Course Outline
Introduction to the following concepts for government applications:
- vector mathematics
- AI vector embedding methodologies
- prominent AI embedding models for official use
- semantic search capabilities
- distance metric calculations
Overview of vector indexing strategies applicable to public sector data systems:
- IVFFlat indexing architecture
- HNSW indexing architecture
Implementation of the PgVector extension for PostgreSQL in government environments:
- installation protocols
- storage and retrieval of high-dimensional vectors
- application of distance measures
- deployment of vector indexes
Course Outcome: Upon completion, participants will possess a comprehensive understanding of advanced PostgreSQL extensions for government systems. They will acquire practical proficiency in integrating large language models (LLMs) and vector search technologies into secure, real-world public sector applications.
Requirements
Foundational proficiency in SQL and basic practical experience with PostgreSQL
Lab Environment: Dedicated desktop workstations configured with Linux virtual machines (supplied by NobleProg)
Target Audience: Database application developers, system architects, and data analysts involved in government projects
Testimonials (3)
Tables indexes and qq reperforming & tuning in order to improve them
Roberto Esposito
Course - PostgreSQL AI for Developers
A good first contact with a new database technology
Cont Florian - Banca Transilvania Cluj
Course - PostgreSQL Server Administration
Tuning strategies.