Amazon Bedrock, Amazon Q & AWS Generative AI [2025]

8+ Use Cases with Amazon Bedrock, Amazon Q, Agents, Knowledge Bases, Chatbot,LangChain,DeepSeek. No AI or Coding exp req
4.61 (2441 reviews)
Udemy
platform
English
language
Other
category
Rahul Trisal
instructor
Amazon Bedrock, Amazon Q & AWS Generative AI [2025]
16 625
students
12.5 hours
content
Apr 2025
last update
$19.99
regular price

What you will 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 : Amazon Q Business - Build a Marketing Manager App with Amazon Q

Use Case 8 - 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

Course Gallery

Amazon Bedrock, Amazon Q & AWS Generative AI [2025] – Screenshot 1
Screenshot 1 – Amazon Bedrock, Amazon Q & AWS Generative AI [2025]
Amazon Bedrock, Amazon Q & AWS Generative AI [2025] – Screenshot 2
Screenshot 2 – Amazon Bedrock, Amazon Q & AWS Generative AI [2025]
Amazon Bedrock, Amazon Q & AWS Generative AI [2025] – Screenshot 3
Screenshot 3 – Amazon Bedrock, Amazon Q & AWS Generative AI [2025]
Amazon Bedrock, Amazon Q & AWS Generative AI [2025] – Screenshot 4
Screenshot 4 – Amazon Bedrock, Amazon Q & AWS Generative AI [2025]

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Our Verdict

The Amazon Bedrock and AWS Generative AI course offers a strong foundation in various AI tools and services, combining theory with practical, hands-on examples. While some basic familiarity with AWS and programming is beneficial, the instructor's clear guidance and documentation references make this an approachable learning experience for those willing to learn. Despite minor issues like outdated code snippets, the course remains a valuable resource for getting started on your GenAI journey using AWS Bedrock and other services.

What We Liked

  • Comprehensive coverage of Amazon Bedrock, Amazon Q, Agents, Knowledge Bases, Chatbot, LangChain, DeepSeek with 8+ Use Cases
  • Instructor develops understanding at each step with demos and use cases, facilitating hands-on learning while you're developing
  • Realistic examples bring concepts to life; instruction on how to code with language and refer documentation for better understanding
  • Regular updates to the course curriculum ensure content relevance, as seen with CodeWhisperer integration into Amazon Q Developer

Potential Drawbacks

  • Some AWS knowledge is recommended as a prerequisite for following along with the course materials
  • Occasional outdated code examples due to rapid library changes like langchain
  • Advanced topics not covered in depth; primarily provides an overview of these subjects
5617274
udemy ID
19/10/2023
course created date
28/12/2023
course indexed date
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course submited by