Official study guides, exam guides, and practice assessments from AWS, Azure, and Google Cloud.
Foundational understanding of AWS Cloud, services, and terminology.
Foundational knowledge of AI, ML, and generative AI concepts on AWS.
Design and deploy scalable, highly available, and fault-tolerant systems on AWS.
Develop and maintain applications on the AWS platform.
Deploy, manage, and operate workloads on AWS. Retired September 2025.
Ingest, transform, and orchestrate data pipelines on AWS.
Build, deploy, and maintain ML solutions on AWS at scale.
Advanced architecture skills for complex AWS solutions with 2+ years experience.
Provision, operate, and manage distributed application systems on AWS.
Advanced security skills for securing AWS workloads and infrastructure.
Design and implement AWS and hybrid IT network architectures at scale.
Build, train, and deploy ML solutions using AWS services.
Core Azure concepts, services, pricing, SLAs, and cloud concepts.
Foundational knowledge of AI and machine learning concepts on Azure.
Core data concepts and related Azure data services.
Implement, manage, and monitor identity, governance, storage, compute, and networks.
Build end-to-end Azure solutions with Functions, web apps, storage, security, and APIs.
Implement security controls and maintain security posture across Azure environments.
Design, implement, and maintain Azure networking: VNets, load balancers, routing, and security.
Train, deploy, and monitor ML models using Azure Machine Learning and MLflow.
Design and implement data engineering solutions using Azure Synapse, Databricks, and Data Factory.
Administer SQL Server and Azure SQL database environments in the cloud.
Implement and manage Microsoft Fabric analytics solutions.
Build AI solutions using Azure AI services, Azure AI Search, and Azure OpenAI.
Investigate, respond to, and hunt for threats using Microsoft Sentinel and Defender.
Design, implement, and operate identity and access management using Microsoft Entra ID.
Design cloud and hybrid solutions for compute, network, storage, monitoring, and security.
Design and implement DevOps practices: source control, CI/CD pipelines, security, and monitoring.
Plan, deliver, and manage virtual desktop experiences and remote apps on Azure.
Design and implement cloud-native applications using Azure Cosmos DB.
Core Google Cloud concepts and how cloud technology enables digital transformation.
Foundational knowledge of generative AI concepts and Google Cloud AI offerings.
Deploy apps, monitor operations, and manage enterprise solutions on Google Cloud.
Manage and configure Google Workspace for an organization.
Design, develop, and manage robust Google Cloud solutions aligned with business objectives.
Build scalable, highly available applications using Google-recommended practices.
Build and implement service monitoring strategies and optimize service performance on GCP.
Implement and manage networking infrastructure in Google Cloud.
Design and implement a secure infrastructure on Google Cloud Platform.
Design, create, migrate, and troubleshoot databases on Google Cloud.
Design and build data processing systems and leverage ML models on Google Cloud.
Design, build, and productionize ML models using Google Cloud technologies.