Building Applications Using Amazon Bedrock
Building Applications Using Amazon Bedrock
.MP4, AVC, 1280x720, 30 fps | English, AAC, 2 Ch | 2h 9m | 325 MB
Instructor: Lee Assam
Learn how to build generative AI applications using Amazon Bedrock. In this course, Lee Assam, a principal technologist as well as a university instructor, covers a series of typical use cases, including a semantic search using the RAG (Retrieval Augmented Generation) architecture via a conversational chatbot, text summarization, and content generation.
Discover how to use the LangChain framework to build Generative AI applications. Get an introduction to Streamlit, which has become the de facto platform to easily prototype and deploy web-based data and Generative AI applications. Use vector stores like Knowledge Bases for Amazon Bedrock and Amazon Kendra to index documents and websites. Step through building a conversational chatbot and implementing a variety of application enhancements.
The course uses Python for development, and when you finish this course, you will be able to build and deploy Generative AI applications using Amazon Bedrock, using the tools you learn here.
Exercise Files on GitHub
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Building Applications Using Amazon Bedrock
