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Duration 21 hours
Course Outline
Introduction to AI-Augmented SQL
- An 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
- Mechanisms for LLM interpretation and generation of structured queries
- Comparative analysis of GPT, LlaMA, DeepSeek, Qwen, and Mistral for SQL applications
- Techniques for fine-tuning models for optimal database interaction
Natural Language to SQL (NL2SQL) Systems
- Architectural frameworks and approaches for NL2SQL
- Processes for building and deploying text-to-SQL pipelines
- Methods for evaluating query accuracy and user intent
AI-Assisted Query Optimization
- Leveraging AI to identify and rectify inefficient queries
- LLM-based query rewriting strategies for enhanced performance
- Integrating AI optimization into PostgreSQL and SQL Server
Security, Governance, and Auditability
- Strategies for controlling access to AI-generated queries
- Ensuring explainability and regulatory compliance
- Implementing robust AI governance in enterprise data systems
LLM Integration and Orchestration
- Establishing connections between SQL engines and AI APIs
- Utilizing frameworks such as LangChain and LlamaIndex
- Deploying AI components within hybrid and cloud architectures
Practical Implementation Labs
- Configuration of AI-SQL connections and test environments
- Creation and evaluation of AI-generated queries
- Measuring performance gains through AI optimization
Future Trends and Enterprise Adoption Strategies
- The rise of AI-native database systems and the evolution of SQL
- Integration with data lakes, BI tools, and data pipelines
- Developing internal AI query assistants for organizations
Requirements
- A solid grasp of SQL fundamentals
- Practical experience in database administration or data engineering
- Foundational knowledge of AI or machine learning concepts
Target Audience
- Data engineers and database administrators
- Enterprise architects and analytics leads
- AI integration and platform engineering teams