CF

Build AI Agents with AWS

3h 9m 7s
English
Paid

Unlock the power of artificial intelligence by designing, creating, and deploying AI agents using AWS. Build your own intelligent travel assistant, ready for production, while gaining practical experience to enhance your AI skills!

Course Highlights

What You Will Learn

  • How to create AI agents that collaborate to accomplish tasks using AWS Bedrock language models.
  • Design a system where multiple agents work together under the management of a supervisor.
  • Utilize AWS Lambda for efficient operation, eliminating the need for server management.
  • Structure and store critical travel data in Amazon S3 to ensure agents have constant access.
  • Set up secure and scalable APIs using AWS API Gateway to make AI agents accessible via the internet.
  • Integrate all components to build a full-fledged AI travel agent that provides real-time recommendations.

Benefits of Learning AI Agent Creation with AWS

AI isn't just about individual models—it's about their collaborative work. This course teaches you to build multi-agent AI systems using AWS Bedrock, enabling specialized agents to handle dynamic tasks. You will design and develop a travel planner capable of recommending restaurants, finding hotels, and addressing user queries in real time.

Through this course, you'll explore AWS Bedrock language models, organize agent workflows, and deploy comprehensive solutions using Lambda, API Gateway, and S3. Engage in practical assignments to gain real-world skills and confidence in crafting sophisticated AI applications.

Upon completing the course, you'll possess a production-ready AI system and the expertise to scale intelligent automation leveraging AWS cloud services.

Additional

Github Link to Resources

Agent Instructions

About the Author: Zero To Mastery

Zero To Mastery thumbnail

Zero To Mastery (ZTM) is a Toronto-based online coding academy founded by Andrei Neagoie, originally a senior developer at large Canadian tech firms before turning to teaching full-time. The academy's signature is the cohort-based bootcamp track combined with a deep self-paced course library, all aimed at career-changers and self-taught developers preparing to land software-engineering roles at top companies.

The instructor roster has grown well beyond Andrei to include other senior practitioners: Daniel Bourke (machine learning), Aleksa Tešić (DevOps), Jacinto Wong, and others. Courses cover the full software-engineering career path: web development with React and Next.js, Python, machine learning and deep learning, DevOps and cloud, system design, mobile, and the algorithm / data-structure interview prep that gates engineering jobs.

The CourseFlix listing under this source carries over 120 ZTM courses spanning that full range. Material is paid; ZTM itself runs on a monthly / annual membership model. The teaching style favours long-form, project-based courses where students build complete portfolio-quality applications rather than disconnected feature tutorials.

Watch Online 27 lessons

This is a demo lesson (10:00 remaining)

You can watch up to 10 minutes for free. Subscribe to unlock all 27 lessons in this course and access 10,000+ hours of premium content across all courses.

View Pricing
0:00
/
#1: What We Are Building - Part 1
All Course Lessons (27)
#Lesson TitleDurationAccess
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
Unlock unlimited learning

Get instant access to all 26 lessons in this course, plus thousands of other premium courses. One subscription, unlimited knowledge.

Learn more about subscription

Related courses

Frequently asked questions

What prerequisites do I need before enrolling in this course?
Before enrolling in the course, it is recommended that you have a basic understanding of cloud computing concepts and some familiarity with AWS services. While not mandatory, prior experience with programming languages used in AWS Lambda, such as Python or Node.js, will be beneficial. Knowledge of RESTful APIs and serverless architecture can also enhance your learning experience.
What will I build during the course?
During the course, you will build a fully functional AI travel agent capable of providing real-time recommendations for restaurants and accommodations. This includes designing a system where AI agents collaborate under a supervisory agent, utilizing AWS Bedrock language models, and integrating AWS services like Lambda, S3, and API Gateway. By the end, you'll have a production-ready travel assistant system.
Who is the target audience for this course?
The course is designed for developers and IT professionals interested in artificial intelligence and cloud services. It is particularly beneficial for those looking to leverage AWS for building AI applications. Students, engineers, and professionals aiming to enhance their skills in AI agent systems and cloud-based deployment will find this course valuable.
How does this course compare to other AI courses in terms of depth and scope?
Unlike many AI courses that focus on single-agent models, this course emphasizes the creation of multi-agent systems using AWS. It covers the collaborative aspect of AI, teaching you how to design and deploy agents that work together to complete tasks. The course provides hands-on experience with AWS-specific tools, which may not be the focus of other AI courses.
What specific AWS tools and platforms will I learn to use?
In the course, you will learn to use several AWS tools, including AWS Bedrock for language models, AWS Lambda for serverless computing, Amazon S3 for data storage, and AWS API Gateway for setting up secure APIs. These tools are integral to building and deploying the AI travel agent and will give you practical experience in using AWS for AI solutions.
What topics are not covered in this course?
The course does not cover advanced machine learning model training or data science methodologies. It focuses on the deployment and orchestration of pre-trained models using AWS services rather than building or training models from scratch. Those seeking to learn in-depth data science or custom model training should consider additional resources.
How much time should I expect to commit to this course?
The course consists of 27 lessons, each designed to progressively build your understanding and skills. While the total runtime is not specified, students should plan to spend several hours per week on lessons, exercises, and practical assignments. The time commitment will vary based on individual learning pace and familiarity with the topics covered.