Build Production Ready AI Agents on AWS-Bedrock,CrewAI & MCP

Build Production-Ready AI Agents on AWS – Bedrock, CrewAI & MCP is a hands-on course focused on designing, building, and deploying real-world AI agents on AWS. Unlike beginner-level GenAI courses, this program emphasizes production-ready agentic systems using Amazon Bedrock, CrewAI, and the Model Context Protocol (MCP).

The course walks learners through four practical AI agent use cases, covering core agent concepts such as planning, tool usage, memory, and multi-agent orchestration. It is ideal for professionals who want to move from experimentation to enterprise-grade AI agent deployment on AWS.

Course Snapshot

• Rating: 4.7 / 5

• Students Enrolled: 6,551+

• Skill Level: Intermediate

• Language: English (Auto captions), German (Auto captions)

• Content Length: ~9.5 hours

• Format: On-demand video + articles + downloadable resources

• Access: Full lifetime access

• Refund Policy: 30-day money-back guarantee

What This Course Focuses On

This course is centered around building production-ready AI agents, not just prototypes. Learners gain practical experience with:

• Agentic AI fundamentals (planning, tools, memory, multi-agent systems)

• Amazon Bedrock Agents and orchestration

• CrewAI framework for collaborative agents

• Model Context Protocol (MCP) for tool interoperability

• AWS-native deployment using Lambda, Knowledge Bases, and CloudFormation

The emphasis is on real AWS architectures used in enterprise environments.

AI Agents: Building Teams of LLM Agents that Work For You

Start Course

Tools & Technologies Covered

The course introduces modern agentic AI tooling within the AWS ecosystem, including:

• AI & Agent Frameworks

  • Amazon Bedrock Agents

  • Bedrock Multi-Agent Orchestration

  • CrewAI

• AWS Services

  • AWS Lambda

  • Amazon Bedrock Knowledge Bases

  • AWS CloudFormation

  • Amazon Q CLI

  • Boto3

• Protocols & Concepts

  • Model Context Protocol (MCP)

  • Tool calling and agent memory

  • Multi-agent collaboration patterns

Hands-On Use Cases You’ll Build

Use Case 1: Hotel Booking Agent

• Build a hotel booking AI agent using:

  • Amazon Bedrock Agents

  • AWS Lambda

  • Amazon Bedrock Knowledge Bases

Use Case 2: Enterprise Travel Agent (Multi-Agent)

• Create a multi-agent enterprise travel system

• Use Amazon Bedrock’s Multi-Agent Orchestration Framework

• Coordinate multiple agents for complex workflows

Use Case 3: Vacation Planner AI App

• Build a vacation planning application using:

  • CrewAI framework

  • Amazon Bedrock for LLM access

Use Case 4: Coding Agent with MCP

• Learn the basics of Model Context Protocol (MCP)

• Build a coding agent using:

  • AWS CloudFormation MCP Server

  • Amazon Q CLI

Skills & Concepts You’ll Learn

Agentic AI Foundations

• Planning, memory, and tool usage in AI agents

• Designing autonomous and collaborative agent behavior

Amazon Bedrock Deep Dive

• Bedrock Agents architecture

• Knowledge Bases and retrieval integration

• Multi-agent orchestration patterns

CrewAI Framework

• Core concepts of CrewAI

• Building collaborative AI agent teams

MCP & Tool Interoperability

• Understanding Model Context Protocol (MCP)

• Connecting agents to external tools and services

AWS-Ready Development

• Using AWS Lambda with AI agents

• Python and Boto3 for Bedrock integration

• Infrastructure automation with CloudFormation

AI Agents For All! Build No-Code AI Agents & Master AI

Start Course

Who This Course Is Best Suited For

• AI engineers working with AWS and Generative AI

• Cloud engineers exploring agentic AI architectures

• Developers building enterprise-grade AI agents

• Professionals preparing for production AI workloads

• Learners familiar with AWS who want deeper Bedrock experience

Prerequisites

• Basic knowledge of AWS services

• Familiarity with AWS Lambda and Amazon Bedrock is helpful

• Python basics recommended (refresher included)

Practical Value

This course stands out by focusing on production realism:

• Real AWS architectures

• Multi-agent orchestration

• Tool-driven agents

• Cloud-native deployment

Rather than toy examples, learners gain transferable skills directly applicable to enterprise AI projects.

Career & Industry Relevance

Skills from this course align with roles such as:

• AI Engineer (Agentic AI)

• AWS Generative AI Engineer

• Cloud AI Architect

• MLOps / AI Platform Engineer

• Enterprise Automation Engineer

Final Verdict

Build Production-Ready AI Agents on AWS – Bedrock, CrewAI & MCP is a focused, hands-on course for professionals who want to deploy scalable, real-world AI agents on AWS. With practical use cases, multi-agent architectures, and deep Bedrock integration, it’s an excellent choice for moving from experimentation to production-grade agentic AI systems.