Microsoft Certified: SQL AI Developer Associate Certification | DP-800 Exam Prep

SKU: 3928
12 Lesson
|
30 Hours
Advance your SQL development skills with igmGuru's Microsoft Certified: SQL AI Developer Associate Certification | DP-800 Exam Prep. This training covers database design, advanced T-SQL, AI-assisted development, security, performance optimization, SQL Database Projects, CI/CD, Data API Builder, embeddings, vector search, hybrid search, and retrieval-augmented generation across Microsoft SQL platforms.

SQL AI Developer Associate Course Overview

DP-800 preparation focuses on designing, securing, optimizing, deploying, and extending AI-enabled database solutions across SQL Server, Azure SQL, and SQL databases in Microsoft Fabric. The course develops practical knowledge of database objects, advanced T-SQL, GitHub CI/CD, SQL Database Projects, Data API Builder, intelligent search, embeddings, and RAG patterns aligned with the current Microsoft exam objectives.

Prerequisites

  • T-SQL Programming
  • Microsoft SQL Server Database Development
  • Azure SQL Database Knowledge
  • Microsoft Fabric SQL Database Knowledge
  • GitHub CI/CD Fundamentals
  • AI-Assisted Development Tools
  • AI Fundamentals
  • embeddings and Vector Concepts

What Will You Learn

  • Design and Implement SQL Database Objects
  • Build Tables, Constraints, Indexes, and Partitions
  • Develop Views, Functions, Stored Procedures, and Triggers
  • Write Advanced T-SQL with CTEs and Window Functions
  • Work with JSON, Regular Expressions, Fuzzy Matching, and Graph Queries
  • Use GitHub Copilot and Microsoft Copilot in Fabric
  • Connect SQL and Fabric Solutions to MCP Servers
  • Implement Encryption, Dynamic Data Masking, RLS, and Auditing
  • Optimize Query Performance with Query Store, DMVs, and Execution Plans
  • Build CI/CD Pipelines with SQL Database Projects
  • Configure Data API Builder for REST and GraphQL
  • Implement embeddings Function and Intelligent Search
  • Build Vector, Semantic, and Hybrid Search
  • Design Retrieval-Augmented Generation (RAG) Solutions
  • Integrate SQL Data with Language Models

Who Can Join This Training

  • SQL Developers
  • Database Developers
  • Database Administrators
  • Data Engineers
  • Azure SQL Professionals
  • Microsoft Fabric Professionals
  • Application Developers
  • Data Architects
  • AI Engineers Working with SQL
  • DevSecOps Engineers

Is This the Right Certification for You?

This certification is a strong fit when you already work with SQL and want to add AI capabilities to database solutions. You should have experience writing T-SQL and developing databases on Microsoft SQL platforms, along with familiarity with GitHub CI/CD, AI-assisted development, embeddings, vectors, and models.

You will be a good fit if you want to:

  • Build AI-enabled database solutions without moving away from SQL
  • Add vector and semantic search to SQL applications
  • Implement RAG patterns with SQL data
  • Secure and optimize enterprise database solutions
  • Use AI-assisted development tools with SQL
  • Work with Azure SQL, SQL Server, and Microsoft Fabric

Tools and Technologies Covered

  • Microsoft SQL Server
  • Azure SQL
  • Microsoft Fabric
  • T-SQL
  • SQL Database Projects
  • GitHub
  • GitHub Copilot
  • Microsoft Copilot in Fabric
  • Model Context Protocol (MCP)
  • Data API Builder
  • Azure Monitor
  • Application Insights
  • Log Analytics
  • Azure Functions
  • Azure Logic Apps
  • Azure AI Foundry
  • Query Store
  • Dynamic Management Views (DMVs)
  • Always Encrypted
  • Dynamic Data Masking
  • Row-Level Security (RLS)
  • Vector Search
  • Semantic Search
  • Hybrid Search
  • embeddings Function
  • Retrieval-Augmented Generation (RAG)

SQL AI Developer Associate Training Modules

1. Design and implement tables
2. Select data types, columns, and index structures
3. Implement columnstore indexes
4. Design specialized tables
5. Implement in-memory tables
6. Implement temporal tables
7. Implement external tables
8. Implement ledger tables
9. Implement graph tables
10. Design JSON columns and indexes
11. Implement primary keys, foreign keys, unique, check, and default constraints
12. Implement sequences
13. Implement table and index partitioning
1. Create views
2. Create scalar functions
3. Create table-valued functions
4. Create stored procedures
5. Create triggers
6. Implement reusable database logic
1. Common table expressions (CTEs)
2. Window functions
3. JSON functions
4. Regular expression functions
5. Fuzzy string matching
6. Correlated queries
7. Graph queries with the MATCH operator
8. SQL error handling
1. AI-assisted database development
2. Security considerations for AI-assisted tools
3. GitHub Copilot for SQL development
4. Microsoft Copilot in Microsoft Fabric
5. Configure model options
6. Configure Model Context Protocol (MCP) tools
7. Create GitHub Copilot instruction files
8. Connect to MCP servers
9. Connect MCP tools to SQL Server and Fabric lakehouses
1. Data encryption
2. Always Encrypted
3. Column-level encryption
4. Dynamic Data Masking
5. Row-Level Security (RLS)
6. Object-level permissions
7. Secure database access
8. Passwordless authentication
9. Database auditing
10. Managed Identity
11. Secure REST, GraphQL, and MCP endpoints
1. Recommend database configurations
2. Transaction isolation levels
3. Concurrency controls
4. Query execution plans
5. Dynamic Management Views (DMVs)
6. Query Store
7. Query Performance Insight
8. Query performance troubleshooting
9. Blocking and deadlock resolution
1. SQL Database Projects
2. Unit and integration testing strategies
3. Reference and static data management
4. Database model creation and validation
5. SDK-style SQL Database Projects
6. Source control configuration
7. Branching strategies
8. Pull requests
9. Conflict resolution
10. Secrets management
11. Schema drift detection
12. Database project updates and deployment
13. Deployment pipeline controls
14. Branching policies
15. Approval triggers
16. Authentication tables
17. Code owners
1. Data API Builder (DAB)
2. DAB configuration files
3. REST entities
4. GraphQL entities
5. Data caching
6. Pagination
7. Searching and filtering
8. REST endpoints
9. GraphQL endpoints
10. Exposing tables, views, and stored procedures
11. GraphQL relationships
12. DAB deployment
13. Azure Monitor configuration
14. Application Insights
15. Log Analytics
16. Change Event Streaming (CES)
17. Change Data Capture (CDC)
18. Change Tracking
19. Azure Functions SQL trigger bindings
20. Azure Logic Apps
1. Evaluate external AI models
2. Multimodal models
3. Multilanguage models
4. Model size and structured output considerations
5. Create and manage external models
6. Embedding maintenance methods
7. Table triggers
8. Change Tracking
9. Azure Functions SQL trigger bindings
10. Azure Logic Apps
11. CDC
12. CES
13. Azure AI Foundry
14. Select columns for embeddings
15. Design embedding chunks
16. embeddings
1. Full-text search
2. Semantic search
3. Vector search
4. Hybrid search
5. Vector data types
6. Vector indexes
7. Vector dimensions
8. VECTOR_NORMALIZE
9. VECTOR_DISTANCE
10. VECTORPROPERTY
11. VECTOR_SEARCH
12. Approximate Nearest Neighbor (ANN)
13. Exact Nearest Neighbor (ENN)
14. Vector index types
15. Vector search metrics
16. Reciprocal Rank Fusion (RRF)
17. Search performance evaluation
1. RAG concepts and use cases
2. Prompt creation with sp_invoke_external_rest_endpoint
3. Convert structured SQL data to JSON
4. Send SQL-derived context to Azure OpenAI
5. Process language model responses
6. Ground language model responses with database data
1. Design and develop database solutions
2. Secure, optimize, and deploy database solutions review
3. Implement AI capabilities in SQL solutions review
4. Review exam domains and skills matrix
5. Practice scenario-based questions
6. Work with interactive exam question formats
7. Complete mock assessments
8. Review exam readiness
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SQL AI Developer Associate Course Fees

Online Class Room Program

US $ 799.00
100% Money Back Guarantee
  • Duration : 30 Hrs
  • Plus Self Paced

Classes Starting From

  • Fast Track Batch 02 Sep 2026
  • Weekday Batch 07 Sep 2026
  • Weekend Batch 05 Sep 2026

1 ON 1 Training

US $ 899.00
100% Money Back Guarantee
  • Duration : 30 Hrs
  • Plus Self Paced

Classes Starting From

  • Fast Track Batch 02 Sep 2026
  • Weekday Batch 07 Sep 2026
  • Weekend Batch 05 Sep 2026

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Microsoft SQL AI Developer Associate (DP-800) Certification Training

The Microsoft Certified: SQL AI Developer Associate certification validates skills in designing, developing, securing, optimizing, and deploying AI-enabled database solutions across Microsoft SQL Server, Azure SQL, and SQL databases in Microsoft Fabric. The DP-800 training covers advanced T-SQL, database development, AI-assisted SQL development, security, performance optimization, CI/CD, vector search, embeddings, and retrieval-augmented generation (RAG). Upon successful completion of the training, igmGuru provides a Course Completion Certificate, which is separate from the official Microsoft certification.

Exam Details:

  • Official Certification: Microsoft Certified: SQL AI Developer Associate
  • Exam: DP-800: Developing AI-Enabled Database Solutions
  • Certification Provider: Microsoft
  • Exam Duration: 120 Minutes
  • Passing Score: 700 out of 1000
  • Exam Delivery: Pearson VUE, proctored
  • Exam Language: English
  • Exam Cost: USD 165 in the United States; pricing varies by country or region
  • Certification Renewal: Annual renewal through a free online assessment on Microsoft Learn
Microsoft SQL AI Developer Associate (DP-800) Certification Training

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