PostgreSQL AI: Introduction to semantic search Training Course
This program explores the essential PostgreSQL server extensions that enable the integration of artificial intelligence into database architectures, with a specific focus on similarity and semantic search driven by embedding vectors. Participants will develop the skills necessary to install PgVector, generate and manage vector embeddings, construct optimized vector indexes, and execute semantic search queries. Through a combination of live demonstrations and hands-on exercises, learners will solidify their understanding of these core concepts and enhance their practical application abilities.
This course is available as onsite live training in Vietnam or online live training.Course Outline
Foundations of:
- vectors
- AI vector embeddings
- leading AI embedding models
- semantic search
- distance metrics
Insights into vector indexing strategies:
- IVFFlat index
- HNSW index
The PgVector extension for PostgreSQL:
- deployment
- managing and retrieving high-dimensional vectors
- distance metrics
- utilizing vector indexes
Learning Outcomes: Upon completion, participants will have a comprehensive understanding of widely adopted AI-driven PostgreSQL extensions. They will acquire practical expertise in implementing large language models (LLMs) and vector search capabilities within real-world applications.
Requirements
Foundational proficiency in SQL and basic experience working with PostgreSQL
Lab setup: DaDesktops Linux virtual machines (supplied by NobleProg)
Target audience: database application developers, system architects, and data analysts
Open Training Courses require 5+ participants.
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Testimonials (2)
Tuning strategies.
Jeffrey Zieg - Matrix Consulting
Course - PostgreSQL Performance Tuning
Logging behaviour when the instance is under stress, and the hierarchy/nomenclature of instances, databases, files, etc.
Daniel Inwood - Sinara Consultants LTD
Course - PostgreSQL Advanced DBA
Provisional Upcoming Courses (Require 5+ participants)
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