Develop AI-Enabled Database Solutions with SQL Server and Azure SQL.

  • Why get trained: Learn how to build AI-enabled database solutions using SQL Server, Azure SQL, Microsoft Fabric, vector search, embeddings, Data API Builder and retrieval-augmented generation.
  • Why it matters: AI-enabled database skills help organizations create secure, scalable AI-powered applications that combine structured data, semantic search and modern SQL development.
  • Who should attend: Database developers, data engineers, DBAs and SQL professionals who want to build AI-enabled applications across Microsoft SQL platforms.

Build practical SQL AI development skills and prepare for the Microsoft Certified: SQL AI Developer Associate certification. HRD Corp Claimable.

Overview

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.

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Skills Covered

  • Design and develop database solutions
  • Secure, optimize, and deploy database solutions
  • Implement AI capabilities in database solutions

 

Prerequisites

Before starting this learning path, you should have experience writing T-SQL queries, a basic understanding of database concepts such as tables, joins, and transactions, and familiarity with SQL Server, Azure SQL Database, or SQL databases in Microsoft Fabric.

Target Audience

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.

Course Curriculum

Module 1: Design and develop database solutions

Build database solutions across SQL Server, Azure SQL, and Microsoft Fabric. You learn to create well-structured database objects and indexes. You encapsulate business logic with stored procedures and functions. You write advanced T-SQL using techniques such as Common Table Expressions (CTE), window functions, and error handling. You also accelerate your development workflow with AI-assisted tools including GitHub Copilot and Fabric Copilot.

  • Design and implement database objects with SQL
  • Implement programmability objects with SQL
  • Write advanced T-SQL code
  • Implement SQL solutions by using AI-assisted tools

Module 2: Secure, optimize, and deploy database solutions

Take your database solutions from development to production. You learn to protect sensitive data with encryption, masking, and row-level security. You tune query performance using execution plans, Query Store, and dynamic management views. You automate deployments with CI/CD pipelines using SQL Database Projects. Finally, you expose your databases through REST and GraphQL APIs with Data API Builder.

  • Implement data security and compliance with SQL
  • Optimize database performance
  • Implement CI/CD by using SQL Database Projects
  • Integrate SQL solutions with Azure services

Module 3: Implement AI capabilities in database solutions

This learning path explores how to implement AI capabilities directly in Azure SQL Database. You learn to design intelligent search using full-text and vector search, integrate AI models and embeddings, and build Retrieval Augmented Generation (RAG) solutions entirely in T-SQL.

  • Design and implement models and embeddings with SQL
  • Design and implement intelligent search with SQL
  • Design and implement RAG with SQL

 

Dates & Locations

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August 3, 2026 - August 5, 2026

Location: Kuala Lumpur
Modal: ILT
Availability: TBC
Exam:
RM 374
RM 2800

August 3, 2026 - August 5, 2026

Location: Online
Modal: VILT
Availability: TBC
Exam:
RM 374
RM 2800

October 5, 2026 - October 9, 2026

Location: Kuala Lumpur
Modal: ILT
Availability: TBC
Exam:
RM 374
RM 2800

October 5, 2026 - October 9, 2026

Location: Online
Modal: VILT
Availability: TBC
Exam:
RM 374
RM 2800

December 7, 2026 - December 9, 2026

Location: Kuala Lumpur
Modal: ILT
Availability: TBC
Exam:
RM 374
RM 2800

December 7, 2026 - December 9, 2026

Location: Online
Modal: VILT
Availability: TBC
Exam:
RM 374
RM 2800
Trainocate exam and cert

Exam & Certification

Microsoft Certified: SQL AI Developer Associate.

As a candidate for this certification, you should be adept at building AI‑enabled database solutions across Microsoft SQL platforms, integrating AI features, applying T‑SQL and CI/CD practices, and collaborating with cross‑functional teams to deliver secure, scalable, high‑performance data solutions.

  • Level: Intermediate
  • Product: Azure
  • Role: Developer
  • Subject: Data management

You should also have experience writing T-SQL code and developing databases in Microsoft SQL platforms. Plus, you need to be familiar with continuous integration and continuous deployment (CI/CD) practices in GitHub, AI-assisted development tools, and AI concepts, such as embeddings, vectors, and models.

Your responsibilities include:

  • Designing and developing database solutions that include both structured and semi-structured data.
  • Integrating AI features into modern and highly scalable enterprise applications.
  • Securing, optimizing, and deploying database solutions.
  • Implementing AI capabilities in database solutions.

You work closely with application developers; database administrators (DBAs); architects; AI engineers; development, security, operations (DevSecOps) engineers; security and compliance administrators; and other stakeholders to deliver robust, high-performance database solutions that power modern applications and AI-driven experiences.

Training & Certification Guide

As a candidate for this Microsoft Certification, you should have subject matter expertise in designing and developing AI-enabled database solutions across Microsoft SQL platforms, including Microsoft SQL Server, Azure SQL, and SQL databases in Microsoft Fabric.

You should also have experience writing T-SQL code and developing databases in Microsoft SQL platforms. Plus, you need to be familiar with continuous integration and continuous deployment (CI/CD) practices in GitHub, AI-assisted development tools, and AI concepts, such as embeddings, vectors, and models.

  • Applying advanced T-SQL techniques for AI-ready database solutions.
  • Building vector and semantic search experiences directly in SQL.
  • Implementing RAG workflows to ground large language model (LLM) outputs and reduce hallucinations.
  • Integrating LLMs into SQL-based applications without migrating data.
  • Designing secure, compliant, and scalable AI-enabled data solutions.
  • Exposing SQL data through APIs by using Data API builder.
  • Building and monitoring data APIs by using Data API builder and event-driven change patterns.

These capabilities power use cases like semantic and hybrid search, chatbots, personalized recommendations, fraud detection, and predictive analytics.

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Frequently Asked Questions

DP-800T00 teaches you how to build AI-enabled database solutions using Microsoft Azure.

This course focuses on combining database development with artificial intelligence capabilities. Learners will design intelligent applications by integrating Azure data services with AI tools, enabling automation, predictive analytics, and smarter decision-making.

Key learning areas:

  • AI integration with structured data
  • Azure AI and data services
  • Intelligent application design
  • Scalable and secure database solutions

Pro Tip: Focus on understanding how AI enhances real-world applications, not just theory. Employers value practical AI implementation skills.

It is designed for database developers and data professionals moving into AI-driven roles.

This course is ideal for professionals who already understand databases and want to expand into AI-enabled solutions. It bridges the gap between traditional data roles and modern AI applications.

Best suited for:

  • Database developers
  • Data engineers
  • Backend developers
  • Cloud and AI solution architects

Pro Tip: If you already work with SQL or data platforms, this course can significantly expand your career opportunities into AI-related roles.

You will gain the ability to design and build intelligent, AI-powered database applications.

The course emphasizes practical implementation of AI within data systems. You will learn how to combine data engineering with AI tools to create scalable and intelligent solutions.

Skills gained:

  • Designing AI-enabled data architectures
  • Integrating Azure AI services
  • Building intelligent applications
  • Optimizing performance and scalability

Pro Tip: Build a small portfolio project after the course. Demonstrating AI + data skills is more impactful than listing certifications alone.

It focuses on building intelligent systems, not just managing data.

Traditional database training emphasizes storage, querying, and performance. DP-800T00 goes further by enabling systems that can analyze data, generate insights, and automate decisions using AI.

Key differences:

  • AI-driven insights vs static queries
  • Predictive analytics capabilities
  • Integration with Azure AI services
  • Real-time intelligent applications

Pro Tip: Understanding AI concepts alongside databases makes your skillset more future-proof compared to traditional database roles.

It prepares you for high-demand roles combining data engineering and AI.

Malaysia’s digital economy is rapidly growing, with increasing demand for professionals who can work across data and AI domains.

Relevant roles:

  • AI Data Engineer
  • Azure Data Engineer
  • AI Solutions Developer
  • Data Engineer (AI-enabled systems)

Malaysia salary benchmark:

  • Average Data Engineer salary: RM5,350 – RM7,850/month
  • Median salary: RM9,000/month, with ranges up to RM14,500
  • Annual range can reach RM96,000 – RM240,000 depending on experience

These figures show strong earning potential, especially for professionals with AI-integrated data skills.

Pro Tip: Roles that combine AI + data tend to command higher salaries than traditional data roles. Prioritize learning both skillsets together.

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