Amazon Bedrock AgentCore: Build & Deploy any AI Agent on AWS (Udemy.com)
Build & deploy production ready agentic AI apps on AWS with Amazon Bedrock AgentCore & serverless architecture[Hands-On]
Created by: Rahul Trisal
Last updated August 2026
What you will learn
- Learn the basic concepts related to Amazon Bedrock AgentCore Building Blocks (Primitives)- Agentcore Runtime, Observability, Memory, Identity and Gateway
- Build an Agentic AI App from scratch - Vacation Planner app
- Bedrock AgentCore Runtime – Deploy Agentic AI App with AgentCore Runtime + Lambda + API Gateway [Hands-On]
- Bedrock AgentCore Observability [Hands-On] – Monitor with OpenTelemetry & CloudWatch
- Amazon Bedrock AgentCore Memory [Hands-On] – Add context and session memory
- Amazon Bedrock AgentCore Identity & Gateway [Hands-On]– Setup AgentCore Gateway & invoke Agent Tools
- Refresher: Agentic AI, CrewAI, and MCP
How it compares
Against the other 1,182 rated Udemy courses in IT & Software on CourseDuck:
- Rating4.5 out of 5higher than 45% of them
- Reviews722#484 of 1,183 by number of reviews
- Length5.6 hourslonger than 50% of them
- Last updatedAugust 2026more recently than 84% of them
Course Description
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)
Instructor Details
- 4.5 Rating
722 Reviews
Rahul Trisal
- I work as an AWS Agentic and Generative AI Architect with a Fortune 500 company and have over 17 years of hands-on experience designing, modernizing, and scaling systems on AWS.
- I have built more than 12 enterprise-grade Agentic AI applications, with multiple solutions running in production environments. (Read more about the production grade solutions that I built on my Linkedin profile)
- I started working on AWS in 2008 and since then, I have led the migration of several hundred applications to AWS. In recent years, my primary focus has been on building and productionizing Generative AI and Agentic AI systems using modern AWS services.
- I am a 9× Certified and AWS Community Builder.
- Have taught over 50,000+ learners GenAI and Agentic AI on AWS, with more than 10 million minutes of content consumed.
- My goal is to help engineers and architects bridge the gap between tutorials and real-world, production systems.
- Currently based out of Bengaluru, India. Previously worked across USA, UK, Africa, and Latin America
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Reviews
By Sampark Mehrotra on 9/21/2026
This course is highly informative, and the hands-on exercises are especially very valuable. I would definitely recommend it to anyone who wants to understand AgentCore functionalities from scratch, particularly how AgentCore can be integrated into real-world production applications.
By rama chandra on 9/3/2026
Highly recommended! It’s a neat, clean, and well-structured course that is very easy to understand. The explanations are clear and practical, making it easy to follow along and learn the concepts.
By Manab Das on 8/12/2026
Easy explanation without unnecessary jargons and flashy show up. Plain and simple, just to the point demo without wasting your time. Short and crisp but loaded with adequate information. Good one !!!. Many of my colleagues recommended me this course and I recommend this too.
By Pulkit Agarwal on 8/3/2026
All good, but one thing to mention: the resources you have attached are quite large, around 256 MB on average, and after extraction, they are around 700 MB. However, almost 90% of the size is due to the `.venv` folder. Kindly remove these `.venv` files containing such a large amount of data and reduce the resource size. This will help us set up the code locally much faster.
By Vidyasakar on 7/26/2026
Some sessions would have broken into multiple sessions like the aws api config and could have given more details like how to connect multi agents, the end was so quick and no next steps etc., apart from that there is more to learn in this course, thank you for the same.
By Yuki Umetsu on 7/19/2026
This is a great hands on course with good explanations but CrewAI version used in the video is outdated. The CrewAI documentation changed a lot since then (version 0.X vs 1.X). The project setup through CLI is very different as well. If the CrewAI coding part gets updated, I'll give 5 star! Thank you!
By Rakesh Kuwar on 7/3/2026
I liked the way the course has been structured. Learned something new this week. However, I have mainly worked on Langchain/LangGraph so it would be great if any agentic use-case using this framework. Besides, good to learn crew-ai to some extent.
By Dhulagouda Sidagoudanavar on 5/6/2026
The best instructor I’ve ever come across—your explanations are clear, combining strong concepts with real-time projects. Thank you so much, Rahul Trisal, for your course. It truly builds confidence in many people to understand and develop AI skills
By Anonymized User on 3/13/2026
Bhai, sach mein maza aa gaya — aapne ise bahut hi simple bana diya. Please ek baar LangGraph par bhi kuch banaiye, mujhe woh abhi bhi kaafi complex lagta hai. Lekin is course me sach mein bahut maza aaya.
By Peter Buswell DrVoIP on 1/14/2026
Rahual has done a remarkable job with the Agentic subject matter. Well written, well presented and appropriate for those who are looking to understand how AWS implements Agentic's. Thank you for your excellent work as both a developer and as a talented instructor!
Quality Score
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Overall Score : 90 / 100
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