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Build Real world End-to-End AI Agents using AWS Bedrock · LearnSpace
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courseraПрограммирование

Build Real world End-to-End AI Agents using AWS Bedrock

Курс от Packt
Средний≈ 11.6 чАнглийский
О курсеНавыкиПрограммаПреподаватели

О курсе

This course features Coursera Coach! A smarter way to learn with interactive, real-time conversations that help you test your knowledge, challenge assumptions, and deepen your understanding as you progress through the course. You will learn to build advanced AI agents using AWS Bedrock, a platform for creating generative AI applications. The course introduces key concepts like Retrieval-Augmented Generation (RAG) and function orchestration to enhance AI models with external data. As you progress, you'll gain hands-on experience deploying chatbots, creating knowledge bases, and integrating AWS services like Lambda and DynamoDB.. Throughout the course, you’ll dive deeper into working with multi-agent systems and their applications in real-world scenarios like product inventory management and mortgage processing. By the end, you'll have the skills to build fully functional, scalable AI agents that can interact with complex data sources. This course is perfect for developers with some Python and cloud experience. Knowledge of basic cloud computing concepts is helpful, but no prior experience with AWS Bedrock is required. Ideal for those aiming to create sophisticated AI solutions.

Навыки, которые вы освоите

AI WorkflowsAI OrchestrationRetrieval-Augmented GenerationCloud DeploymentTool CallingAgentic WorkflowsVector DatabasesModel Deployment

Программа курса

10 модулей · 70 учебных материалов

01Course Introduction & Background4 материалов

Course Introduction & Background

IntroductionВидеоFull Course ResourcesЧтениеEmerging AI Roles in the IndustryВидеоCourse Prerequisites - Must WatchВидео
02Fundamental Concepts in LLM-Driven Apps & AI

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Packt - Course Instructors

Преподаватель курса

Build Real world End-to-End AI Agents using AWS Bedrock
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Обучение откроется на Coursera
в новой вкладке

Обучение на Coursera

≈ 11.6 ч

10 модулей

Язык: Английский

Часть программы вашего университета
5 материалов

Fundamental Concepts in LLM-Driven Apps & AI

Overview of RAG ArchitectureВидеоIntroduction to Function Calling and OrchestrationВидеоWhat is Agentic AI?ВидеоUnderstanding Retrieval Augmented Generation and AI AgentsDIALOGUEFundamental Concepts in LLM-Driven Apps & AI - AssessmentЗадание
03Dependent Software Installation4 материалов

Dependent Software Installation

Tools & Frameworks to be InstalledВидеоLab - Install Docker and AWS CLIВидеоUnderstanding Software and Tool Setup for Cloud DevelopmentDIALOGUEDependent Software Installation - AssessmentЗадание
04Introduction to AWS Bedrock8 материалов

Introduction to AWS Bedrock

Overview of AWS BedrockВидеоLab - Bedrock Console WalkthroughВидеоLab - Getting Started with Python/Boto3 for BedrockВидеоLab - Deploy Streamlit Chatbot as Docker Container to AWS ECSВидеоLab - Invoke Bedrock's MultiModal LLMs Using Python/Boto3 LibraryВидеоAssignment - Deploy Image Generation using Stable Diffusion to AWS ECSВидеоUnderstanding AWS Bedrock and LLMsDIALOGUEIntroduction to AWS Bedrock - AssessmentЗадание
05Working with Bedrock KnowledgeBase as Vector Store9 материалов

Working with Bedrock KnowledgeBase as Vector Store

Overview of AWS Bedrock KnowledgeBaseВидеоLab - Create Your First KnowledgeBase for Q&AВидеоLab - Test Your KnowledgeBase Using Web ConsoleВидеоLab - Invoke KnowledgeBase with Python SDK & Lambda Functions Using API GatewayВидеоAssignment - Setup Electric Vehicle Infrastructure KnowledgeBaseВидеоAssignment Solution - Part 1 | Deploy Lambda Functions with API GatewayВидеоAssignment Solution - Part 2 | Deploy Chatbot to AWS ECSВидеоBuilding and Grounding an LLM-based Knowledge Base ChatbotDIALOGUEWorking with Bedrock KnowledgeBase as Vector Store - AssessmentЗадание
06Getting Started with Bedrock Agents8 материалов

Getting Started with Bedrock Agents

Overview of Bedrock AgentsВидеоUse-Case Overview - Product Inventory Assistant for ECommerce PlatformsВидеоLab - Setup DynamoDB and Bedrock KnowledgeBase as Data SourcesВидеоLab - Deploy & Test Lambda Functions to Access DynamoDBВидеоLab - Deploy Bedrock Agent - Full ImplementationВидеоLab - Invoke Agents Using Python/Boto3 SDKВидеоBuilding and Testing a Bedrock Agent with AWS Lambda and Knowledge Base IntegrationDIALOGUEGetting Started with Bedrock Agents - AssessmentЗадание
07Introduction to Multi-Agent Collaboration Using Bedrock9 материалов

Introduction to Multi-Agent Collaboration Using Bedrock

Introduction to Multi-Agent CollaborationВидеоOverview of Mortgage Assistant LabВидеоLab - Setup First Sub-Agent Part-1ВидеоLab - Setup First Sub-Agent Part-2ВидеоLab - Setup Your Second Sub-AgentВидеоLab - Setup Supervisor AgentВидеоLab - Deploy a Mortgage Assistant Chatbot to AWS ECSВидеоBuilding and Testing a Multi-Agent Mortgage Support SystemDIALOGUEIntroduction to Multi-Agent Collaboration Using Bedrock - AssessmentЗадание
08Lab - Develop Hotel Booking Assistant with AWS Bedrock, Dynamo & Lambda Functions5 материалов

Lab - Develop Hotel Booking Assistant with AWS Bedrock, Dynamo & Lambda Functions

Introduction to the Use-CaseВидеоLab - Deploy Hotel Booking Assistant Lambda FunctionsВидеоLab - Full Deployment of Hotel Booking Assistant Using AWS ECSВидеоWorking with Multiple Lambda Functions in an AWS Bedrock AgentDIALOGUELab - Develop Hotel Booking Assistant with AWS Bedrock, Dynamo & Lambda Functions - AssessmentЗадание
09Redshift as a KnowledgeBase for Structured Data8 материалов

Redshift as a KnowledgeBase for Structured Data

Introduction to Structured Data Source for KnowledgeBaseВидеоLab - Setup Redshift Serverless for Rental Apartment ListingsВидеоLab - Setup KnowledgeBase with Redshift Data SourceВидеоLab - Setup Rental Assistant Agents Using BedrockВидеоRemember This Before Using Redshift with Bedrock KnowledgeBaseВидеоLab - Assignment | Deploy Lambda Functions to Query Redshift for Bedrock AgentsВидеоUsing Redshift as a Structured Data Source for AWS Bedrock AgentsDIALOGUERedshift as a KnowledgeBase for Structured Data - AssessmentЗадание
10Workflows for Generative AI Apps Using Bedrock Flows10 материалов

Workflows for Generative AI Apps Using Bedrock Flows

Introduction to Bedrock FlowsВидеоLab - Build Your First Workflow for User Feedback for Ecommerce StoresВидеоLab - Integrate Bedrock KnowledgeBase with Flows for Reliable ResponsesВидеоIntroduction to Multi-turn ConversationsВидеоLab - Deploy Agents with Bedrock Flows | Part 1ВидеоLab - Deploy Agents with Bedrock Flows | Part 2ВидеоLab - Invoke Bedrock Flows Using Python/Boto3 SDKВидеоWorkflows for Generative AI Apps Using Bedrock Flows - AssessmentЗаданиеFull Course Practice AssessmentЗаданиеFull Course AssessmentЗадание