DP-800: Microsoft SQL AI Developer Associate Exam Prep

Name: DP-800: Microsoft SQL AI Developer Associate Exam Prep
Rating: 4.7 (33 reviews)

Prepare for the DP-800 Exam with Instructor-led videos and hands-on labs

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Created byKuljot Singh Bakshi

Last updated 6/2026

English

What you'll learn

Build AI-powered SQL solutions using Azure SQL, embeddings, and external models
Design and implement Retrieval-Augmented Generation (RAG) pipelines using T-SQL
Apply advanced SQL features like JSON, graph queries, and stored procedures for AI scenarios
Secure and optimize AI-driven databases using encryption, indexing, and performance tuning

Course content

12 sections • 87 lectures • 15h 12m total length

Course Introduction2:50

Introduction to Some SQL Basics and Jargons14:18
SQL v/s T-SQL4:20
Lab: Deploying an Azure SQL Server and Database (Hands-On Lab)11:00
Lab: Setting up SQL Server in SSMS (Hands-On Lab)7:00
Note: GitHub Repository for Labs1:40
Understanding Azure SQL Offerings14:16
Choosing Appropriate Data Types6:26
Understanding the Star Schema Model for Data Modelling8:07
Understanding Case Studies for the Labs - ESG Reporting6:52
Lab: Creating our Tables with DDL Operations (Hands-On Lab)17:48
Lab: Visualizing with a DB Diagram (Hands-On Lab)4:01
Lab: Getting Comfortable with Some SQL Queries (Hands-On Lab)12:43
Introduction to SQL JOINS10:29
Lab: Running some SQL JOINS (Hands-On Lab)19:07

Introduction to Views6:20
Lab: Implement Basic Views in SQL (Hands-On Lab)8:06
Lab: Implement Logical and Indexed Views in SQL (Hands-On Lab)9:56
Understand Stored Procedures7:38
Lab: Implement Stored Procedures (Hands-On Lab)19:11
Understand Scalar Functions4:29
Lab: Implement Scalar Functions (Hands-On Lab)7:48
Understand Table-Valued Functions: Inline and Multi-Statement8:53
Lab: Implement Table-Valued Functions (Hands-On Lab)10:44
Understand SQL Triggers: DDL and DML3:09
Lab: Implement SQL Triggers (Hands-On Lab)15:32

Understand CTEs: Common Table Expressions4:13
Lab: Implement CTEs (Hands-On Lab)8:55
Window Functions: Ranking, Aggregation and Range10:11
Lab: Window Functions Part 1 - Ranking Functions (Hands-On Lab)15:44
Window Functions: Analytical Functions and Queries12:26
Lab: Window Functions Part 2 - Trend Analysis (Hands-On Lab)11:17
Lab: Process JSON Data with Built-In Functions (Hands-On Lab)13:02
Lab: Match Patterns with Regular Expressions (Hands-On Lab)11:12
Understand String Similarity Concepts7:46
Lab: Find Matches with String Similarity Functions (Hands-On Lab)10:28
Lab: Traverse Relationships with Graph Queries (Hands-On Lab)12:46
Lab: Compare Rows with Correlated Subqueries (Hands-On Lab)13:11
Error Handling: Try...Catch and Transaction Rollbacks11:34
Lab: Implement Error Handling (Hands-On Lab)8:59

Introduction to GenAI and LLM Systems7:12
GAI-101: Introduction to some GenAI Jargons10:10
Understanding the Microsoft Foundry Ecosystem10:02
Lab: Deploying a Microsoft Foundry Resource (Hands-On Lab)8:42
Lab: Deploying a LLM in Microsoft Foundry (Hands-On Lab)7:32
Compare Model Deployment Types in Foundry4:38
Understanding "External AI Models" in SQL Server7:24
Lab: Setting up the Tables and Data (Hands-On Lab)4:45
Lab: Set up the Managed Identity and API Key Credentials (Hands-On Lab)14:33
Lab: Make a LLM API Call using the DB Credentials (Hands-On Lab)14:23
Lab: Encapsulate LLM API Logic in a Stored Procedure (Hands-On Lab)11:15
Lab: Sentiment Analysis and Summarization using LLM (Hands-On Lab)17:55
Understand Vector Embeddings9:17
Lab: Deploy an Embedding Engine in Microsoft Foundry (Hands-On Lab)3:04
Lab: Generate Vector Embeddings with SQL (Hands-On Lab)8:20
Choose an Embedding Maintenance Method5:29

Requirements

Familiarity with databases or data concepts is helpful but not mandatory
A Microsoft Azure account
Willingness to learn how SQL integrates with AI concepts like embeddings and RAG

Description

SQL is no longer just about querying data — it’s becoming a powerful foundation for building AI-driven applications.

In this course, you’ll learn how to combine traditional SQL development with modern AI capabilities to build intelligent, production-ready solutions using Microsoft technologies. Whether you’re preparing for the DP-800: Microsoft Certified SQL AI Developer Associate exam or looking to upgrade your skillset, this course is designed to give you both depth and practical experience.

We start with core SQL concepts and quickly move into advanced topics that power real-world AI scenarios. You’ll learn how to work with JSON, graph queries, stored procedures, and advanced querying techniques to model complex data. From there, we introduce AI integration — including embeddings, external models, and Retrieval-Augmented Generation (RAG) — all implemented directly using SQL.

What makes this course unique is its hands-on, lab-driven approach. You won’t just learn theory — you’ll build solutions that simulate real enterprise use cases, including secure data handling using encryption, masking, and access control, along with performance tuning using indexing and query optimization.

By the end of this course, you will be able to design and implement AI-powered database solutions, understand how SQL fits into modern AI architectures, and confidently approach the DP-800 certification.

If you’re ready to move beyond traditional SQL and step into the future of SQL + AI, this course is for you.

Who this course is for:

SQL developers looking to integrate AI capabilities into database solutions
Data engineers and analysts preparing for the DP-800 certification
Developers curious about building RAG pipelines using SQL and Azure AI
Professionals working with Azure SQL who want to modernize with AI features
Anyone interested in combining traditional databases with modern AI techniques

DP-800: Microsoft SQL AI Developer Associate Exam Prep

What you'll learn

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Course content

Introduction1 lecture • 3min

Course Outline and Learning Recommendations1 lecture • 5min

Azure SQL Foundations14 lectures • 2hr 18min

Design and Implement Database Objects8 lectures • 1hr 48min

Implement Programmability Objects11 lectures • 1hr 42min

Write Advanced T-SQL Code14 lectures • 2hr 32min

Design and Implement SQL Solutions with AI Assistance4 lectures • 49min

Implement Data Security and Compliance4 lectures • 44min

Integrate SQL Solutions with Azure Services3 lectures • 33min

GenAI Foundations and Primers with SQL16 lectures • 2hr 25min

Requirements

Description

Who this course is for: