Course Information
Course Overview
Build 7+ GenAI Use Cases on AWS with Amazon Bedrock, RAG, Langchain, AI Agents, MCP, LLM. No AI/Coding exp req
Amazon Bedrock, Amazon Q and AWS GenAI Course :
***Hands - On Use Cases implemented as part of this course***
Use Case 1 - Text Summarization for Manufacturing Industry using API Gateway, S3 and Cohere Foundation Model
Use Case 2 - Build a Chatbot using Amazon Bedrock - DeepSeek, Langchain and Streamlit.
Use Case 3- Build an Employee HR Q & A Application with Retrieval Augmented Generation (RAG) -
Claude FM + Langchain (Ochestrator)+ FAISS (Vector DB) + Streamlit
Use Case 4 - Serverless e-Learning App using Bedrock Knowledge Base + Claude FM + AWS Lambda + API Gateway
Use Case 5 - 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 6 - Build Infrastructure Coding Agent using Amazon Q CLI and AWS CloudFormation Server.
Use Case 7 - Amazon Q Business - Build a Marketing Manager App with Amazon Q Business
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: Text Summarization for Manufacturing Industry using API Gateway, S3 and Cohere Foundation Model
Section 6 - Use Case 2 : Build a Chatbot using Bedrock - DeepSeek, Langchain and Streamlit
Section 7 - Use Case 3- Build a Employee HR Q & A Application with Retrieval Augmented Generation (RAG) -
Amazon Bedrock (Claude Foundation Model) + Langchain (Ochestrator)+ FAISS (Vector DB) + Streamlit
Section 8 - Serverless e-Learning App using Bedrock Knowledge Base + Claude FM + AWS Lambda + API Gateway
Section 9 - Build a Retail Banking Agent using Amazon Bedrock Agents and Knowledge Bases, Dynam0DB, Lambda
Section 10 - Python Basics Refresher
Section 11 - AWS Lambda Refresher
Section 12 - 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)
Course Content
- 23 section(s)
- 97 lecture(s)
- Section 1 Introduction
- Section 2 Basics of AI, ML & Neural Networks - Overview for Beginners
- Section 3 Generative AI & Foundation Models Concepts
- Section 4 Amazon Bedrock – Deep Dive
- Section 5 Use Case : GenAI Powered Equipment SME Assistant (PoC to Production)
- Section 6 GenAI AI Architect Roadmap on AWS: Skills You Need to Learn in 2026 (Optional)
- Section 7 Use Case 3 (Hands-On) : Build a Chatbot with DeepSeeK, Langchain and Streamlit
- Section 8 Overview of Vectors & Embedding (From my AWS AI Practioner Certificaion Course)
- Section 9 Use Case 4 (Hands-On) : Building HR Q & A with Retrieval Augmented Generation
- Section 10 Use Case 5 : Serverless E-Learning App with Knowledge Base, Lambda and API GW
- Section 11 Use Case 6 - Building a Retail Bank Agent using Bedrock Agents and KnowledgeBase
- Section 12 AWS Model Context Protocol (From my other Udemy course on AWS AI Agents)
- Section 13 Phase 1 of GenAI Project - Use Case Identification
- Section 14 Phase 2 of GenAI Project - Foundation Model Selection
- Section 15 Phase 3 (A) of GenAI Project - Prompt Engineering
- Section 16 Phase 3(B) of GenAI Project - Fine Tuning of Foundation Model
- Section 17 Building AI responsibly (From my AWS AI Practitioner Certification Udemy Course)
- Section 18 Use Case 7 : Amazon Q-Marketing Manger App (From my AWS AI Practitioner Course)
- Section 19 Amazon Q - Developer (From my AWS AI Practitioner Certification Udemy Course)
- Section 20 Python Basics Refresher
- Section 21 AWS Lambda Function Refresher
- Section 22 AWS API Gateway Refresher
- Section 23 Bonus Lecture
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: Text Summarization for Manufacturing Industry using API Gateway, S3 and Cohere Foundation Model, Use Case 2 - Build a Chatbot using Bedrock Converse API - DeepSeek and Nova Pro Foundation Model, Langchain and Streamlit, Use Case 3- Employee HR Q & A App with Retrieval Augmented Generation (RAG) - Bedrock - Claude Foundation Model + Langchain + FAISS + Streamlit, Use Case 4 : Serverless e-Learning App using Bedrock Knowledge Base + Claude FM + AWS Lambda + API Gateway, Use Case 5 : Build a Retail Banking Agent using Amazon Bedrock Agents & Knowledge Bases, Use Case 6 - Build Infrastructure Coding Agent using Amazon Q CLI and AWS CloudFormation Server., Use Case 7 : Amazon Q Business - Build a Marketing Manager App with Amazon Q, Python Basics Refresher, AWS Lambda and API Gateway Refresher
Skills covered in this course
Reviews
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AAnonymized User
To the point , Good ever course on bedrock and aws services. Thanks
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SSourav Maharana
One of the best AWS AI course I have taken in Udemy. Its not like your traditional course, but a better one. The instructor is very knowledgeable and takes time to explain certain concepts and makes sure he demonstrates it in the AWS. If you are someone looking forward more to the AI implementations, then this is the course. The instructor has done a very good job of sharing his architecture knowledge and keeps the course very engaging
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SSridhar
I am a beginner to gen AI and this is my first online course. Course was designed in a proper order and made it easy for a new learner. Rahul has good understanding on the subject and he has put it in easy way. Very much useful to me. I recommend this as a must course for everyone to go through.
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RRastin Mehr
This course offered a great overview of the AI tools AWS provides. It also complemented my existing knowledge of AWS services and helped me understand how to build custom AI tools.