What you'll learn
⚡ Build an AI-powered document assistant using Amazon Bedrock and RAG
⚡ Use Amazon Bedrock Knowledge Bases and S3 to answer questions from your own documents
⚡ Define and deploy cloud infrastructure using AWS CDK, Docker, ECS, and Fargate
⚡ Build an automated CI/CD workflow with GitHub Actions while working with an AI coding agent

Requirements
❗ Basic understanding of web development
❗ Basic familiarity with AWS

Description
This hands-on workshop brings together generative AI, cloud, application development, Infrastructure as Code, containers, and CI/CD to build a complete AI document assistant on AWS.

Unlike my regular Hands-On Introduction courses, this workshop isn't focused on teaching one technology from scratch.

Instead, we'll start with an empty folder and use an AI coding agent inside Cursor to build and deploy an application that lets users upload their own documents and ask questions grounded in those documents.

And just like in the other workshops in this series, we're not going to hand-write the application or infrastructure code ourselves.

We'll direct the AI agent, review what it produces, test its decisions, and work through the problems we encounter along the way.

The application we'll build is an AI-powered document assistant.

Users will be able to upload documents through a Next.js application, store them in Amazon S3, and make them available through an Amazon Bedrock Knowledge Base. Once the documents have been processed and indexed, users can ask questions and receive answers grounded in their own content, together with citations pointing back to the source documents.

This gives us a practical implementation ofRetrieval-Augmented Generation, or RAG.

Throughout the workshop, we'll work with

✨ AI-assisted development with Cursor

✨ Retrieval-Augmented Generation (RAG)

✨ Amazon Bedrock

✨ Amazon Bedrock Knowledge Bases

✨ Foundation models

✨ Embeddings and vector search

✨ Amazon S3

✨ Next.js

✨ Docker

✨ AWS CDK with TypeScript

✨ Infrastructure as Code

✨ Amazon ECS

✨ Git and GitHub

✨ GitHub Actions for CI/CD

✨ Automated cloud deployments

We'll start with an empty project and use the AI coding agent to help us determine how the different pieces should fit together.

We'll build a Next.js interface where users can upload documents and interact with them through a question-and-answer experience.

Those documents will be stored in Amazon S3 and connected to an Amazon Bedrock Knowledge Base, giving us a managed RAG workflow for ingesting, indexing, retrieving, and using our own documents as context for foundation models.

On the question-answering side, we'll retrieve relevant information from the knowledge base and use Amazon Bedrock to generate responses grounded in our documents rather than relying solely on the model's existing knowledge.

We'll also work with citations so users can see which source documents contributed to an answer.

But building the AI functionality is only part of the workshop.

We'll useAWS CDK with TypeScript to define our cloud infrastructure as code, containerize the application with Docker, and deploy it using Amazon ECS and AWS Fargate.

We'll then connect everything to GitHub and create a GitHub Actions CI/CD pipeline so changes can automatically move from our repository to the deployed application.

As with every workshop in this series, the AI agent won't necessarily get everything right the first time.

That's intentional.

AI coding agents are non-deterministic. They can choose approaches we didn't expect, create incorrect configurations, misunderstand requirements, or generate code and infrastructure that simply don't work.

Instead of hiding those moments, we'll use them to understand how to direct an agent, inspect what it generates, troubleshoot problems, and decide whether its proposed solution actually makes sense.

That's one of the main differences between this workshop and a traditional step-by-step tutorial.

By the end of the workshop, we'll have connected application development, generative AI, RAG, document storage, vector search, Infrastructure as Code, containers, cloud deployment, and CI/CD into one working system.

More importantly, you'll have seen how all of these individual technologies fit together when building something larger than another isolated AI chatbot demo.

This workshop is a great fit if you are

✨ A developer interested in building practical generative AI applications

✨ An AWS developer or cloud engineer exploring Amazon Bedrock

✨ A developer who wants to understand RAG through a real project

✨ A full-stack developer exploring AI-powered applications

✨ Someone interested in AI-assisted software development with Cursor

✨ Anyone familiar with individual AWS, AI, or DevOps technologies who wants to see how they work together

This workshop assumes some familiarity with AWS, web development, generative AI concepts, and Infrastructure as Code. We won't teach every individual technology from scratch.

If concepts such as Amazon Bedrock, embeddings, vector databases, AWS CDK, or containers are completely new to you, my individual Hands-On Introduction courses cover those topics in more detail.

Here, the goal is differentut the pieces together and build something.

Who this course is for
⭐ Developers interested in building practical generative AI and RAG applications
⭐ AWS developers exploring Amazon Bedrock and Knowledge Bases
⭐ Full-stack developers who want to add AI capabilities to applications
⭐ Cloud and DevOps engineers interested in AI workloads
⭐ Developers experimenting with Cursor and AI coding agents
⭐ Students familiar with individual technologies who want to see how they work together in a complete project


https://rapidgator.net/file/ef570f672d14f27d06c41ac2db5d2f6f/Hands-On_Workshop_Build_an_AI_Document_Assistant_on_AWS.part1.rar.html
https://rapidgator.net/file/92eab288b832e9e1832ea4f503799497/Hands-On_Workshop_Build_an_AI_Document_Assistant_on_AWS.part2.rar.html
https://rapidgator.net/file/21d8796418fab4a1bf0d5dba5ee84dea/Hands-On_Workshop_Build_an_AI_Document_Assistant_on_AWS.part3.rar.html
https://rapidgator.net/file/ca22f5f95476f3b575b84b5ba9cc30a4/Hands-On_Workshop_Build_an_AI_Document_Assistant_on_AWS.part4.rar.html