План на курса

Enterprise AI Fundamentals for PostgreSQL

  • Positioning PostgreSQL in modern AI infrastructure
  • AI model lifecycle and data pipeline architecture
  • Integrating AI with enterprise data strategy

Deploying PostgreSQL for AI Workloads

  • Installing PostgreSQL and required AI extensions
  • Configuring pgvector and AI processing plugins
  • Optimizing PostgreSQL for embedding and inference performance

AI Integration Strategies

  • Connecting PostgreSQL with Deepseek, Qwen, Mistral Small, and OpenAI
  • Building RESTful APIs for AI-PostgreSQL interaction
  • Embedding LLM-driven analytics directly in SQL queries

Vector Databases and Semantic Intelligence

  • Understanding embeddings and vector similarity search
  • Implementing pgvector for semantic retrieval
  • Integrating PostgreSQL with hybrid vector databases

Performance Tuning and Optimization

  • High-performance indexing and caching for AI-driven queries
  • Parallel query execution and workload partitioning
  • Scaling PostgreSQL horizontally in AI applications

Security, Compliance, and Governance

  • Data lineage and model transparency in PostgreSQL
  • Access control and audit logging for AI data
  • Compliance with GDPR, SOC 2, and ISO 27001 standards

Automation and Monitoring

  • Using AI for database monitoring and anomaly detection
  • Automating SQL query generation and optimization with LLMs
  • Integrating PostgreSQL logs with AI-powered observability platforms

Enterprise Case Studies and Future Roadmap

  • Enterprise-scale deployments of AI with PostgreSQL
  • Cost-performance optimization in production environments
  • Emerging trends in AI-native relational databases

Summary and Next Steps

Изисквания

  • An understanding of relational database systems and SQL
  • Experience with PostgreSQL administration and development
  • Familiarity with AI/ML models and data processing workflows

Audience

  • Enterprise data architects integrating AI with PostgreSQL
  • Engineering leads responsible for AI-driven database systems
  • Database administrators managing secure AI-enabled environments
 21 часа

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