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 Duration 21 hours

Course Outline

Introduction to AI-Augmented SQL

  • Overview of AI integration within data systems
  • The evolution from traditional SQL to AI-assisted querying
  • Key enterprise use cases and associated benefits

Understanding LLMs in SQL Context

  • How LLMs interpret and generate structured queries
  • Comparative analysis of GPT, LlaMA, DeepSeek, Qwen, and Mistral for SQL applications
  • Fine-tuning models for effective database interaction

Natural Language to SQL (NL2SQL) Systems

  • Architectures and methodologies for NL2SQL
  • Building and deploying text-to-SQL pipelines
  • Evaluating query accuracy and aligning with user intent

AI-Assisted Query Optimization

  • Utilizing AI to identify and correct inefficient queries
  • LLM-based query rewriting for enhanced performance
  • Integrating AI optimization into PostgreSQL and SQL Server

Security, Governance, and Auditability

  • Controlling access permissions for AI-generated queries
  • Ensuring explainability and regulatory compliance
  • Implementing AI governance frameworks in enterprise data systems

LLM Integration and Orchestration

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

Practical Implementation Labs

  • Setting up AI-SQL connections and test environments
  • Creating and evaluating the output of AI-generated queries
  • Measuring performance improvements through AI optimization

Future Trends and Enterprise Adoption Strategies

  • AI-native database systems and the evolution of SQL
  • Integration with data lakes, BI tools, and data pipelines
  • Building internal AI query assistants for organizations

Requirements

  • A solid understanding of SQL fundamentals
  • Practical experience with database administration or data engineering
  • Basic knowledge of AI or machine learning concepts

Audience

  • Data engineers and database administrators
  • Enterprise architects and analytics leads
  • AI integration and platform engineering teams

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