Amazon Bedrock, Amazon Q & AWS Generative AI [HANDS-ON]

Build 8+ Use Cases with Amazon Bedrock, Amazon Q, Agents, Knowledge Bases, Chatbot, LangChain. No AI or Coding exp req

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 - Llama 2 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 : Amazon Q Business - Build a Marketing Manager App with Amazon Q
Use Case 8 - Capabilities of Amazon Q Developer over SDLC - HandsON
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.

Description
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 ModelUse Case 2 - Text Summarization for Manufacturing Industry using API Gateway, S3 and Cohere Foundation ModelUse Case 3 - Build a Chatbot using Amazon Bedrock - Llama 2, 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) + StreamlitUse Case 5 - Serverless e-Learning App using Bedrock Knowledge Base + Claude FM + AWS Lambda + API GatewayUse Case 6 - Build a Retail Banking Agent using Amazon Bedrock Agents and Knowledge Bases -                          Claude Sonnet + AWS Lambda + DynamoDB + Bedrock Agents + Knowledge Bases + OpenAPI SchemaUse Case 7 - Amazon Q Business - Build a Marketing Manager App with Amazon Q BusinessUse Case 8 - Amazon Q Developer - Overview of the Code Generation capabilities of Amazon Q Developer - Over the SDLCWelcome 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 OverviewSection 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 ModelSection 6 - Use Case 2: Text Summarization for Manufacturing Industry using API Gateway, S3 and Cohere Foundation ModelSection 7 - Use Case 3 : Build a Chatbot using Bedrock - Llama 2, Langchain and StreamlitSection 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) + StreamlitSection 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, LambdaSection 11 - GenAI Project Lifecycle: Phase 1 - Use Case Selection - Discuss about various phases of GenAI and How to identify right use caseSection 12 - GenAI Project Lifecycle: Phase 2 - Foundation Model Selection - Theory and Handson using AWS Bedrock Model Evaluation ServiceSection 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 ModelsSection 14 - GenAI Project Lifecycle: Phase 4 - Fine Tuning of Foundation Models - Theory and Hands-OnSection 15 - Code Generation using AWS CodeWhisperer and CDK - In TypescriptSection 16 - Python Basics RefresherSection 17 - AWS Lambda RefresherSection 18 - AWS API Gateway RefresherServices Used in the Course :Amazon BedrockAmazon Q Llama 2 Foundation ModelCohere Foundation ModelStability Diffusion ModelClaude Foundation Model from AnthropicClaude SonnetAmazon Bedrock AgentsBedrock Knowledge BaseLangchain - Chains and Memory ModulesFAISS Vector StoreAWS Code Generation using AWS Code Whisperer API GatewayAWS LambdaAWS DynamoDBOpen API SchemaStreamlitS3Prompt design Techniques (Zero Shot, One Shot.)  for Claude, Titan and Stability AI Foundation Models (LLMs)Fine Tuning Foundation Models - Theory and Hands-OnPythonEvaluation of Foundation Models - Theory and Hands-OnBasics of AI, ML, Artificial Neural NetworksBasics of Generative AIEverything related to AWS Amazon Bedrock

Who this course is for:
The course is designed to help you switch careers and move into lucrative Generative AI and Amazon Bedrock roles.