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 Duration 21 hours

Course Outline

Enterprise AI Fundamentals for PostgreSQL

  • Positioning PostgreSQL within modern AI infrastructure.
  • The AI model lifecycle and data pipeline architecture.
  • Aligning AI integration with enterprise data strategies.

Deploying PostgreSQL for AI Workloads

  • Installing PostgreSQL and the requisite 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.
  • Developing RESTful APIs for interaction between AI and PostgreSQL.
  • Incorporating LLM-driven analytics directly into SQL queries.

Vector Databases and Semantic Intelligence

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

Performance Tuning and Optimisation

  • Implementing high-performance indexing and caching for AI-driven queries.
  • Managing parallel query execution and workload partitioning.
  • Scaling PostgreSQL horizontally for AI applications.

Security, Compliance, and Governance

  • Ensuring data lineage and model transparency in PostgreSQL.
  • Managing access control and audit logging for AI data.
  • Maintaining compliance with GDPR, SOC 2, and ISO 27001 standards.

Automation and Monitoring

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

Enterprise Case Studies and Future Roadmap

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

Summary and Next Steps

Requirements

  • A solid 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.

Custom Corporate Training

Training solutions designed exclusively for businesses.

  • Customised Content: We adapt the syllabus and practical exercises to the real goals and needs of your project.
  • Flexible Schedule: Dates and times adapted to your team's agenda.
  • Format: Online (live), In-company (at your offices), or Hybrid.
Investment

Price per private group, online live training, starting from £4800 + VAT*

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