Microsoft DP-800 SQL AI Developer Associate Practice Tests
About this course
Are you preparing for the Microsoft Certified: SQL AI Developer Associate (exam DP-800)? This course contains six full-length practice tests that mirror the real exam: scenario based, covering the development of AI-enabled database solutions across SQL Server, Azure SQL, and Fabric SQL database.Every question is scenario-based, just like the real exam. No trivia. No "What is X?" definitions. You read a realistic database development situation and choose the right T-SQL feature, AI capability, or security control.What makes these practice tests different:Every question is grounded in the official Microsoft Learn documentation for SQL Server, Azure SQL, Fabric SQL, and the DP-800 study guide. Each explanation ends with a Reference link to the source.Questions are distributed across all three skill areas at the exam blueprint weights: Design and develop database solutions (around 38%), Secure, optimize, and deploy database solutions (around 37%), and Implement AI capabilities in database solutions (around 25%).Explanations cover every option, not just the correct answer. You learn why each wrong option does not fit, which builds the elimination skills you need on exam day.Content reflects current SQL AI features: the native vector data type, VECTOR_DISTANCE and VECTOR_SEARCH, AI_GENERATE_EMBEDDINGS, retrieval-augmented generation with sp_invoke_external_rest_endpoint, hybrid search, advanced T-SQL, GitHub Copilot for SQL, and security features like Always Encrypted, row-level security, and dynamic data masking.
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What you'll learn
- understand scenario-based questions related to AI database solutions
- identify the correct T-SQL features to apply in different cases
- explain why certain answers are incorrect to improve elimination skills
- be familiar with current SQL AI functionalities and security features
Course objectives
- prepare effectively for the DP-800 certification exam
- gain insights into AI-enabled database solutions
- master the implementation of AI capabilities in SQL databases
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