Microsoft DP-800 SQL AI Developer Practice Tests

About this course

About the Certification: Microsoft Certified: SQL AI Developer Associate (DP-800)The Microsoft Certified: SQL AI Developer Associate (DP-800) certification is earned by passing Exam DP-800. This credential focuses on professionals who build, integrate, and optimize AI-enabled database solutions using SQL and Azure services. The role centers on combining traditional database development with modern AI capabilities such as embeddings, intelligent search, and retrieval-augmented generation.Professionals preparing for DP-800 are expected to work with key areas including AI integration in databases, performance optimization, security implementation, and deployment strategies. The exam focuses on how database solutions interact with AI models, APIs, and external services to support intelligent applications and data-driven scenarios.The official exam outline is organized around core skill areas such as implementing AI capabilities, integrating SQL with Azure services, and securing and optimizing database solutions. These areas reflect real-world responsibilities where developers design systems that handle structured and unstructured data, support intelligent querying, and maintain reliability under production workloads.In practical terms, the exam covers designing and implementing embeddings, vector search, and hybrid search solutions, as well as configuring intelligent retrieval patterns such as retrieval-augmented generation (RAG). Candidates are expected to understand how to prepare data, generate embeddings, and query them efficiently using vector operations.Another important focus area is integrating SQL with external services. This includes working with Data API builder (DAB), REST and GraphQL endpoints, and Azure services such as Azure Functions and Logic Apps. These integrations enable applications to expose and consume data in scalable and

Course objectives

• prepare for the DP-800 exam
• understand AI integration in databases
• develop strategies for efficient querying of structured and unstructured data