Build AI Agents with AWS
Course description
Learn to design, create, and deploy multiple AI agents using AWS by building your own intelligent travel assistant, ready for production. Gain practical experience and enhance your AI skills!
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What you will learn:
- How to create AI agents that work together to accomplish tasks using AWS Bedrock language models
- Design a system where multiple agents collaborate under the management of one supervisor
- Use AWS Lambda for efficient operation of agents without needing to manage servers
- Store and structure important travel data in Amazon S3 to ensure agents have constant access to it
- Make AI agents accessible via the internet by setting up secure and scalable APIs using AWS API Gateway
- Combine everything into one project, creating a full-fledged AI travel agent capable of providing real-time recommendations
Why learn to create AI agents with AWS?
AI is not just about individual models but their collaborative work. This course will teach you how to build multi-agent AI systems using AWS Bedrock, where specialized agents dynamically handle tasks. You will design a travel planner that can recommend restaurants, search for hotels, and respond to user requests in real time.
We will explore AWS Bedrock language models, the organization of agent work, and the deployment of solutions using Lambda, API Gateway, and S3. Practical assignments will give you real skills and confidence in creating AI applications.
By the end of the course, you will have a production-ready AI system and skills for scaling intelligent automation using AWS cloud services.
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All Course Lessons (27)
| # | Lesson Title | Duration | Access |
|---|---|---|---|
| 1 | What We Are Building - Part 1 Demo | 05:34 | |
| 2 | What We Are Building - Part 2 | 04:57 | |
| 3 | Sign In to AWS | 04:33 | |
| 4 | Creating an IAM User | 05:34 | |
| 5 | Signing In to New IAM User | 03:16 | |
| 6 | What To Do If Your AWS Gets Hacked | 01:32 | |
| 7 | Architecture Diagram of Our Multi Agentic Workflow | 06:42 | |
| 8 | LLM Model Access, API Rate Limits, Quotas, and AWS Regions | 07:48 | |
| 9 | Introduction to AWS Bedrock Agents | 01:05 | |
| 10 | Creating the Restaurant Agent | 17:34 | |
| 11 | Creating our AWS S3 Bucket To Store Our Data | 04:05 | |
| 12 | Uploading Restaurant Data to AWS S3 | 00:49 | |
| 13 | Creating an Action Group For Our Restaurant Agent | 13:02 | |
| 14 | Finishing Our Lambda Function for our Restaurant Agent | 12:27 | |
| 15 | Testing Our Restaurant Agent | 14:39 | |
| 16 | Setting Up the Accommodation Agent | 08:46 | |
| 17 | Uploading Our Hotel and Airbnb Data to AWS S3 | 01:15 | |
| 18 | Creating The Lambda Function Action Group For The Accommodation Agent | 17:41 | |
| 19 | Finishing Our Accommodation Agent | 09:50 | |
| 20 | Testing the Accommodation Agent | 08:21 | |
| 21 | Creating and Testing The Supervisor Agent | 09:01 | |
| 22 | Explaining Agent Collaborators | 04:42 | |
| 23 | Multi Agent UI Enhancement, Timing Agents | 02:52 | |
| 24 | Serverless Invocation of the Supervisor Agent using AWS Lambda | 11:52 | |
| 25 | Setting up AWS API Gateway to Deploy Our Worfklow Through the Internet | 03:25 | |
| 26 | Testing Our Endpoint Through The Internet with Postman | 05:15 | |
| 27 | Cleaning Up Resources | 02:30 |
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