Course Outline

Introduction to AI in Postgres for Government

  • Overview of AI and data-driven systems for government operations
  • AI use cases within Postgres environments for government agencies
  • Architecture considerations for AI workloads in the public sector

Setting Up the Environment for Government Use

  • Installing PostgreSQL and configuring pgvector for government systems
  • Setting up Python for AI integrations within government networks
  • Connecting Postgres to local and cloud-based LLMs for government applications

AI Extensions and Vector Databases for Government

  • Understanding vector embeddings in Postgres for government data
  • Using pgvector for similarity search and semantic queries in government databases
  • Benchmarking AI extensions versus external vector stores for government use cases

Integrating LLMs with Postgres for Government

  • Connecting Postgres with OpenAI, Deepseek, Qwen, and Mistral Small for government applications
  • Designing AI query pipelines for government data processing
  • Storing and retrieving embeddings efficiently in government databases

Building Intelligent Query Systems for Government

  • Natural language to SQL using LLMs for government queries
  • Automating query generation and optimization for government datasets
  • AI-assisted database search and summarization for government reports

Optimizing Postgres for AI Workloads in Government

  • Indexing strategies for embeddings in government databases
  • Performance tuning and caching for AI queries in government systems
  • Scaling Postgres with distributed and cloud architectures for government operations

Security and Governance in AI-Enabled Databases for Government

  • Data privacy and compliance considerations for government agencies
  • Managing API keys and access control in government environments
  • Auditing AI interactions and query logs for government accountability

Case Studies and Enterprise Use Cases for Government

  • AI-powered recommendation systems with Postgres for government services
  • Enterprise search and analytics with embeddings in government data
  • Automation and predictive modeling within Postgres for government operations

Summary and Next Steps for Government Implementation

Requirements

  • An understanding of SQL and relational database concepts for government use.
  • Experience with Postgres administration or development in a public sector environment.
  • Basic familiarity with AI and machine learning principles to enhance data management.

Audience

  • Database administrators who wish to integrate AI into Postgres for government operations.
  • Data engineers building AI-powered database pipelines for government systems.
  • Developers and architects designing intelligent data-driven applications for government use.
 21 Hours

Number of participants


Price per participant

Upcoming Courses

Related Categories