Learn to build AWS Bedrock based end to end AI Web App

Name: Learn to build AWS Bedrock based end to end AI Web App
Rating: 5.0 (1 reviews)

Hands on course to build an AI/LLM based web Application using Amazon Bedrock, Lambda, API Gateway & CloudFront

Created byNilesh Shukla

Last updated 4/2026

English

English [Auto],

What you'll learn

Learn about AWS services like: CloudFront, S3, API Gateway, Lambda, Bedrock, IAM and CloudWatch
Be able to code & test Lambda using Python 3.13 and use CloudWatch & Amazon Q to debug and resolve permissions issues
Able to build Global & Scalable static website using S3
Able to build website to call Lambda function from Web Page hosted on S3
Able to sent curated prompt from End user's web browser to Amazon's Titan Model provided by Bedrock & send results back to the end user Browser
Able to look at CloudWatch logs and write Python code to parse json and extract required data elements

Course content

5 sections • 16 lectures • 1h 54m total length

Introduction5:32
Learn to build an end-to-end AI web app on AWS Bedrock by wiring a static site, S3, API gateway, Lambda, and foundation models for dynamic prompts and global deployment.

AWS Account Creation5:41
Create an AWS account using the free tier, verify email, and enter contact and credit card details. Access the console to launch EC2 instances.
AWS Navigation & IAM User Creation, AWS Billing Overview7:57
Explore the AWS console navigation, create admin IAM users and groups, attach policies, and monitor billing with budgets and alarms to manage end-to-end Bedrock AI app workloads.

AWS Lambda Overview7:44
Explore AWS Lambda, a serverless compute service that runs code without server management, highlighting event-driven design, automatic scaling, and cost efficiency.
AWS S3 Overview6:04
Learn about S3, 11 nines durability, a scalable object storage with static website hosting and CloudFront/Lambda integration, including storage classes and latency, access control, and cost considerations.
AWS Bedrock service overview4:56
Explore AWS Bedrock, a fully managed serverless service that provides access to foundation models from major providers via a single API, with retrieval augmented generation and knowledge base integration.
AWS API Gateway Overview2:58
Explore AWS API Gateway, a managed service that exposes AWS artifacts to internet, integrates with Lambda and S3, and balances security, scaling, and tradeoffs like cold starts and rate limits.
AWS CloudFront Overview4:41
Explore AWS CloudFront, a global content delivery network with edge locations and caching that yields low latency, reduces origin load, and note the free tier of 1 TB data transfer.

Build Static website with AWS S36:42
Learn to create a static website on AWS S3, configure a bucket, enable static website hosting, set public access, upload index.html, and obtain the website endpoint.
Explore & Create Basic Lambda Function7:22
Explore bedrock, an AWS managed service, and build a Python lambda to fetch available models, connect to a foundation model, send a prompt, and view results via CloudWatch.
Code Lambda to get Foundation Model List provided by Bedrock9:23
Learn to connect to bedrock with boto3, list all foundation models in us-east-1, and parse and display model ids, names, and providers for an ai web app.
Build Lambda to call Foundation Model using AWS Bedrock10:25
Learn to connect a lambda function to AWS Bedrock, request access to Titan text G1 express, invoke the model via Bedrock runtime, and decode the response to extract the output.
Integrate AWS API Gateway with AWS Lambda12:46
Integrate a Lambda function with an API Gateway HTTP endpoint to power a static site form, decode inputs, and prompt an LLM for end-to-end AWS Bedrock AI web app recipes.
Deploy CloudFront for AWS S3 static website7:14
Deploy a CloudFront distribution for an AWS S3 static website, configure the endpoint and http-to-https redirection, and publish the static content and architecture diagram.

Test Application End to End and validate Architecture5:26
Learn to validate an aws bedrock end-to-end ai web app by tracing the browser to cloudfront and s3, through api gateway and lambda to bedrock, with decoding in python 3.13.
Wrap-up and Next Steps!9:42
Wrap up the course by summarizing an end-to-end AWS Bedrock AI web app, covering AWS services, architecture, cost awareness, and knowledge bases with retrieval augmented generation.

Requirements

Ability to create Amazon AWS Account (need valid credit card, charges depend on services used, less than 5$ for me))

Description

In this hands-on course, you will follow along step-by-step to build a Cloud Native AWS Bedrock based AI Web App that sends data from User's Web Browser, using S3 based static website on CloudFront to API Gateway, to AWS Lambda and finally to an AWS Bedrock, where in call is made to a Foundation Model (FM) provided by bedrock and response is sent back to end user's browser based on the prompt that was received. This course is designed to provide practical, real-world skills by walking through each component of the architecture, ensuring that learners not only understand the concepts but also apply them directly in a cloud environment.

On the AWS side, you will gain experience working with several important services, including AWS IAM for securing resources, AWS CloudFront for deploying the web app we create globally at scale, API Gateway to be able to execute AWS Lambda function via a public end point used in S3 web form and AWS CloudWatch for monitoring and logging the data sent back & forth to Lambda. The AWS Lambda interacts with AWS Bedrock service and sends prompts to LLM/FM and obtain Generative response for the user to view on the browser based on prompt sent. These services are essential for building secure, scalable, and reliable applications in the cloud. In this course we curate prompt for user to send 3 Ingredients and send back a recipe idea generated by Foundation Model (FM/LLM - Amazon - Titan) back to user browser.

By the end of this course, you will have built a working, scalable AI based Web Application, gained insights into cloud-native architectures, and acquired hands-on experience that can be directly applied to real-world projects or professional roles.

This course is suitable for Entry Level budding Cloud Engineers who are looking to build AWS development skills, looking to work on Real Life project and wanting to add one to their resume. It will help them be more confident when interviewing, since they will work hands-on in this course. This course will also help mid level Cloud Engineers expose themselves to latest and fastest growing Technology area of AI, Foundation Models and their Applications. It will also help Product Owners, Product Mangers, Scrum Masters and Technology Leaders looking to get a hands-on experience of building an End to End Web Browser based Application that leverages Generative power of Foundation Model/LLM provided by AWS Bedrock.

Who this course is for:

Beginner Budding Cloud Engineers looking to build AWS skills and add to their Resumes
Beginner Budding Cloud Engineers looking to build AWS Bedrock skills to make headway to learn building AI Apps
Mid Level to Sr. Cloud Engineers to foray into Bedrock and build End to End POC type AI application
Product Owners and Product Managers wanting to know details on what goes in to build Cloud Native AI app using AWS and help them brainstorm for future use cases
Technology Leaders looking to get hands-on and know more of issues/efforts/potential of building Cloud Native AWS based End to End AI Application

Learn to build AWS Bedrock based end to end AI Web App

What you'll learn

Explore related topics

Course content

Introduction1 lecture • 6min

AWS Account creation & Overview2 lectures • 14min

AWS Services Overview5 lectures • 26min

Building the Application6 lectures • 54min

Tie all parts and Test Application End to End2 lectures • 15min

Requirements

Description

Who this course is for: