Udemy.Building.Multi.Agentic.Workflows.on.AWS.Bedrock.BOOKWARE-BLZiSO

Section

Appz

Group

BLZiSO

Size

7,61 GB

Files

35

Date

2026-11-08

NFO

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    ███▌     ▀▓▓▄▄▀   ▐█▓▓ ██▓▌    ▀   .;.BLiZZaRD.;.   ░     ▐█▓▓      ░    ▀ 
     ▀██▄▄▄▄▄▄▄▄▄▄▄▄▄▄███▀  ▀██▄▄▀ ░ .prouldy presents. ▄  ▀▄▄██▀ ▌   ▄ ▓    ▐█
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            █ Building Multi Agentic Workflows on       █            ▀▀███▀▀
            █ AWS Bedrock                               █            ▀▀███▀▀
          ▀▀█▀█▀▀                                  ▀▀▀▀▀█▀▀ ▀           █
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           ▀█ release date.: 08/11/26  disks........: 01                ▓
            █ supplier.....: Bill      os...........: Win               █
            ▓ cracker......: Bill      protection...: Bill            ▄ █
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       ▀▄▄▄   ▄▄█▓   ▀  .;Program info;.  ░                          ▀ 
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	You'll build a fully operational travel planner where Supervisor Agents
	coordinate tasks while Collaborator and Helper Agents handle database
	lookups, API calls, and travel preferences on your behalf. You'll
	also build a personal assistant agent with live web search powered
	by DuckDuckGo ù capable of fetching real-time information and
	responding with up-to-date answers.
	What You'll Learn:
	- Multi-Agent Design ù When to break tasks into specialized agents, how
	  to handle inter-agent communication, and how to ensure seamless collaboration
	- AWS Bedrock LLMs ù Customize prompt templates, override parameters, and
	  optimize AI output using foundation models
	- Serverless Deployment ù Store data in S3, build with Lambda Action Groups,
	  and deploy via API Gateway for live, scalable requests
	- AgentCore Runtime ù What Amazon Bedrock AgentCore is and how to deploy
	  and run agents at scale on purpose-built infrastructure
	- Web Search Agents ù Build agents using the Strands framework with Claude
	  Haiku that search the web in real time via DuckDuckGo
	- Short-Term Memory ù Track conversation context within a session using
	  AgentCore's get_last_k_turns
	- Long-Term Memory ù Configure extraction strategies that automatically
	  capture Semantic facts, User Preferences, and Session Summaries ù so
	  your agents remember users across sessions
	- Understanding the AWS agent harness and runtime architecture
	- Swarm-based agent collaboration
	- Graph-based workflows
	- Agents as Tools
	- Agent-to-Agent communication
	https://www.udemy.com/course/building-multi-agentic-ai-workflows-on-aws-bedrock/
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            █    we wish them the best in real life and thank them for  █
            █    for all their great work they have done for blizzard...█
            █    we'll never forget you!! our fallen heroes:            █
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                         if we need you then we will contact you!       █
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        Software worth using is worth buying.. keep this in mind!       █
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       ▀▄▄▄   ▄▄█▓   ▀ .; Artwork updated 31.01.2005 ░               ▀    
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