Course Outline

Introduction to AI-Augmented SQL for Government

  • Overview of AI integration in data systems for government operations
  • Evolution from traditional SQL to AI-assisted querying in public sector environments
  • Key enterprise use cases and benefits for government agencies

Understanding LLMs in the SQL Context for Government

  • How LLMs interpret and generate structured queries for government data systems
  • Comparison of GPT, LlaMA, DeepSeek, Qwen, and Mistral for SQL applications in public sector operations
  • Fine-tuning models for database interaction in government environments

Natural Language to SQL (NL2SQL) Systems for Government

  • Architectures and approaches for NL2SQL tailored for government data management
  • Building and deploying text-to-SQL pipelines in public sector applications
  • Evaluating query accuracy and user intent in government systems

AI-Assisted Query Optimization for Government

  • Using AI to detect and correct inefficient queries in government databases
  • LLM-based query rewriting for performance enhancement in public sector operations
  • Integrating AI optimization into PostgreSQL and SQL Server for government use

Security, Governance, and Auditability for Government

  • Controlling access to AI-generated queries in government systems
  • Ensuring explainability and compliance with regulatory requirements for government data
  • Implementing AI governance in enterprise data systems for government agencies

LLM Integration and Orchestration for Government

  • Connecting SQL engines with AI APIs in government environments
  • Using frameworks such as LangChain and LlamaIndex for government applications
  • Deploying AI components in hybrid and cloud architectures for government use

Practical Implementation Labs for Government

  • Setting up AI-SQL connections and test environments for government agencies
  • Creating and evaluating AI-generated queries in public sector contexts
  • Measuring performance improvements with AI optimization in government operations

Future Trends and Enterprise Adoption Strategies for Government

  • AI-native database systems and SQL evolution for government data management
  • Integration with data lakes, BI tools, and pipelines in public sector operations
  • Building internal AI query assistants for government organizations

Summary and Next Steps for Government

Requirements

  • A solid understanding of SQL fundamentals for government applications
  • Experience in database administration or data engineering roles
  • Basic knowledge of artificial intelligence and machine learning concepts

Audience

  • Data engineers and database administrators for government agencies
  • Enterprise architects and analytics leaders in the public sector
  • AI integration and platform engineering teams supporting government initiatives
 21 Hours

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