : A Hotel Booking Agent using Amazon Bedrock Agents, AWS Lambda and Amazon Bedrock Knowledge Bases (Using the Amzon Nova Model)

• Next, we will build Use Case 2 -  Enterprise Travel Agent (Multi-Agent) : A Enterprise Travel Agent using Amazon Bedrock Multi-Agent Orchestration Framework.

• Use Case 3 - Build Vacation Planner AI App using CrewAI framework and Bedrock

• Use Case 4 - Build FleetMate Application using AWS KIRO - Agentic AI powered Integrated Development Environment (IDE)

• Use Case 5 - Build an Infra Coding Agent using AWS MCP CloudFormation Server and Amazon Q CLI.

• Included a refresher lectures on GenAI, Bedrock and AWS Lambda which will be used in the course to build 2 use cases.

• I will continue to update this course as the Agentic AI evolves to give you a detailed understanding and learning required in enterprise context, so that you are ready to switch careers.

  
  

  Detailed Course Overview

• Section 1 - Course Introduction

• Section 2 - Evolution of AI Agents : Learn fundamentals about AI Agents such as Planning, Tools, Memory, Multi-Agent Framework

• Section 3 - AWS AI Agentic Framework Deep Dive  - Amazon Bedrock Multi-Agent Frameworks : Learn about Amazon Bedrock Agents, Multi-Agent Orchestration Framework

• Section 4 - Use Case 1 - Hotel Booking Agent : Build a Hotel Booking Agent using Amazon Bedrock Agents, AWS Lambda and Amazon Bedrock Knowledge Bases

• Section 5 - Use Case 2 -  Enterprise Travel Agent (Multi-Agent) : Build a Enterprise Travel Agent using Amazon Bedrock Multi-Agent Orchestration Framework.

• Section 6 - Use Case 3 - Vacation PlannerAI app  using CrewAI framework and Bedrock

• Section 7 - Use Case 4 - Build an Infra Coding Agent using AWS MCP CloudFormation Server and Amazon Q CLI

• Section 8 - Refresher - Generative AI, Amazon Bedrock and Knowledge Bases

• Section 9 - Refresher - Basic Python, AWS Lambda and Boto3

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)