Spin Up Weaviate

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Spin Up Weaviate

This course is part of Chroma, Weaviate & Production RAG Deployment Specialization

Instructor: LearningMate

Included with

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3 modules

Gain insight into a topic and learn the fundamentals.

Intermediate level

Recommended experience

2 hours to complete

Flexible schedule

Learn at your own pace

3 modules

Gain insight into a topic and learn the fundamentals.

Intermediate level

Recommended experience

2 hours to complete

Flexible schedule

Learn at your own pace

What you'll learn

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

Skills you'll gain

Tools you'll learn

Details to know

Shareable certificate

Add to your LinkedIn profile

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This course is part of the Chroma, Weaviate & Production RAG Deployment Specialization

When you enroll in this course, you'll also be enrolled in this Specialization.

Learn new concepts from industry experts
Gain a foundational understanding of a subject or tool
Develop job-relevant skills with hands-on projects
Earn a shareable career certificate

There are 3 modules in this course

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.

What's included

1 video1 reading2 assignments

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.

What's included

2 videos1 reading2 assignments

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.

What's included

2 videos1 reading2 assignments

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Instructor

LearningMate

210 Courses 11,134 learners

Offered by

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Frequently asked questions

To access the course materials, assignments and to earn a Certificate, you will need to purchase the Certificate experience when you enroll in a course. You can try a Free Trial instead, or apply for Financial Aid. The course may offer 'Full Course, No Certificate' instead. This option lets you see all course materials, submit required assessments, and get a final grade. This also means that you will not be able to purchase a Certificate experience.

When you enroll in the course, you get access to all of the courses in the Specialization, and you earn a certificate when you complete the work. Your electronic Certificate will be added to your Accomplishments page - from there, you can print your Certificate or add it to your LinkedIn profile.

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