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Explore the data science process and learn how to train machine learning models to accomplish artificial intelligence in Microsoft Fabric. (DP-604T00)

Modules in this learning path:

• Introduction End Analytics Use Microsoft Fabric
• Get Started Data Science Fabric
• Explore Data for Data Science Microsoft Fabric
• Preprocess Data with Data Wrangler Microsoft Fabric
• Train Track Model Fabric
• Generate Batch Predictions Fabric

Products: Fabric

Roles: Data Scientist, Data Analyst, Data Engineer

Level: Beginner

Subjects: Machine Learning, Data Analytics, Data Engineering, Data Integration, Data Management

Duration: 329 minutes

Explore the data warehousing process and learn how to load, monitor, secure, and query a warehouse in Microsoft Fabric.

Modules in this learning path:

• Introduction End Analytics Use Microsoft Fabric
• Get Started Data Warehouse
• Load Data Into Microsoft Fabric Data Warehouse
• Query Data Warehouse Microsoft Fabric
• Get Started Copilot Fabric Data Warehouse
• Monitor Fabric Data Warehouse
• Secure Data Warehouse in Microsoft Fabric

Products: Fabric

Roles: Data Analyst, Data Engineer

Level: Beginner

Subjects: Data Analytics, Data Engineering

Duration: 398 minutes

Implement a hybrid file server infrastructure using Azure Files and Azure File Sync, including cloud tiering, DFS Replication migration, and Storage Migration Services.

Units in this learning path:

• Introduction
• Describe Azure File Services
• Configure Azure Files
• Configure Connectivity Azure Files
• Describe Azure File Sync
• Implement Azure File Sync
• Deploy Azure File Sync
• Deploy Azure File Sync2
• Manage Cloud Tiering
• Migrate from Dfsr to Azure File Sync
• Knowledge Check
• Summary

Products: Azure, Azure Cloud Shell, Azure Files, Azure Portal, Azure Storage, Azure Virtual Machines

Roles: Administrator, Solution Architect, Technology Manager

Level: Intermediate

Duration: 92 minutes

Implement a non-relational data model

Units in this learning path:

• Introduction
• Whats Difference Between Nosql Relational Databases
• Identify Access Patterns for Your App
• When to Embed Reference Data
• Exercise Measure Performance for Customer Entities
• Choose Partition Key
• Model Small Lookup Tables
• Knowledge Check
• Summary

Products: Azure Cosmos Db

Roles: Developer

Level: Intermediate

Subjects: Data Modeling

Duration: 57 minutes

A practical approach to implementing generative AI responsibly, and exploring guardrails in AI Foundry portal.

Units in this learning path:

• Introduction
• Plan Responsible AI
• Identify Harms
• Measure Harms
• Mitigate Harms
• Operate Responsibly
• Exercise Content Filters
• Knowledge Check
• Summary

Products: Microsoft Foundry

Roles: AI Engineer, Developer, Solution Architect, Student

Level: Intermediate

Subjects: Artificial Intelligence

Duration: 45 minutes

Implement a secure environment for a database service

Modules in this learning path:

• Configure Database Authentication Authorization
• Protect Data Transit at Rest
• Implement Compliance Controls for Sensitive Data

Products: Azure, Azure SQL Database, SQL Server

Roles: Data Analyst, Data Engineer, Database Administrator

Level: Intermediate

Subjects: Security

Duration: 238 minutes

Learn to implement effective versioning strategies for packages using semantic versioning, package promotion workflows, and Azure Artifacts views to manage package quality and lifecycle.

Units in this learning path:

• Introduction
• Understand Versioning of Artifacts
• Explore Semantic Versioning
• Examine Release Views
• Promote Packages
• Explore Best Practices for Versioning
• Knowledge Check
• Summary

Products: Azure, Azure Artifacts, Azure Boards, Azure Cloud Services, Azure Devops, Azure Pipelines, Azure Repos, Azure Test Plans, Github

Roles: Administrator, AI Engineer, Data Engineer, Developer, Devops Engineer, Platform Engineer, Security Engineer, Security Operations Analyst, Service Adoption Specialist, Solution Architect, Startup Founder, Technology Manager

Level: Advanced

Subjects: Devops

Duration: 29 minutes

Explore how to use built-in Azure roles, managed identities, and RBAC-policy to control access to Azure resources. Identity is the key to secure solutions.

Units in this learning path:

• Introduction
• Assign Azure Roles
• Configure Custom Azure Roles
• Create Configure Managed Identities
• Access Managed Identities
• Analyze Azure Role Permissions
• Configure Azure Key Vault Rbac Policies
• Retrieve Objects from Azure Key Vault
• Knowledge Check
• Summary Resources

Products: Azure, Entra, Entra Id

Roles: Administrator, Identity Access Admin, Security Engineer

Level: Advanced

Subjects: Identity Access, Infrastructure, Security

Duration: 30 minutes

Implement access management for apps

Modules in this learning path:

• Plan Design Integration of Enterprise Apps for Sso
• Implement Monitor Integration of Enterprise Apps for Sso
• Implement App Registration
• Register Apps Use Microsoft Entra Id

Products: Azure, Entra, Entra Id

Roles: Administrator, Security Engineer

Level: Intermediate

Subjects: Identity Access

Duration: 154 minutes

Build a complete event collection and response architecture in Microsoft Sentinel. Set up and secure a Microsoft Sentinel workspace, deploy Content Hub solutions, connect Azure resource data, collect Linux and Windows security events with data collection rules, implement automated response workflows with Logic Apps playbooks, and manage data retention for compliance.

Modules in this learning path:

• Create Manage Azure Sentinel Workspaces
• Manage Content Microsoft Sentinel
• Connect Microsoft Services to Azure Sentinel
• Connect Syslog Data Sources to Azure Sentinel
• Connect Common Event Format Cef Logs to Azure Sentinel
• Connect Windows Hosts to Azure Sentinel
• Implement Automation Rules Playbooks Sentinel
• Manage Data Storage Audit Logs Sentinel

Products: Microsoft Sentinel, Defender Xdr, Azure Log Analytics, Azure Monitor

Roles: Security Engineer

Level: Intermediate

Subjects: Security, Cloud Security

Duration: 218 minutes

Implement advanced retrieval-augmented generation (RAG) pipelines for production AI agents using Azure AI Search and Microsoft Foundry. Design hybrid search architectures, implement reranking strategies, configure dynamic knowledge source routing, and optimize chunking and embedding strategies.

Units in this learning path:

• Introduction
• Design Hybrid Search Architectures
• Implement Rerank Context Rank
• Design Dynamic Knowledge Source Route
• Optimize Chunk Embed Strategies
• Knowledge Check
• Summary

Products: Azure, Microsoft Foundry, Azure Cognitive Search

Roles: AI Engineer, Solution Architect, Data Scientist

Level: Advanced

Subjects: Artificial Intelligence, Machine Learning

Duration: 41 minutes

Learn how to develop advanced flows in Power Automate for desktop.

Modules in this learning path:

• Pad Message Boxes
• Pad Flow Control
• Pad Text Manipulation
• Pad Mouse Keyboard
• Pad System Services Actions

Products: Power Platform, Power Automate

Roles: Maker, Developer, Functional Consultant

Level: Intermediate

Subjects: Process Workflow

Duration: 107 minutes