Master Amazon Bedrock Agents, CrewAI & AWS MCP: Build Production-Ready AI Agents and Enterprise GenAI Applications
Description
[NEW] Amazon Bedrock Agents and AI Agents – Complete Course :
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Welcome to the most comprehensive guide on AWS Amazon Bedrock Multi-Agent Framework and CrewAI 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 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
Services Used in the Course :
Amazon Bedrock Agents
CrewAI
AWS MCP CloudFormation Server
Amazon Q CLI
Amazon Bedrock Agents – Multi-Agent Orchestration Framework
Amazon Bedrock Knowledge Bases
Amazon Nova Foundation Model
Claude Sonnet Foundation Model
AWS Lambda
AWS DynamoDB
Open API Schema
Streamlit
Basics of Generative AI
Everything related to AWS Amazon Bedrock
S3
Prompt design Techniques (Zero Shot, One Shot.) for Claude, Titan and Stability AI Foundation Models (LLMs)
Python
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Total Students | 3756 |
---|---|
Duration | 9.5 hours |
Language | English (US) |
Original Price | |
Sale Price | 0 |
Number of lectures | 70 |
Number of quizzes | 2 |
Total Reviews | 564 |
Global Rating | 4.597983 |
Instructor Name | Rahul Trisal |
Course Insights (for Students)
Actionable, non-generic pointers before you enroll
Student Satisfaction
90% positive recent sentiment
Momentum
🔥 Trending
Time & Value
- Est. time: 9.5 hours
- Practical value: 8/10
Roadmap Fit
- Beginner → Intermediate → Advanced
Key Takeaways for Learners
- Hands-on practice
- Real-world examples
- Project-based learning
- Step By Step
- Hands On
Course Review Summary
Signals distilled from the latest Udemy reviews
What learners praise
- Step By Step
- Hands On
- Clear Explanation
- Well Structured
- Project
Watch-outs
- Missing project
Difficulty
Best suited for
Marketers with some platform experience, Doers who prefer project-led learning
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