hands-on lab
Developing An Application on AWS using Generative AI
Difficulty: Beginner
Duration: Up to 1 hour and 30 minutes
Students: 232
Rating: 5/5
On average, students complete this lab in35m
Get guided in a real environmentPractice with a step-by-step scenario in a real, provisioned environment.
Learn and validateUse validations to check your solutions every step of the way.
See resultsTrack your knowledge and monitor your progress.
Description
Generative AI models can be an invaluable resource when developing applications. Using them to provide expert-level advice and assistance can greatly speed up and improve the quality of application development.
Learning how to make use of Generative AI models in a development context will benefit anyone looking to develop applications more efficiently.
In this hands-on lab, you will access a Generative AI model, and use it to develop and deploy an application hosted on AWS.
Learning objectives
Upon completion of this beginner-level lab, you will be able to:
- Access the Amazon Bedrock console and prompt a model
- Use a Generative AI model to generate an Infrastructure as Code (IaC) template
- Generate AWS Lambda function code that identifies anomalous amounts in transactions
- Validate and verify code manually and using tooling
Intended audience
- Candidates for the AWS Certified AI Practitioner certification
- Cloud Architects
- Data Engineers
- DevOps Engineers
- Machine Learning Engineers
- Software Engineers
Prerequisites
Familiarity with the following will be beneficial but is not required:
- Amazon Bedrock
- AWS Serverless Application Model (SAM)
- The Python coding language
The following content can be used to fulfill the prerequisites:
Environment before
Environment after
Covered topics
Lab steps
Logging In to the Amazon Web Services Console
Accessing an Amazon Bedrock Model
Using Generative AI to Create an AWS SAM Template
Deploying an AWS SAM Template
Implementing Your Function Using Generative AI