By the end of this learning path, learners will be able to:

• Understand how Azure Database for PostgreSQL supports AI-powered application architectures

• Build applications using generative AI models and Azure AI extensions

• Implement semantic search using vector embeddings and similarity matching

• Store, manage, and query vector data within PostgreSQL

• Integrate Azure AI services (e.g., Language, Translator, and Azure OpenAI) to enrich applications with intelligent features

• Perform advanced operations such as text summarization, sentiment analysis, translation, and entity recognition

• Design and implement retrieval-augmented generation (RAG) patterns for intelligent data retrieval

• Use Azure Machine Learning to run inference directly from PostgreSQL-based applications

• Build end-to-end AI-enabled solutions that combine database capabilities with AI services

Before starting this learning path, learners should have:

• Experience working with PostgreSQL databases

• Ability to write and understand SQL queries

• Basic understanding of artificial intelligence and machine learning concepts

• Familiarity with Azure services and cloud computing (helpful)

• Programming experience (e.g., Python) is beneficial but not strictly required