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The Microsoft Azure - Fundamentals Exam AZ-900
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Microsoft Certified: Azure - Fundamentals Exam AZ-900 Syllabus
Describe cloud concepts (25–30%)
Describe cloud computing
- Define cloud computing
- Describe the shared responsibility model
- Define cloud models, including public, private, and hybrid
- Identify appropriate use cases for each cloud model
- Describe the consumption-based model
- Compare cloud pricing models
Describe the benefits of using cloud services
- Describe the benefits of high availability and scalability in the cloud
- Describe the benefits of reliability and predictability in the cloud
- Describe the benefits of security and governance in the cloud
- Describe the benefits of manageability in the cloud
Describe cloud service types
- Describe infrastructure as a service (IaaS)
- Describe platform as a service (PaaS)
- Describe software as a service (SaaS)
- Identify appropriate use cases for each cloud service (IaaS, PaaS, SaaS)
Describe Azure architecture and services (35–40%)
Describe the core architectural components of Azure
- Describe Azure regions, region pairs, and sovereign regions
- Describe availability zones
- Describe Azure datacenters
- Describe Azure resources and resource groups
- Describe subscriptions
- Describe management groups
- Describe the hierarchy of resource groups, subscriptions, and management groups
Describe Azure compute and networking services
- Compare compute types, including container instances, virtual machines (VMs), and functions
- Describe VM options, including Azure Virtual Machines, Azure Virtual Machine Scale Sets, availability sets, and Azure Virtual Desktop
- Describe resources required for virtual machines
- Describe application hosting options, including the Web Apps feature of Azure App Service,
containers, and virtual machines
- Describe virtual networking, including the purpose of Azure Virtual Networks, Azure virtual subnets, peering, Azure DNS, Azure VPN Gateway, and Azure ExpressRoute
- Define public and private endpoints
Describe Azure storage services
- Compare Azure storage services
- Describe storage tiersd
- Describe redundancy options
- Describe storage account options and storage types
- Identify options for moving files, including AzCopy, Azure Storage Explorer, and Azure File Sync
- Describe migration options, including Azure Migrate and Azure Data Box
Describe Azure identity, access, and security
- Describe directory services in Azure, including Microsoft Azure Active Directory (Azure AD), part
of Microsoft Entra and Azure Active Directory Domain Services (Azure AD DS)
- Describe authentication methods in Azure, including single sign-on (SSO), multifactor
authentication, and passwordless
- Describe external identities and guest access in Azure
- Describe Conditional Access in Microsoft Azure Active Directory (Azure AD), part of Microsoft
- Describe Azure role-based access control (RBAC)
- Describe the concept of Zero Trust
- Describe the purpose of the defense in depth model
- Describe the purpose of Microsoft Defender for Cloud
Describe Azure management and governance (30–35%)
Describe cost management in Azure
- Describe factors that can affect costs in Azure
- Compare the Pricing calculator and the Total Cost of Ownership (TCO) calculator
- Describe the Azure Cost Management and Billing tool
- Describe the purpose of tags
Describe features and tools in Azure for governance and compliance
- Describe the purpose of Azure Blueprints
- Describe the purpose of Azure Policy
- Describe the purpose of resource locks
- Describe the purpose of the Service Trust Portal
Describe features and tools for managing and deploying Azure resources
- Describe the Azure portal
- Describe Azure Cloud Shell, including Azure CLI and Azure PowerShell
- Describe the purpose of Azure Arc
- Describe Azure Resource Manager and Azure Resource Manager templates (ARM templates)
- Configure backup and recovery of certificates, secrets, and keys
Describe monitoring tools in Azure
- Describe the purpose of Azure Advisor
- Describe Azure Service Health
- Describe Azure Monitor, including Log Analytics, Azure Monitor alerts, and Application Insights
Describe Artificial Intelligence workloads and considerations (20-25%)
Identify features of common AI workloads
- Identify features of anomaly detection workloads
- Identify computer vision workloads
- Identify natural language processing workloads
- Identify knowledge mining workloads
Identify guiding principles for responsible AI
- Describe considerations for fairness in an AI solution
- Describe considerations for reliability and safety in an AI solution
- Describe considerations for privacy and security in an AI solution
- Describe considerations for inclusiveness in an AI solution
- Describe considerations for transparency in an AI solution
- Describe considerations for accountability in an AI solution
Describe fundamental principles of machine learning on Azure (25-30%)
Identify common machine learning types
- Identify regression machine learning scenarios
- Identify classification machine learning scenarios
- Identify clustering machine learning scenarios
Describe core machine learning concepts
- Identify features and labels in a dataset for machine learning
- Describe how training and validation datasets are used in machine learning
Describe capabilities of visual tools in Azure Machine Learning studio
- Automated machine learning
- Azure Machine Learning designer
Describe features of computer vision workloads on Azure (15-20%)
Identify common types of computer vision solution
- Identify features of image classification solutions
- Identify features of object detection solutions
- Identify features of optical character recognition solutions
- Identify features of facial detection and facial analysis solutions
Identify Azure tools and services for computer vision tasks
- Identify capabilities of the Computer Vision service
- Identify capabilities of the Custom Vision service
- Identify capabilities of the Face service
- Identify capabilities of the Form Recognizer service
Describe features of Natural Language Processing (NLP) workloads on Azure (25-30%)
Identify features of common NLP Workload Scenarios
- Identify features and uses for key phrase extraction
- Identify features and uses for entity recognition
- Identify features and uses for sentiment analysis
- Identify features and uses for language modeling
- Identify features and uses for speech recognition and synthesis
- Identify features and uses for translation
Identify Azure tools and services for NLP workloads
- Identify capabilities of the Language service
- Identify capabilities of the Speech service
- Identify capabilities of the Translator service
Identify considerations for conversational AI solutions on Azure
- Identify features and uses for bots
- Identify capabilities of the Power Virtual Agents and Azure Bot service
