We’re tremendously excited to be developing a library of AI-focused courses, as well as new courses focused on traditional SQL Server topics, all based on SQL Server 2025 and Azure SQL Database. Joe Sack is back with us and he gets the honors for our first new course: AIVSE: Vector Search Essentials.
This course prepares SQL Server DBAs and developers for AI-powered semantic search. You’ll learn how to store, index, and query vector embeddings directly in SQL Server 2025, enabling natural language search, recommendation systems, and retrieval-augmented generation (RAG) patterns.
The hands-on lab database and all demo scripts are available on GitHub. Whether you’re running SQL Server locally, on a VM, or in Azure, the core concepts and query patterns you’ll learn apply across all deployment options.
You’ll learn the following:
- Semantic search fundamentals and when vector search outperforms traditional full-text
- Vector data types, embeddings, and how to generate them from text
- Distance metrics (cosine, Euclidean, dot product) and when to use each
- Approximate nearest neighbor (ANN) search with DiskANN indexes
- Hybrid query patterns combining vector similarity with traditional filters
- Production deployment strategies including performance tuning and monitoring
More information about the course is here.
It’s available for one-year and lifetime access and is on sale through the end of the year in our revamped shop. If you’re a Blackbelt Lifetime subscriber, login and use the discount code ‘bbai’ to save $100 on the sale price (it automatically checks your account email), otherwise, check the newsletter Wednesday morning for a $50 discount coupon.
Any questions, let me know.
Enjoy!