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Amazon Bedrock – The Complete Guide to AWS Generative AI

سرفصل های دوره

Learn to Deploy Scalable, Reliable, and Secure Generative AI Apps Using AWS and Amazon Bedrock (Python and TypeScript)


1 - Course Introduction
  • 1 - How to take this course
  • 2 - Udemy tips
  • 3 - Tools setup

  • 2 - Introduction to Amazon Bedrock
  • 4 - Section intro
  • 5 - What is Amazon Bedrock
  • 6 - Bedrock console overview
  • 7 - AWS configure CLI access
  • 8 - Bedrock API Boto3 Python
  • 8 - Code changes in this lecture.txt
  • 9 - Bedrock API JS SDK TypeScript
  • 9 - Code changes in this lecture.txt
  • 10 - Code changes in this lecture.txt
  • 10 - Optional VSCode debug

  • 3 - Working with text models
  • 11 - Section intro
  • 12 - Amazon Bedrock text models intro
  • 13 - Understanding tokens
  • 14 - Text models parameters
  • 15 - Bedrock text models Python
  • 15 - Code changes in this lecture.txt
  • 16 - Bedrock text models TypeScript
  • 16 - Code changes in this lecture.txt
  • 17 - Code changes in this lecture.txt
  • 17 - Prompt engineering
  • 17 - Prompt engineering docs.txt
  • 18 - Code changes in this lecture.txt
  • 18 - Project ChatBot
  • 19 - ChatBot with History Python
  • 19 - Code changes in this lecture.txt
  • 20 - ChatBot with History TypeScript
  • 20 - Code changes in this lecture.txt

  • 4 - Amazon Bedrock Image models
  • 21 - Section intro
  • 22 - Image models intro
  • 23 - Stability AI parameters
  • 23 - Stability AI params.txt
  • 24 - Code changes in this lecture.txt
  • 24 - Stability AI images Python and TypeScript
  • 25 - Code changes in this lecture.txt
  • 25 - Titan model image generation
  • 26 - Code changes in this lecture.txt
  • 26 - Titan model image editing

  • 5 - Amazon Bedrock embedding models
  • 27 - Section intro
  • 28 - Code changes in this lecture.txt
  • 28 - Embeddings and Similarity
  • 29 - Code changes in this lecture.txt
  • 29 - Embedding models Python and TypeScript
  • 30 - Code changes in this lecture.txt
  • 30 - Text embeddings Python
  • 31 - Code changes in this lecture.txt
  • 31 - Text embeddings TypeScript
  • 32 - Code changes in this lecture.txt
  • 32 - Image embeddings Python
  • 33 - Code changes in this lecture.txt
  • 33 - Image embeddings TypeScript
  • 34 - Vector databases

  • 6 - Halfway discussion
  • 35 - Section intro

  • 7 - Project RAG app local
  • 36 - Section intro
  • 36 - langchain-py.zip
  • 36 - langchain-ts.zip
  • 37 - Langchain intro
  • 38 - Code changes in this lecture.txt
  • 38 - First Chain Python
  • 39 - Code changes in this lecture.txt
  • 39 - First Chain TypeScript
  • 40 - What is a RAG app
  • 41 - Basic RAG app Python
  • 41 - Code changes in this lecture.txt
  • 42 - Basic RAG app TypeScript
  • 42 - Code changes in this lecture.txt
  • 43 - Code changes in this lecture.txt
  • 43 - Document app Python
  • 44 - Code changes in this lecture.txt
  • 44 - Document app TypeScript

  • 8 - Practice Text API
  • 45 - Section intro
  • 46 - Project architecture
  • 47 - Code changes in this lecture.txt
  • 47 - Summary Lambda Python
  • 48 - Code changes in this lecture.txt
  • 48 - Summary Lambda test Python
  • 49 - Code changes in this lecture.txt
  • 49 - Summary Lambda TypeScript
  • 50 - Code changes in this lecture.txt
  • 50 - Summary Lambda test TypeScript
  • 51 - ApiGateway and Lambda integration
  • 51 - Code changes in this lecture.txt
  • 52 - Code changes in this lecture.txt
  • 52 - IAC Summary api CDK Python
  • 53 - Code changes in this lecture.txt
  • 53 - IAC Summary api CDK TypeScript

  • 9 - Practice Image API
  • 54 - Section intro
  • 55 - Project architecture
  • 56 - Code changes in this lecture.txt
  • 56 - Image Lambda Python
  • 57 - Code changes in this lecture.txt
  • 57 - Lambda Test Python
  • 58 - Code changes in this lecture.txt
  • 58 - Image Lambda TypeScript
  • 59 - Code changes in this lecture.txt
  • 59 - Lambda Test TypeScript
  • 60 - ApiGateway and Lambda integration
  • 60 - Code changes in this lecture.txt
  • 61 - Code changes in this lecture.txt
  • 61 - IAC Image api CDK Python
  • 62 - Code changes in this lecture.txt
  • 62 - IAC Image api CDK TS

  • 10 - Practice Bedrock knowledge bases
  • 63 - Section intro
  • 64 - What is Bedrock knowledge base
  • 65 - Bedrock Knowledge base model access
  • 66 - New console account creation
  • 67 - Creating a knowledge base
  • 68 - Code changes in this lecture.txt
  • 68 - RAG Lambda Python
  • 69 - Code changes in this lecture.txt
  • 69 - RAG Lambda TypeScript
  • 70 - Code changes in this lecture.txt
  • 70 - RAG Lambda AWS test
  • 71 - Code changes in this lecture.txt
  • 71 - RAG ApiGateway integration
  • 72 - Resorces deletion

  • 11 - Custom Amazon Bedrock models
  • 73 - Section intro
  • 74 - Fine tuning
  • 75 - Custom models Amazon Bedrock console

  • 12 - Ending section
  • 76 - Thank you

  • 13 - Optional AWS Recap
  • 77 - Section intro
  • 78 - AWS IAM presentation
  • 79 - AWS Lambda presentation
  • 80 - AWS API Gateway presentation

  • 14 - Optional Infrastructure as code
  • 81 - Section intro
  • 82 - AWS CloudFormation
  • 82 - Code changes in this lecture.txt
  • 83 - AWS CDK install
  • 84 - AWS CDK with Python
  • 84 - Code changes in this lecture.txt
  • 85 - AWS CDK with TypeScript
  • 85 - Code changes in this lecture.txt
  • 86 - Cleanup
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    شناسه: 38590
    حجم: 4240 مگابایت
    مدت زمان: 446 دقیقه
    تاریخ انتشار: 26 تیر 1403
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