GenAI核心概念与实战框架详解

视频详细介绍了什么是GenAI了解Foundation Models、Prompt Engineering、RAG（检索增强生成）、Agents等核心技术原理及其实际应用。 在这一节课程中，你将系统学习生成式人工智能（Generative AI）的核心概念与主流实践框架，深入理解Prompt Engineering、RAG系统、LangChain应用以及多智能体Agent架构在AI工程中的落地方式。课程不仅梳理了从基础模型（Foundation Models）的构建原理，还结合企业实际应用，讲解如何将大模型能力整合进业务流程中。 会了解到以下内容： 1. 生成式AI的原理与典型应用场景 2. Prompt提示词设计策略与调试技巧 3. RAG（检索增强生成）系统的构建与部署流程 4. LangChain框架的核心模块与实战项目演练 5. 如何构建具备推理与工具调用能力的Agent系统 6. 嵌入模型（Embedding）的微调与性能评估方法 7. GenAI Ops：从开发到上线的工程化全流程 This session provides a comprehensive overview of Generative AI (GenAI), designed to help you understand and apply key technologies such as Foundation Models, Prompt Engineering, Retrieval-Augmented Generation (RAG), and Autonomous Agents in real-world engineering contexts. Through expert-led instruction and practical project demos, you'll not only grasp the theoretical underpinnings of large language models but also explore how GenAI is driving innovation across industries by integrating with business processes and applications. 🔍 In this session, you will learn: The principles and real-world use cases of Generative AI How to design, optimize, and iterate effective prompts (Prompt Engineering) How to build and deploy RAG systems from scratch using LangChain and vector databases Core components of the LangChain framework with hands-on project applications How to create intelligent agents capable of reasoning and tool invocation Techniques for fine-tuning embedding models and evaluating retrieval performance The end-to-end engineering workflow of GenAI Ops, from prototype to production.