문의를 보내주셔서 감사합니다! 팀원이 곧 연락드리겠습니다.
예약을 보내주셔서 감사합니다! 저희 팀 멤버 중 한 분이 곧 연락드리겠습니다.
코스 개요
Introduction to AI-Augmented SQL
- Overview of AI integration in data systems
- Evolution from traditional SQL to AI-assisted querying
- Key enterprise use cases and benefits
Understanding LLMs in SQL Context
- How LLMs interpret and generate structured queries
- Comparison of GPT, LlaMA, DeepSeek, Qwen, and Mistral for SQL applications
- Fine-tuning models for database interaction
Natural Language to SQL (NL2SQL) Systems
- Architectures and approaches for NL2SQL
- Building and deploying text-to-SQL pipelines
- Evaluating query accuracy and user intent
AI-Assisted Query Optimization
- Using AI to detect and correct inefficient queries
- LLM-based query rewriting for performance
- Integrating AI optimization into PostgreSQL and SQL Server
Security, Governance, and Auditability
- Controlling access to AI-generated queries
- Ensuring explainability and compliance
- Implementing AI governance in enterprise data systems
LLM Integration and Orchestration
- Connecting SQL engines with AI APIs
- Using frameworks such as LangChain and LlamaIndex
- Deploying AI components in hybrid and cloud architectures
Practical Implementation Labs
- Setting up AI-SQL connections and test environments
- Creating and evaluating AI-generated queries
- Measuring performance improvements with AI optimization
Future Trends and Enterprise Adoption Strategies
- AI-native database systems and SQL evolution
- Integration with data lakes, BI tools, and pipelines
- Building internal AI query assistants for organizations
Summary and Next Steps
요건
- An understanding of SQL fundamentals
- 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
21 시간
