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Validates understanding of cloud concepts, core Azure services, and Azure management and governance.

Focuses on core data concepts and how they're implemented using Azure data services.

Covers fundamental concepts of artificial intelligence and how they are implemented on Azure.

The newly updated foundational certification for AI, ML, and emerging Generative AI architectures on the Azure platform.

Provides foundational knowledge of security, compliance, and identity concepts and services across Microsoft.

Validates skills in implementing, managing, and monitoring an organization's Microsoft Azure environment.

Focuses on designing, building, testing, and maintaining cloud applications and services on Azure.

Covers managing security posture, identifying and remediating vulnerabilities, and implementing threat protection.

Validates expertise in using cognitive services, machine learning, and knowledge mining to architect and implement AI solutions on Azure.

Focuses on integrating, transforming, and consolidating data from various structured and unstructured data systems into structures suitable for building analytics solutions.

Validates the ability to apply Azure's machine learning techniques to train, evaluate, and deploy models that solve business problems.

Covers implementing and managing the operational aspects of cloud-native and hybrid data platform solutions built with Microsoft SQL Server and Microsoft Azure Data Services.

Focuses on designing, implementing, and operating an organization's identity and access management systems using Azure AD.

Validates the ability to collaborate with organizational stakeholders to secure information technology systems.

Covers planning, implementing, and maintaining Azure networking solutions, including hybrid networking, connectivity, routing, security, and private access to Azure services.

Focuses on configuring and managing Windows Server on-premises, hybrid, and IaaS platform workloads.

Validates the ability to plan, deploy, package, update, and maintain the Azure Stack Hub infrastructure.

Validates expertise in designing cloud and hybrid solutions that run on Azure, including compute, network, storage, monitoring, and security.

Focuses on combining people, process, and technologies to continuously deliver valuable products and services that meet end user needs and business objectives.

Validates the ability to design and evolve the cybersecurity strategy to protect an organization's mission and business processes across all aspects of the enterprise architecture.

Focuses on leading successful implementations and focusing on how solutions address the broader business and technical needs of organizations.

Validates the ability to develop cloud and edge components of an Azure IoT solution.

Focuses on planning, delivering, and managing virtual desktop experiences and remote apps, for any device, on Azure.

Validates the ability to leverage Azure resources that include setting up and maintaining the SAP environment.

Covers designing, implementing, and monitoring cloud-native applications that store and manage data using Azure Cosmos DB.

Validates overall understanding of AWS Cloud, including core services, security, architecture, pricing, and support.

Introduced in 2024, this certification validates foundational knowledge of AI, ML, and generative AI concepts and use cases.

Validates the ability to design distributed systems on AWS.

Focuses on developing and maintaining applications on AWS.

Covers deployment, management, and operations on AWS.

Validates skills in implementing data pipelines and optimizing cost and performance on AWS.

Introduced in 2024, validates the ability to build, deploy, and maintain machine learning solutions on AWS.

Validates advanced expertise in designing distributed applications and systems on the AWS platform.

Focuses on provisioning, operating, and managing distributed application systems on the AWS platform.

Validates skills in complex networking tasks.

Focuses on designing and implementing AWS services to derive value from data.

Validates expertise in recommending, designing, and maintaining the optimal AWS database solution.

Validates expertise in building, training, tuning, and deploying machine learning models on AWS.

Focuses on securing data and workloads in the AWS Cloud.

Validates the ability to build, test, and publish Amazon Alexa skills.

Understanding of cloud technology and Google Cloud products. General cloud concepts, including digital transformation, infrastructure, and app modernization.

Deploying and managing GCP applications. Managing cloud solutions with the Google Cloud Console and command-line tools. Monitoring and maintaining GCP projects.

Designing and planning cloud solution architecture. Managing and provisioning infrastructure. Ensuring security, compliance, and reliability.

Building scalable and highly available applications. Using GCP managed services, CI/CD pipelines, and monitoring tools.

Applying Site Reliability Engineering (SRE) principles. Optimizing service performance. Implementing service monitoring.

Configuring identity and access management. Setting up network and data protection. Managing incident response and compliance.

Designing and implementing secure, scalable GCP networks. Configuring VPCs, hybrid connectivity, and network services.

Designing and building data processing systems. Operationalizing ML models. Ensuring quality, security, and compliance in data systems.

Framing ML problems and building solutions. Automating and orchestrating ML pipelines. Monitoring, optimizing, and maintaining models.

Managing Google Workspace (G Suite) environments. Controlling email, endpoint, and user access.

Designing and managing scalable cloud-native and hybrid databases. Ensuring availability, performance, and disaster recovery.

Deploying applications, monitoring systems, and maintaining infrastructure. Using observability tools to diagnose and resolve production issues.