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Duration 21 hours
Course Outline
Introduction to AI-Augmented SQL
- Overview of AI integration strategies in data systems
- The transition from traditional SQL to AI-assisted querying
- Key enterprise use cases and associated benefits
Understanding LLMs in a SQL Context
- Mechanisms for how LLMs interpret and generate structured queries
- Comparative analysis of GPT, LlaMA, DeepSeek, Qwen, and Mistral for SQL applications
- Techniques for fine-tuning models for database interaction
Natural Language to SQL (NL2SQL) Systems
- Architectures and methodologies for NL2SQL implementation
- Development and deployment of text-to-SQL pipelines
- Strategies for evaluating query accuracy and user intent
AI-Assisted Query Optimization
- Leveraging AI to identify and remediate inefficient queries
- Utilizing LLM-based query rewriting to enhance performance
- Integrating AI optimization features into PostgreSQL and SQL Server
Security, Governance, and Auditability
- Regulating access to AI-generated queries
- Maintaining explainability and ensuring regulatory compliance
- Implementing robust AI governance frameworks in enterprise data systems
LLM Integration and Orchestration
- Establishing connections between SQL engines and AI APIs
- Leveraging frameworks such as LangChain and LlamaIndex
- Deploying AI components across hybrid and cloud architectures
Practical Implementation Labs
- Configuring AI-SQL connections and establishing test environments
- Generation and evaluation of AI-created queries
- Assessing performance gains through AI optimization
Future Trends and Enterprise Adoption Strategies
- The rise of AI-native database systems and the evolution of SQL
- Synergy with data lakes, BI tools, and data pipelines
- Developing internal AI query assistants for organizational use
Requirements
- A solid grasp of SQL fundamentals
- Professional experience in database administration or data engineering
- Familiarity with core AI and machine learning concepts
Target Audience
- Data engineers and database administrators
- Enterprise architects and analytics leads
- Teams specializing in AI integration and platform engineering
