05-24-2025, 06:22 PM
[center]
![[Image: maxresdefault.jpg]](https://i.postimg.cc/908tbsqY/maxresdefault.jpg)
Learn To Build Aws Bedrock Based End To End Ai Web App
Published 5/2025
MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz, 2 Ch
Language: English | Duration: 1h 54m | Size: 1.41 GB
Hands on course to build an AI/LLM based web Application using Amazon Bedrock, Lambda, API Gateway & CloudFront[/center]
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
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
Published 5/2025
MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz, 2 Ch
Language: English | Duration: 1h 54m | Size: 1.41 GB
Hands on course to build an AI/LLM based web Application using Amazon Bedrock, Lambda, API Gateway & CloudFront[/center]
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
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
Code:
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