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所在平台: Udemy |
课程主页: https://www.udemy.com/course/salesforce-agentforce-real-time-project-implementation/
课程评论：没有评论
课程名称：Salesforce Agentforce 实时项目实施 课程概述： 欢迎参加Salesforce Agentforce实时项目实施课程。本课程旨在通过引导您完成实际项目，帮助您在真实场景中构建AI代理。随着Agentforce需求的迅速增长，许多Salesforce专业人士仍缺乏实践经验。本课程将填补这一空白，使您在构建实时AI代理时更具信心，无论您是第一次学习Agentforce，还是为客户构建POC（概念验证），本课程均提供必要的实践经验，帮助您自信地与Agentforce打交道。 您将在课程中从零开始构建以下项目： 1. Roomie代理 - 在此项目中，您将构建第一个AI代理——Roomie，这是一款服务于豪华酒店网站的虚拟助理。此项目适合初学者，介绍Agentforce的基础概念。 - 您将学习如何： - 创建第一个Agentforce AI代理 - 定义可重用的操作以支持特定任务（如房间服务和点餐） - 训练代理以提出合适的问题 - 利用上下文提供个性化和准确的回应 - 将代理与客户面向的体验云网站集成，任何酒店客人均可无登录访问 - Roomie旨在协助酒店客人，具体功能包括： - 帮助客户入驻 - 辅助点餐 - 处理房间服务请求 - 在结账过程中支持用户 - 课程结束时，您将构建一个完全面能的AI助理，模拟真实的酒店行业用例，奠定日后更高级项目的基础。 2. 临床研究代理（前端）与入组后代理（后端） - 在此项目中，您将向更高级的AI代理迈出一大步，构建临床研究代理。该代理针对医疗和研究行业，能够回答患者关于临床研究、试验资格和公司特定研究的详细问题。 - 您将学习如何： - 利用Agentforce数据库让您的代理回答用户的问题 - 使用知识提示模板、Apex、Flows和API构建复杂代理操作 - 通过给予代理对非结构化业务数据的访问，实现更少编码和记录创建的业务使用案例 - 在与客户对话前共享上下文变量，以便全面了解每个细节 - 利用多个代理分配任务，前端代理与客户交流，后端代理执行分析和操作 - 此代理使用Salesforce Einstein AI和Agentforce的多项功能，包括： - Agentforce与AI代理 - 数据云与RAG - Agentforce数据库 - 提示构建器 - 上下文变量 - 使用Apex、Flows、API构建复杂操作 - 通过记录触发的Flows调用代理 - 课程结束时，您将能够为医疗和研究等关键高影响行业构建生产级AI代理。 请注意：课程中讲解的代码和提示模板将在相应课程中提供。
Welcome to the Salesforce Agentforce Real-Time Project Implementation Course, where you'll learn to build AI agents in real-world scenarios.The demand for Agentforce is growing rapidly, yet many Salesforce professionals still lack hands-on experience. This course is designed to bridge that gap by guiding you through practical projects that help you build real-time AI agents with confidence.Whether you're learning Agentforce for the first time or building a POC for your clients, this course offers hands-on experience and the confidence you need to work effectively with Agentforce. you will build Projects that you can confidently explain in an Interview , You're encouraged to share them with recruiters and hiring managers.in this course, we'll build real time projects from scratch:1. Roomie Agent In this project, we'll begin by building our very first AI Agent - Roomie, a virtual assistant for a luxury hotel website. This is a beginner-friendly project that introduces you to the foundational concepts of Agentforce.You'll learn how to:Create your first Agentforce AI AgentDefine reusable actions that power specific tasks like room service and food orderingTrain the agent to ask the right questions at the right timeLeverage context to offer personalized and accurate responsesIntegrate the agent with a customer-facing Experience Cloud site, accessible to any hotel guest - no login requiredRoomie is designed to assist hotel guests throughout their stay. It can:Help onboard new customersAssist with food order placementHandle room service requestsSupport users during the checkout processYou'll also get hands-on with:Defining Topics that translate into real agent capabilitiesAdding instructions and actions that guide the agent in performing tasksBuilding custom actions using Flows and ApexCreating dependent actions, where the output of one action feeds into the nextBy the end of this section, you'll have built a fully functional AI assistant that simulates a real-world hospitality use case - laying a strong foundation for more advanced projects ahead.2. Clinical Research Agent (Frontend) And Post Enrollment Agent (Backend)In this project, we'll take a major leap and build a much more advanced AI agent - the Clinical Research Agent. This agent is designed for the healthcare and research industry, capable of answering detailed patient queries around clinical research, trial eligibility, and company-specific studies.You'll learn how to:Equip your Agent to Answer User's question by utilizing Agentforce Data libraryBuild Complex Agent Actions using Knowladge Prompt templates, Apex , Flows and API'sSolve business Use case with Less code and Less Record Creation by giving Agent Access to Unstructured Business Data and Train it to take intelligent Actions.Work With Context Variable to get all the Share all the details with Agent before the Conversation starts with CustomerWork with Multiple Agents to divide the Task Among them, the Front end agent to talk with Customer and Backend agent to perform backend Analysis and ExecutionThis agent uses several features of Salesforce Einstein AI and Agentforce, including:Agentforce & AI AgentsData Cloud and RAGAgentforce Data LibraryPrompt BuilderContext VariableComplex Actions using Apex ,flow , APIInvoking Agent with Record Triggered flowsBy the end of this section, you'll be capable of building production-grade AI agents for critical, high-impact industries like healthcare and researchNote:Code and Prompt Templates Built in Lectures will be provided in the Respective lectures.
