Partner Skilling Catalog

PSC

Implement AI Solutions with Azure SQL Database and SQL Server 2025

This course equips developers and technical professionals to build AI-powered applications using modern SQL capabilities in SQL Server 2025 and Azure SQL. You’ll learn how to design RAG solutions, create and query vector embeddings, and integrate Azure OpenAI and Microsoft Foundry models with your data. The course also covers Copilot-enhanced SQL development, secure AI integrations using Managed Identity and REST endpoints, and exposing SQL through REST, GraphQL, and MCP for intelligent applications.

8 hours(Suggested: 2 days, 4h/day)TechnicalProject ReadyHands-on Labs

MS Course ID: 00969

Last Updated: Feb 23, 2026

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Pre-requisites

Prior knowledge of Azure Database for SQL ,SQL server and Azure OpenAI

Related Certifications

AI-102

DP-600

Course Syllabus

Foundations Core AI Features

Module 1: Implementing Retrieval-Augmented Generation (RAG)
• Why RAG matters for enterprise AI
• Retrieval patterns (Keyword → Metadata → Vector)
• Designing RAG patterns in SQL server 2025
• LLM consumes external data
Module 2: Azure OpenAI Models & Prompting
• Model families
• Registering models using CREATE EXTERNAL MODEL
• Chat Completion API
• Embeddings API
• Prompt structuring
• Microsoft Foundry
• Capabilities (chat, embeddings, reasoning)
Module 3: Vector Search and Embeddings in SQL Server 2025
• Fundamentals of embeddings
• Storing vectors in SQL Server
• VECTOR_SEARCH and VECTOR_DISTANCE
• Exact vs Approximate search (DiskANN)
• Hybrid search
Module 4: Building Intelligent Applications
• Using Azure OpenAI Service
• “Chat with your data” using SQL and NLP
• Real-world use cases

150 mins

Lecture

Hands on labs

Lab 1: Building a Semantic Patient Case Search Engine for Healthcare Using SQL Server 2025
• Exercise 1: Provision SQL Server on Azure VM
• Exercise 2: Setup SQL Server 2025 environment
• Exercise 3: Create Azure OpenAI resource and deploy Embedding Model
• Exercise 4: Create Data base and tables
• Exercise 5: Import Patient Notes.csv
• Exercise 6: Create external embedding model
• Exercise 7: Generate embeddings and store vectors
• Exercise 8: Semantic case retrieval (doctor symptom query)
• Exercise 9: Compare keyword vs semantic search
Lab 2: Developing a Knowledge-Augmented Medical Library Assistant with RAG and Azure SQL Database
• Exercise : Create SQL Database Server
• Exercise 2: Create an Azure SQL Database
• Exercise 3: Create a database via SSMS and upload csv file.
• Exercise 4: Create Azure OpenAI service and deploy chat and embedding models
• Exercise 5: Create Azure AI Search Service
• Exercise 6: Create Search Index
• Exercise 7: Build RAG Agent in Azure AI Foundry

90 mins

Lab

Advanced Integration and Real-World Scenarios

Module 5: MSSQL extension for Visual Studio Code
• MSSQL VS Code extension
• SQL Server local container
• Schema design & management
• Using GitHub Copilot with SQL server 2025
Module 6: GitHub Copilot in SQL Server Management Studio (SSMS)
• GitHub Copilot in SSMS
• Chat, inline suggestions, slash commands
• Generating T-SQL queries from natural language
• Security Analyzer, Query Builder
• Troubleshooting & optimization
Module 7: Security & Governance for AI with SQL Server 2025
• Managed Identity for secure API calls from SQL to Azure OpenAI
• Role-Based Access Control (RBAC) and dynamic data masking
• Compliance considerations for AI workloads
• Secure external REST calls using sp_invoke_external_rest_endpoint
Module 8: Exposing SQL to AI Apps
• Data API Builder for REST
• Data API Builder for GraphQL
• Data API Builder for MCP tooling
• Integrate SQL endpoints with Microsoft Foundry
• Monitoring & performance optimization

150 mins

Lecture

Hands on labs

Lab 3: Building and Securing a Safe Clinical Report Search API
Requirements: GitHub account (free) , Azure VM (on skillable cloud slice), SSMS, VSCode
• Exercise 1: Provision SQL Server on Azure VM
• Exercise 2: Create Azure OpenAI resource and deploy embedding models
• Exercise 3: Connect SQL server 2025 via SSMS
• Exercise 4: Enable SQL Server 2025 AI Capabilities
• Exercise 5: Azure OpenAI Integration (SQL Server 2025 Pattern)
• Exercise 6: Create Embeddings Table
• Exercise 7: Create Vector Index (DiskANN) and Exact vs ANN Search
• Exercise 8: Secure with Managed Identity
• Exercise 9: Apply Masking and RBAC
• Exercise 10: Expose the Search as a Secure API
• Exercise 11: Build the Core Search Stored Procedure with SSMS Copilot
Lab 4: Building a Secure Inventory System with SQL Server 2025, GitHub Copilot, and Data APIs
• Exercise 1: Connect SQL Server 2025 on VS Code
• Exercise 2: Copilot Experiences for Schema Design & Query Generation
• Exercise 3: Security & Governance with SQL Server 2025
• Exercise 4: Exposing SQL Data to AI Applications using Data API Builder

90 mins

Lab

What You'll Learn

Understand core concepts and best practices

Hands-on experience with real-world scenarios

Learn from certified Microsoft experts

Prepare for relevant certifications

Access to lab environments

Post-training support and resources

Course Details

Duration: 8 hours
Level: Intermediate
Role: Technical
Course Type: Project Ready
Course Stage: Available
Hands-on Labs: Yes
Labs Platform: Spektra