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 Duration 21 hours

Course Outline

Introduction to AI-Enhanced SQL

  • Overview of AI integration within data systems
  • The transition from conventional SQL to AI-assisted querying
  • Key enterprise applications and associated benefits

Understanding LLMs in the SQL Context

  • How LLMs parse and generate structured queries
  • Comparing GPT, LLaMA, DeepSeek, Qwen, and Mistral for SQL use cases
  • Model fine-tuning for effective database interaction

Natural Language to SQL (NL2SQL) Systems

  • Architectures and methodologies for NL2SQL
  • Developing and deploying text-to-SQL pipelines
  • Assessing query accuracy and alignment with user intent

AI-Assisted Query Optimization

  • Leveraging AI to identify and resolve inefficient queries
  • Using LLMs to rewrite queries for improved performance
  • Integrating AI optimization with PostgreSQL and SQL Server

Security, Governance, and Auditability

  • Managing access controls for AI-generated queries
  • Safeguarding explainability and regulatory compliance
  • Establishing AI governance frameworks in enterprise data systems

LLM Integration and Orchestration

  • Bridging SQL engines with AI APIs
  • Utilizing frameworks such as LangChain and LlamaIndex
  • Deploying AI components across hybrid and cloud architectures

Practical Implementation Labs

  • Configuring AI-SQL connections and testing environments
  • Generating and assessing AI-created queries
  • Quantifying performance gains through AI optimization

Future Trends and Enterprise Adoption Strategies

  • The rise of AI-native database systems and the evolution of SQL
  • Interoperability with data lakes, BI tools, and data pipelines
  • Developing internal AI query assistants for organizational use

Requirements

  • A solid grasp of SQL fundamentals
  • Background in database administration or data engineering
  • Familiarity with core AI or machine learning concepts

Target Audience

  • Data engineers and database administrators
  • Enterprise architects and analytics leads
  • Teams focused on AI integration and platform engineering

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