Building AI Data Foundations with Azure Database for PostgreSQL

Modern AI applications are only as good as the data infrastructure supporting them. Building a reliable, scalable database foundation is the first step toward launching intelligent software. In this course, you will learn how to set up, configure, and query Azure Database for PostgreSQL as a robust backend for AI-driven applications. You will transition from understanding basic relational database concepts to designing efficient schemas and connecting your data directly to Python-based application workflows. What you will learn: Understand foundational relational database concepts and PostgreSQL terminology; Design optimized schemas and tables tailored for relational and semi-structured data; Write efficient SQL queries to retrieve, filter, and manipulate application data; Integrate PostgreSQL with Python using modern database adapters and connection pools; Store and query high-dimensional vector embeddings using the pgvector extension for AI search; Apply security and performance best practices to keep your database secure and responsive. You will start with the fundamental principles of database design and SQL syntax before advancing to Python integration and modern vector search capabilities. Through structured written explanations and practical code examples, you will build a solid understanding of cloud-hosted database management. This course is designed for beginners, developers, and data enthusiasts looking to build a strong foundation in database management for AI. No prior database administration experience is required. Start reading today to build the data foundation your next intelligent application needs.