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Autor Tópico: Amazon Bedrock Ai Agents - Masterclass  (Lida 191 vezes)

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Amazon Bedrock Ai Agents - Masterclass
« em: 13 de Maio de 2025, 09:59 »


Published 5/2025
MP4 | Video: h264, 1920x1080 | Audio: AAC, 44.1 KHz
Language: English | Size: 1.18 GB | Duration: 2h 0m

Build Intelligent AI Agents with Amazon Bedrock - Step-by-Step Guide to Tools, Lambdas, Function Calling, and Deployment


What you'll learn
Hands-on walkthroughs using the AWS Bedrock Console and APIs
Integration with Knowledge Bases, tools, and external APIs
Deploy a full Agentic Workflow and expose to a Client App
Amazon Bedrock Agents best practices
Requirements
AWS Services Fundamentals
Have an AWS Account
Programming Fundamentals
Description
Unlock the full potential of Amazon Bedrock Agents and learn how to build scalable, intelligent AI-powered applications-from concept to production.This course is a hands-on, practical guide for developers, architects, and technical product managers looking to integrate advanced orchestration capabilities into their applications using Amazon Bedrock's Agent framework.What You'll Learn:What Amazon Bedrock Agents are and why they're changing how we build intelligent applications.How to set up Bedrock Agents using both the AWS Console and the full API.How to decompose user queries into steps, use Knowledge Bases (KBs), invoke actions, and manage dynamic flows using Agents.Full walkthrough of the Bedrock Agent API-including invoking Agents from client applications like Streamlit.Deep dive into multi-agent orchestration, advanced use cases, and best practices.Final capstone project: Build and deploy a production-ready enterprise chatbot that integrates documents, databases, and APIs.Advanced integration with Lambda, guardrails, traces, and action groups.Gain the skills to automate business workflows, build internal tools, and power customer-facing apps with dynamic, AI-driven capabilities.Tools & Technologies Covered:Amazon Bedrock (Agents, KBs, API)AWS Lambda, SAM, and Serverless deploymentStreamlit for frontend integrationAPI-first development with Bedrock AgentsEnterprise-level orchestration patternsThis Course Includes:Hands-on walkthroughs using the AWS Bedrock Console and APIsReal code examples from AWS Labs and AWS serverless blogsIntegration with Knowledge Bases, tools, and external APIsComplete source code and templates to build your own AI workflows
Overview
Section 1: Introduction
Lecture 1 Introduction
Lecture 2 Course Structure
Lecture 3 AWS Account Knowledge - Pre-reqs
Section 2: Source Code and Resources
Lecture 4 Source Code and Resources
Section 3: Amazon Bedrock Deep Dive
Lecture 5 Amazon Bedrock Deep Dive - What is It and Benefits
Lecture 6 Amazon Bedrock Key Features and Security Privacy and Safety
Lecture 7 Amazon Bedrock Pricing
Lecture 8 Hands-on: Amazon Bedrock Console Walkthrough - Playground
Lecture 9 Hands-on - Generate Images
Section 4: Amazon Bedrock AI Agents - Deep Dive
Lecture 10 Amazon Bedrock Agent Deep Dive - Basic Workflow
Lecture 11 Detailed Flow of Bedrock Agent - Full Overview
Lecture 12 Hands-on: Build our First Amazon Bedrock Agent - Simple Agent
Lecture 13 Hands-on: Adding Knowledge Base and Testing It
Lecture 14 Hands-on: Action Groups - Adding a Lambda Function
Lecture 15 Amazon Bedrock Agent and Action Groups - Architectural Overview
Lecture 16 Amazon Bedrock Agent Architectural Overview and Animation
Lecture 17 Build-time vs Runtime Operations - Overview
Lecture 18 Amazon Bedrock Agents - Creation Process & Benefits
Section 5: Capstone Project - Web Scraper Agent - Full Workflow
Lecture 19 Hands-on: Scraper Agent - Console Setup
Lecture 20 Hands-on: Create an Agent Alias - Agent Deployment
Lecture 21 Final - Scraper Agent Frontend Client
Section 6: Wrapup
Lecture 22 Congratulations
Developers and software engineers looking to integrate LLM-based agents into real apps,Solution architects building AI orchestration systems on AWS,Anyone curious about building intelligent tools using generative AI, function calling, and multi-agent systems
Screenshots


Download link

rapidgator.net:
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