Spin Up Weaviate

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

位教师：LearningMate

访问权限由 New York State Department of Labor 提供

3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

3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

Deploy a Weaviate vector database with Docker Compose, configure a schema, ingest data objects, and run vector search queries using its native API.

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

作业

6 任务¹

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授课语言：英语（English）

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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。

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该课程共有3个模块

Spin Up Weaviate is an intermediate, hands-on course for developers and ML engineers who need to get a modern vector database running fast. If you're ready to move from theory to practice, this course provides a direct, step-by-step path to deploying, configuring, populating, and querying Weaviate, one of the most popular open-source vector databases available today. Forget high-level concepts; this course is about execution.

You will learn how to use Docker Compose to launch a Weaviate instance locally, define a data schema using its API, and ingest data objects for semantic search. Through a series of practical and guided screencasts and a final, real-world project, you will configure a live database, load it with a dataset of 1,000 articles, and perform your first vector search query using GraphQL APIs to run similarity-based vector search queries. By the end of this 2-hour session, you will have the confidence and skill to deploy and interact with a vector database environment for your own AI applications.

This module focuses on the essential first step: setting up and running your database environment. You will learn how to use Docker Compose to launch a Weaviate instance locally, understand its configuration, and define a data schema that tells the database how to structure incoming information.

涵盖的内容

1个视频1篇阅读材料2个作业

Your database is running; now it's time to use it. This module focuses on the data lifecycle. You will learn how to use Weaviate's REST APIs to ingest data and the GraphQL API to verify retrieval using vector search queries.

涵盖的内容

2个视频1篇阅读材料2个作业

With data in your database, this final module teaches you how to get it out intelligently. You will master how to construct and refine vector search queries using GraphQL, understand how query choices affect relevance, and apply these skills to retrieve meaningful results from larger datasets.