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You learn how to design and implement Azure ExpressRoute, ExpressRoute Global Reach, ExpressRoute FastPath.

Units in this learning path:

• Introduction
• Explore
• Design Expressroute Deployment
• Exercise Configure Expressroute Gateway
• Exercise Provision Expressroute Circuit
• Configure Peering for Expressroute Deployment
• Connect Expressroute Circuit to Vnet
• Connect Geographically Dispersed Networks Expressroute Global Reach
• Improve Data Path Performance Between Networks Expressroute Fastpath
• Troubleshoot Expressroute Connection Issues
• Summary Resources

Products: Azure Expressroute, Azure Virtual Network

Roles: Administrator, Network Engineer

Level: Intermediate

Subjects: Data Engineering, Networking

Duration: 57 minutes

Learn how to implement Retrieval Augmented Generation (RAG) patterns using Azure SQL Database. Identify RAG use cases, prepare database context for Large Language Model (LLM) processing, construct augmented prompts, and process model responses.

Units in this learning path:

• Introduction
• Identify Rag Use Cases Architecture
• Prepare Retrieval Context Augmentation
• Augment Prompts Database Context
• Generate Process Rag Responses
• Exercise Implement Rag Solution
• Knowledge Check
• Summary

Products: Azure SQL Database, SQL Server

Roles: Database Administrator, Developer, Data Engineer

Level: Intermediate

Subjects: Databases, Artificial Intelligence

Duration: 75 minutes

Design and implement a replication strategy for Azure Cosmos DB for NoSQL

Modules in this learning path:

• Configure Replication Manage Failovers Azure Cosmos Db
• Use Consistency Models Azure Cosmos Db SQL API
• Configure Multi Region Write Azure Cosmos Db SQL API

Products: Azure Cosmos Db

Roles: Developer

Level: Intermediate

Subjects: Data Management

Duration: 116 minutes

Learn how to design and implement data modeling strategies in Azure Databricks with Unity Catalog, including ingestion patterns, table formats, partitioning, slowly changing dimensions, and clustering strategies.

Units in this learning path:

• Introduction
• Design Data Ingestion Logic
• Choose Data Ingestion Tool
• Choose Data Table Format
• Design Data Partitioning Scheme
• Choose Scd Type
• Implement Slowly Changing Dimension Type 2
• Design Temporal History Table
• Choose Granularity
• Choose Managed Vs Unmanaged Tables
• Design Clustering Strategy
• Exercise
• Knowledge Check
• Summary

Products: Azure Databricks

Roles: Data Engineer

Level: Intermediate

Subjects: Data Engineering

Duration: 137 minutes

Learn how to design and implement robust data pipelines using Lakehouse architecture principles, medallion architecture, and Lakeflow Spark Declarative Pipelines in Azure Databricks.

Units in this learning path:

• Introduction
• Design Order Operations Pipeline
• Choose Notebook Vs Lakeflow Pipelines
• Design Task Logic Lakeflow Job
• Design Error Handling Pipelines
• Create Pipeline Notebook Precedence
• Create Pipeline Lakeflow Declarative
• Exercise
• Knowledge Check
• Summary

Products: Azure Databricks

Roles: Data Engineer

Level: Intermediate

Subjects: Data Engineering

Duration: 96 minutes

Learn how to design and implement database objects in SQL Server, Azure SQL, and SQL databases in Microsoft Fabric, including tables, indexes, constraints, and specialized table types.

Units in this learning path:

• Introduction
• Understanding Platform Choices
• Design Implement Tables
• Design Implement Indexes
• Specialized Table Types
• Design Implement Constraints
• Design Implement Json
• Design Implement Partitioning
• Exercise Create Database Objects
• Knowledge Check
• Summary

Products: SQL Server, Azure SQL Database, Azure SQL Managed Instance, Fabric

Roles: Data Engineer, Database Administrator, Developer, Solution Architect

Level: Intermediate, Advanced

Subjects: Databases, Data Management, Data Engineering, Cloud Computing, App Development

Duration: 98 minutes

Implement intelligent search capabilities in SQL Server and Azure SQL by combining traditional full-text search with semantic vector search. Learn to choose search approaches, prepare SQL for vector search, and implement vector, hybrid, and ranking-based search patterns.

Units in this learning path:

• Introduction
• Choose Intelligent Search Approach
• Implement Full Text Search
• Prepare SQL Vector Search
• Implement Vector Search Query Patterns
• Implement Hybrid Search Ranking
• Exercise Implement Intelligent Search
• Knowledge Check
• Summary

Products: Azure, Azure SQL Database, SQL Server

Roles: Developer, Data Engineer

Level: Intermediate

Subjects: Databases, Artificial Intelligence, Cloud Computing

Duration: 84 minutes

Integrate AI models with Azure SQL Database using external models, the vector data type, and built-in AI functions. Design embedding strategies, generate embeddings from text, and implement maintenance patterns.

Units in this learning path:

• Introduction
• Understand Evaluate Models SQL Database Workloads
• Create Manage External Model SQL
• Design Embeddings SQL Database Workloads
• Generate Maintain Embeddings SQL Database Workloads
• Exercise Generate Update Embeddings SQL
• Knowledge Check
• Summary

Products: Azure, Azure SQL Database

Roles: Developer, Data Engineer

Level: Intermediate

Subjects: Databases, Artificial Intelligence, Cloud Computing

Duration: 61 minutes

You learn to design and implement private access to Azure Services with Azure Private Link, and virtual network service endpoints.

Units in this learning path:

• Introduction
• Explain Virtual Network Service Endpoints
• Define Private Link Service Private Endpoint
• Integrate Private Link Dns
• Exercise Restrict Network Paas Resources Virtual Network Service Endpoints Using
• Exercise Create Azure Private Endpoint Using Azure Powershell
• Summary

Products: Azure Private Link, Azure Virtual Network

Roles: Administrator, Network Engineer

Level: Intermediate

Subjects: Data Engineering, Networking

Duration: 42 minutes

Create semantic models that serve reliable, governed analytics at scale — from initial DAX logic through performance optimization, data access control, and automated lifecycle management.

Modules in this learning path:

• Dax Power Bi Create Calculations
• Design Semantic Models Scale
• Optimize Semantic Model Performance
• Enforce Semantic Model Security
• Manage Semantic Model Lifecycle

Products: Fabric

Roles: Data Analyst

Level: Intermediate

Subjects: Data Analytics, Data Modeling

Duration: 381 minutes

Design dimensional models and apply transformations using dataflows, Spark notebooks, and T-SQL to produce consistent, analysis-ready data in Microsoft Fabric.

Modules in this learning path:

• Choose Data Store Fabric
• Design Dimensional Models Fabric
• Fabric Transform Data Dataflows
• Fabric Transform Data Notebooks
• Fabric Transform Data Tsql

Products: Fabric

Roles: Data Analyst, Data Engineer

Level: Intermediate

Subjects: Data Analytics, Data Engineering, Data Integration, Data Modeling

Duration: 314 minutes

Azure Architects design and recommend data integration solutions.

Units in this learning path:

• Introduction
• Solution Azure Data Factory
• Solution Azure Data Lake
• Solution Azure Data Brick
• Solution Azure Synapse Analytics
• Design Strategy for Hot Warm Cold Data Path
• Design Azure Stream Analytics Solution for Data Analysis
• Knowledge Check
• Summary Resources

Products: Azure, Azure Blob Storage, Azure Data Factory, Azure Data Lake, Azure Databricks, Azure Stream Analytics, Azure Synapse Analytics

Roles: Solution Architect

Level: Advanced

Subjects: Data Management

Duration: 53 minutes