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所在平台: Udemy |
课程主页: https://www.udemy.com/course/retrieval-augmented-generation-rag-fine-tuning-explained/
课程评论：没有评论
课程名称：检索增强生成 - RAG微调解析 课程概述： 本课程旨在帮助学员掌握检索增强生成（RAG）与微调技术，构建更智能、准确且基于真实数据的AI系统。学员将了解大型语言模型（LLMs）如何改变企业运营，减少错误生成，提升准确性，并针对企业需求个性化输出。通过学习RAG，学员将掌握如何将AI与实时数据源连接，使其能够检索并生成准确、最新的响应。而微调则确保你的AI能够使用特定行业术语、工作流程或品牌语调进行交流。RAG与微调的结合，使大型语言模型不仅具备功能性，更成为商业中不可或缺的工具。 课程将通过现实案例与实践洞见，展示企业如何利用这些技术构建下一代AI工具。课程结束时，学员将具备设计能够提高效率、客户满意度及创新能力的AI系统的知识。 课程内容： - 实施RAG，将大型语言模型与实时、领域特定的数据对接。 - 微调大型语言模型，以定制其在企业应用中的行为。 - 理解嵌入、知识图谱及其在优化AI输出中的重要性。 - 部署集成检索、增强与生成的AI工作流程，以获取准确、可操作的响应。 - 精通RAFT（检索增强微调），构建既强大又精确的AI模型。 为什么选择本课程： - 掌握前沿的RAG、微调和LLM优化技能。 - 通过实际案例学习企业AI部署中的情境。 - 无需高级编程知识，概念以清晰易懂的方式呈现。 - 适合AI开发者、数据科学家、产品经理和探索AI应用的商业领袖。 适合人群： - 希望通过RAG提升大型语言模型性能的AI开发者和工程师。 - 专注于提高AI准确性和基础的科学家。 - 探索AI驱动自动化和工作流程的商业领袖和经理。 - 有兴趣于先进AI技术及企业应用案例的学生和研究人员。
Unlock the power of Retrieval Augmented Generation (RAG) and Fine Tuning to build AI systems that are smarter, more accurate, and grounded in real-world data.In this course, you'll explore how large language models (LLMs) can transform enterprise operations-reducing hallucinations, enhancing accuracy, and personalizing outputs to fit your organization's unique needs. By mastering RAG, you'll learn to connect AI to live data sources, allowing it to retrieve and generate precise, up-to-date responses.Fine-tuning, on the other hand, ensures your AI speaks your language-whether that's adapting to industry-specific jargon, workflows, or brand voice. Together, RAG and fine-tuning make LLMs not just functional, but indispensable for business.With real-world examples and hands-on insights, this course will show you how enterprises are deploying these techniques to build next-generation AI tools. By the end, you'll have the knowledge to design AI that drives efficiency, customer satisfaction, and innovation.What You'll Learn:Implement RAG to ground LLMs in real-time, domain-specific data.Fine-tune LLMs to customize their behavior for enterprise applications.Understand embeddings, knowledge graphs, and their role in refining AI outputs.Deploy AI workflows that integrate retrieval, augmentation, and generation for accurate, actionable responses.Master RAFT (Retrieval-Augmented Fine-Tuning) to build AI models that are both powerful and precise.Why Take This Course?Gain cutting-edge skills in RAG, fine-tuning, and LLM optimization.Learn by example with practical scenarios from enterprise AI deployments.No advanced programming required - concepts are presented in a clear, accessible format.Ideal for AI developers, data scientists, product managers, and business leaders exploring AI adoption.Who This Course Is For:AI developers and engineers wanting to enhance LLM performance with RAG.Data scientists focused on improving AI accuracy and grounding.Business leaders and managers exploring AI-driven automation and workflows.Students and researchers interested in advanced AI techniques and enterprise use cases.
