Generative AI on AWS - Amazon Bedrock, RAG & Langchain[2026]

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Generative AI on AWS - Amazon Bedrock, RAG & Langchain[2026]

Name: Generative AI on AWS - Amazon Bedrock, RAG & Langchain[2026]
Price: 9.99 USD
Availability: InStock
Rating: 4.5 (26200 reviews)

★4.5

(26,200 students)

13h

>_ What You'll Learn

Learn fundamentals about AI, Machine Learning and Artificial Neural Networks.
Learn how Generative AI works and deep dive into Foundation Models.
Amazon Bedrock – Detailed Console Walkthough, Bedrock Architecture, Pricing and Inference Parameters.
Use Case 1: Media and Entertainment Industry: Generate Movie Poster Design using API Gateway, S3 and Stable Diffusion Foundation Model
Use Case 2: Text Summarization for Manufacturing Industry using API Gateway, S3 and Cohere Foundation Model
Use Case 3 - Build a Chatbot using Bedrock Converse API - DeepSeek and Nova Pro Foundation Model, Langchain and Streamlit
Use Case 4- Employee HR Q & A App with Retrieval Augmented Generation (RAG) - Bedrock - Claude Foundation Model + Langchain + FAISS + Streamlit
Use Case 5 : Serverless e-Learning App using Bedrock Knowledge Base + Claude FM + AWS Lambda + API Gateway
Use Case 6 : Build a Retail Banking Agent using Amazon Bedrock Agents & Knowledge Bases
Use Case 7 - Build Infrastructure Coding Agent using Amazon Q CLI and AWS CloudFormation Server.
Use Case 8 : Amazon Q Business - Build a Marketing Manager App with Amazon Q
Use Case 9 - Capabilities of Amazon Q Developer over SDLC - HandsON
Bedrock Logging with AWS CloudWatch
GenAI Project Lifecycle: Phase 1 - Use Case Selection - Discuss about various phases of GenAI and How to identify right use case
GenAI Project Lifecycle: Phase 2 - Foundation Model Selection - Theory and Handson using AWS Bedrock Model Evaluation Service
GenAI Project Lifecycle: Phase 3 - Prompt Engineering - Factors Impacting Prompt design - Claude, Amazon Titan, Stability Diffusion, Prompt design Techniques
GenAI Project Lifecycle: Phase 4 - Fine Tuning of Foundation Models - Theory and Hands-On
Python Basics Refresher
AWS Lambda and API Gateway Refresher

>_ Requirements

There are no course pre-requisites for this course except basic AWS Knowledge. I will provide basic overview of AI/ML concepts and have included Python, AWS Lambda and API Gateway refresher at end of course in case you are not familiar with python coding or these AWS services.
Only very very basic AWS knowledge such as what is S3, AWS Lambda etc.

/ Course Details & Curriculum

Amazon Bedrock, Amazon Q and AWS GenAI Course :

***Hands - On Use Cases implemented as part of this course***

Use Case 1 - Generate Poster Design for Media Industry using API Gateway, S3 and Stable Diffusion Foundation Model

Use Case 2 - Text Summarization for Manufacturing Industry using API Gateway, S3 and Cohere Foundation Model

Use Case 3 - Build a Chatbot using Amazon Bedrock - DeepSeek, Langchain and Streamlit.

Use Case 4- Build an Employee HR Q & A Application with Retrieval Augmented Generation (RAG) -

Claude FM + Langchain (Ochestrator)+ FAISS (Vector DB) + Streamlit

Use Case 5 - Serverless e-Learning App using Bedrock Knowledge Base + Claude FM + AWS Lambda + API Gateway

Use Case 6 - Build a Retail Banking Agent using Amazon Bedrock Agents and Knowledge Bases -

Claude Sonnet + AWS Lambda + DynamoDB + Bedrock Agents + Knowledge Bases + OpenAPI Schema

Use Case 7 - Build Infrastructure Coding Agent using Amazon Q CLI and AWS CloudFormation Server.

Use Case 8 - Amazon Q Business - Build a Marketing Manager App with Amazon Q Business

Use Case 9 - Amazon Q Developer - Overview of the Code Generation capabilities of Amazon Q Developer - Over the SDLC

Welcome to the most comprehensive guide on Amazon Bedrock and Generative AI on AWS from a practising AWS Solution Architect and best-selling Udemy Instructor.

This course will start from absolute basics on AI/ML, Generative AI and Amazon Bedrock and teach you how to build end to end enterprise apps on Image Generation using Stability Diffusion Foundation, Text Summarization using Cohere, Chatbot using Llama 2,Langchain, Streamlit and Code Generation using Amazon CodeWhisperer.

The focus of this course is to help you switch careers and move into lucrative Generative AI roles.

There are no course pre-requisites for this course except basic AWS Knowledge. I will provide basic overview of AI/ML concepts and have included Python, AWS Lambda and API Gateway refresher at end of course in case you are not familiar with python coding or these AWS services.

I will continue to update this course as the GenAI and Bedrock evolves to give you a detailed understanding and learning required in enterprise context, so that you are ready to switch careers.

Detailed Course Overview

Section 2 - Evolution of Generative AI: Learn fundamentals about AI, Machine Learning and Artificial Neural Networks (Layers, Weights & Bias).

Section 3 - Generative AI & Foundation Models Concepts: Learn about How Generative AI works (Prompt, Inference, Completion, Context Window etc.) & Detailed Walkthrough of Foundation Model working.

Section 4 - Amazon Bedrock – Deep Dive: Do detailed Console Walkthough, Bedrock Architecture, Pricing and Inference Parameters.

Section 5 - Use Case 1: Media and Entertainment Industry: Generate Movie Poster Design using API Gateway, S3 and Stable Diffusion Foundation Model

Section 6 - Use Case 2: Text Summarization for Manufacturing Industry using API Gateway, S3 and Cohere Foundation Model

Section 7 - Use Case 3 : Build a Chatbot using Bedrock - DeepSeek, Langchain and Streamlit

Section 8 - Use Case 4- Build a Employee HR Q & A Application with Retrieval Augmented Generation (RAG) -

Amazon Bedrock (Claude Foundation Model) + Langchain (Ochestrator)+ FAISS (Vector DB) + Streamlit

Section 9 - Serverless e-Learning App using Bedrock Knowledge Base + Claude FM + AWS Lambda + API Gateway

Section 10 - Build a Retail Banking Agent using Amazon Bedrock Agents and Knowledge Bases, Dynam0DB, Lambda

Section 11 - GenAI Project Lifecycle: Phase 1 - Use Case Selection - Discuss about various phases of GenAI and How to identify right use case

Section 12 - GenAI Project Lifecycle: Phase 2 - Foundation Model Selection - Theory and Handson using AWS Bedrock Model Evaluation Service

Section 13 - GenAI Project Lifecycle: Phase 3 - Prompt Engineering - Factors Impacting Prompt design, Prompt design Techniques (Zero Shot, One Shot.), Good practices for writing prompts for Claude, Titan and Stability AI Foundation Models

Section 14 - GenAI Project Lifecycle: Phase 4 - Fine Tuning of Foundation Models - Theory and Hands-On

Section 15 - Code Generation using AWS CodeWhisperer and CDK - In Typescript

Section 16 - Python Basics Refresher

Section 17 - AWS Lambda Refresher

Section 18 - AWS API Gateway Refresher

IMPORTANT << Learning Path: GenAI Developer / Architect on AWS >>

Many learners ask how to switch their career to an AWS Generative AI Developer or Architect and which sequence of my Udemy courses they should follow. Here is some guidance based on my experience working in the IT industry.

My GenAI/Agentic AI courses are divided into two tracks

Hands-On learning to build real world skills required in the IT industry (Most important)

Certification preparation to help you pass the certification exam (Good to have)

<< Hands-On Courses >>

1. Hands-On Course 1 (Beginner) - Amazon Bedrock, Amazon Q & AWS Generative AI [Hands-On]

Start here if you’re new to GenAI & Amazon Bedrock.

2. Hands-On Course 2 (Intermediate) - Build Production Ready AI Agents on AWS – Bedrock, CrewAI & MCP

Take this after Course 1 - Focused on Agentic AI but will be easier to understand if you have taken Course 1

3. Hands-On Course 3 (Advanced) - Amazon Bedrock AgentCore : Deploy AI Agents on AWS

This is the advanced course and focused on how to deploy, scale, and operate AI agents in Production.

Recommend to take after Course 1 & Course 2.

<< AWS GenAI Certification Path >>

1. Certification Course 1 : AWS Certified AI Practitioner (AIF-C01) – Beginner to Advanced

· Take after Step 1, or

· In parallel with Step 2

Outcome

You pass AWS Certified AI Practitioner (AIF-C01) and understand GenAI concepts AWS expects.

2. Certification Course 2 : AWS Certified Generative AI Developer Professional (Coming Soon)

Author and Instructor

Rahul Trisal

Expert at Udemy

With years of hands-on experience in IT & Software, Rahul Trisal has dedicated thousands of hours to teaching and mentorship. This course is the culmination of industry best practices and a proven curriculum that has helped thousands of students transition into professional roles.

Community Feedback

★★★★★

Michael Chen

Verified Enrollment

"This Generative AI on AWS - Amazon Bedrock, RAG & Langchain[2026] course was exactly what I needed. The instructor explains complex IT & Software concepts clearly. Highly recommended!"

Sarah Johnson

Verified Enrollment

"I've taken many Udemy courses on cloud computing & architectural engineering, but this one stands out. The practical examples helped me land a job."

David Smith

Verified Enrollment

"Great value for money. The section on Amazon Bedrock was particularly helpful."

Emily Davis

Verified Enrollment

"Excellent structure and pacing. I went from zero to hero in IT & Software thanks to this course. Lifetime access is a huge plus."

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