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Model Data in Weaviate

本课程是 Chroma, Weaviate & Production RAG Deployment 专项课程的一部分

位教师：LearningMate

包含在中

了解更多

2个模块

深入了解一个主题并学习基础知识。

中级等级

推荐体验

2 小时完成

灵活的计划

自行安排学习进度

2个模块

深入了解一个主题并学习基础知识。

中级等级

推荐体验

2 小时完成

灵活的计划

自行安排学习进度

您将学到什么

Design, implement, and evaluate a Weaviate vector schema to model complex data relationships and optimize query performance.

您将获得的技能

您将学习的工具

要了解的详细信息

可分享的证书

添加到您的领英档案

了解顶级公司的员工如何掌握热门技能

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Petrobras, TATA, Danone, Capgemini, P&G 和 L'Oreal 的徽标

积累特定领域的专业知识

本课程是 Chroma, Weaviate & Production RAG Deployment 专项课程专项课程的一部分

在注册此课程时，您还会同时注册此专项课程。

向行业专家学习新概念
获得对主题或工具的基础理解
通过实践项目培养工作相关技能
获得可共享的职业证书

该课程共有2个模块

Model Data in Weaviate is an intermediate, project-based course for developers and data professionals who want to unlock the full potential of vector search. In modern AI applications, search speed and relevance are everything, and they both begin with a powerful data model. This course teaches you the principles of designing a sophisticated, high-performance schema, moving beyond flat data structures to build a connected graph of information.

You will learn to model complex relationships using multi-class schemas and relational links. Through a hands-on project using Weaviate as our implementation tool, you will design a schema for a real-world dataset, import interconnected data objects, and, most importantly, learn how to benchmark your design choices. The course culminates in an evaluation where you will use query latency data to prove the performance gains of your schema. You’ll leave with not just a working project, but also a repeatable methodology for optimizing data architecture in any advanced search application.

单元详情

Good performance starts with good design. In this module, you will learn why a well-planned data model is the backbone of any scalable vector application. You'll go from foundational principles to hands-on implementation, creating a complete, multi-class schema with relational links in Weaviate.

涵盖的内容

2个视频1篇阅读材料1个作业1个非评分实验室

A schema isn't complete until you've proven its worth. In this final module, you will learn the professional skill of quantitative evaluation. You will benchmark your schema's query latency and analyze the results to justify why a relational model is superior for complex queries.