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.
