Develop AI solutions with Azure Database for PostgreSQL

Overzicht

Learn how to use Azure Database for PostgreSQL as a data foundation for AI applications, including schema design, SQL queries, and Python integration.After completing this module, you'll be able to:

Explain the architecture and key features of Azure Database for PostgreSQL Establish secure connections to PostgreSQL using Microsoft Entra authentication and TLS Create and manage database schemas including tables, indexes, and constraints Write efficient SQL queries for common data operations Integrate Azure Database for PostgreSQL into applications using Python Learn how to implement vector search in Azure Database for PostgreSQL using the pgvector extension for semantic search, recommendations, and RAG pipelines.After completing this module, you'll be able to:

Store and query vector embeddings using the pgvector extension in Azure Database for PostgreSQL Execute vector similarity searches using different distance metrics and operators Create and manage vector indexes to optimize search performance Implement embedding update and refresh strategies for evolving datasets Build retrieval patterns that integrate PostgreSQL vector search with RAG pipelines Tune pgvector configuration, select vector indexes, design efficient data layouts, and scale Azure Database for PostgreSQL for high-performance AI workloads.After completing this module, you'll be able to:

Tune PostgreSQL and pgvector configuration parameters to optimize query latency and memory usage for AI workloads Select and configure the appropriate vector index type based on dataset size, query patterns, and accuracy requirements Design data layouts that optimize vector storage and metadata filtering performance Scale Azure Database for PostgreSQL to handle high-volume vector workloads Implement connection pooling and session management strategies for AI applications

Lesprogramma

• Build and query with Azure Database for PostgreSQLIntroductionExplore Azure Database for PostgreSQLConnect to PostgreSQLCreate and manage schemasQuery dataIntegrate SDKs and applicationsExercise - Build an agent tool backend on Azure Database for PostgreSQLModule assessmentSummary
• Implement vector search with Azure Database for PostgreSQLIntroductionStore and query embeddings with pgvectorPerform fast vector similarity searchManage index lifecycle and embedding updatesRun vector similarity search for semantic retrievalImplement retrieval patterns for RAG pipelinesExercise - Implement vector search on Azure Database for PostgreSQLModule assessmentSummary
• Optimize vector search in Azure Database for PostgreSQLIntroductionTune PostgreSQL for pgvectorChoose and configure vector indexesOptimize data layoutScale for high-volume workloadsConnection optimizationExercise - Optimize vector search performance in Azure Database for PostgreSQLModule assessmentSummary

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Vakgebieden

Programming