Develop AI-enabled database solutions
(3 days)
Course Description
This course provides students with the knowledge and skills to design and develop AI enabled database solutions across Microsoft SQL platforms, including SQL Server, Azure SQL, and SQL databases in Microsoft Fabric. It is intended for professionals who build modern data solutions that integrate structured and semi structured data and incorporate AI features into scalable enterprise applications. It will also be valuable for individuals who develop applications that rely on SQL based data services enhanced with vector search, embeddings, and other AI driven capabilities.Learning Objectives
-
Design and implement scalable database solutions across SQL platforms
-
Develop advanced T-SQL queries using CTEs, window functions, and JSON
-
Integrate AI capabilities such as embeddings and vector search into databases
-
Implement database security, compliance, and performance optimization techniques
-
Build and deploy database solutions using CI/CD pipelines and DevOps practices
-
Develop AI-powered applications using RAG and AI-assisted tools like GitHub Copilot
Who Should Attend
The audience for this course is data professionals who want to learn about designing and developing AI-enabled database solutions across Microsoft’s SQL platforms, including SQL Server, Azure SQL, and SQL databases in Microsoft Fabric. This role develops database solutions that include both structured and semi-structured data and integrates AI features into modern and highly scalable enterprise applications.
Prerequisites
- Experience writing T-SQL queries.
- Familiarity with SQL Server or Azure SQL Database.
- Basic understanding of security concepts like authentication and authorization.
- Experience with Git version control and CI/CD concepts.
Course Outline
Module 1: Design and develop database solutions
Design and implement database objects with SQL
Exercise - Create and maintain database objects
Implement programmability objects with SQL
Exercise: Implement programmability objects in SQL Server
Write advanced T-SQL code
Exercise - Work with JSON functions
Implement SQL solutions using AI-assisted tools
Exercise - Configure AI-assisted tools for database development
Module 2: Secure, optimize, and deploy database solutions
Implement data security and compliance with SQL
Exercise: Implement security features
Optimize database performance
Exercise: Optimize query performance
Implement CI/CD by using SQL Database Projects
Exercise: Implement CI/CD by using SQL Database Projects
Integrate SQL solutions with Azure services
Exercise - Configure Data API Builder for a product catalog
Module 3: Implement AI capabilities in database solutions
Design and implement models and embeddings with SQL
Exercise - Generate and update embeddings in Azure SQL Database
Design and implement intelligent search with SQL
Exercise - Implement intelligent search with full-text, vector, and hybrid queries
Design and implement RAG with SQL
Exercise: Implement a RAG solution
