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 Duration 7 hours

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

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