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Course Outline

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

Requirements

  • 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 Hours

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