Free Certification Practice Questions

The AWS Certified Cloud Practitioner validates foundational, high-level understanding of AWS Cloud, services, and terminology. Ideal for individuals new to AWS or in non-technical roles.

Validates your ability to design secure, resilient, high-performing, and cost-optimized solutions on AWS. Covers core services and architectural best practices.

Validates foundational knowledge of GitHub and its core features including Git, repositories, collaboration tools, project management, modern development practices, security, and the open-source community.

Validates foundational knowledge of Google Cloud, including digital transformation, data, AI and machine learning, infrastructure modernization, security, operations, and sustainability in business-focused cloud scenarios.

Validates foundational knowledge of cloud concepts and Microsoft Azure services, including Azure architecture, core services, security, management, governance, and cost management capabilities for entry-level cloud roles.

Validates foundational knowledge of Kubernetes and the broader cloud native ecosystem, including Kubernetes fundamentals, container orchestration, cloud native architecture, observability, and application delivery concepts.

Validates foundational IT support skills for mobile devices, networking, hardware, virtualization and cloud computing, and hardware and network troubleshooting aligned to the CompTIA A+ 220-1201 Core 1 V15 exam objectives.

Validates foundational Terraform and HCP Terraform knowledge for practitioners using Terraform 1.12, including official 004 exam domains covering IaC, fundamentals, workflows, configuration, modules, state management, maintenance tasks, and HCP Terraform collaboration.

Validates business-level knowledge of generative AI concepts, Google Cloud's generative AI offerings, techniques to improve model output, and secure, responsible AI strategy for organizational adoption.

Validates advanced practical knowledge of integrating foundation models into production applications and business workflows on AWS, including implementation, security, governance, optimization, and troubleshooting of generative AI solutions.

Validates the ability to design, develop, and manage robust, secure, scalable, highly available, and cost-effective solutions on Google Cloud that align with business objectives and architectural best practices.

Validates foundational understanding of artificial intelligence, machine learning, generative AI concepts, and AWS AI tools, with emphasis on practical business applications of AI on AWS.

Validates proficiency in developing, testing, deploying, and debugging AWS Cloud-based applications, including development with AWS services, security, deployment, and troubleshooting and optimization.

Validates the ability to implement data pipelines and to monitor, troubleshoot, and optimize cost and performance issues in accordance with best practices.

Validates the ability to build, operationalize, deploy, and maintain machine learning (ML) solutions and pipelines by using the AWS Cloud.

Validates skills and knowledge in monitoring and maintaining AWS workloads, implementing security controls and networking concepts, performing business continuity procedures, and implementing cost and performance optimizations.

Validates advanced technical skills and experience in designing optimized AWS solutions that are based on the AWS Well-Architected Framework.

Validates technical expertise in provisioning, operating, and managing distributed systems and services on AWS.

Validates the ability to design, implement, manage, and secure AWS and hybrid network architectures at scale.

Validates expertise in creating and implementing security solutions in the AWS Cloud.

Validates the ability to deploy and secure applications, services, and infrastructure; monitor operations across projects; and maintain enterprise solutions on Google Cloud to meet performance objectives.

Validates the ability to secure and manage data on Google Cloud by using data services for ingestion, transformation, pipeline management, analysis, machine learning, and visualization, with foundational understanding of core cloud concepts.

Validates the ability to design, create, manage, migrate, and troubleshoot Google Cloud databases used by applications to store and retrieve data while translating business and technical requirements into scalable, highly available, and cost-effective database solutions.

Validates the ability to design, build, test, deploy, and integrate scalable, secure, and reliable cloud-native applications on Google Cloud by using recommended tools, services, APIs, and observability practices.

Validates the ability to manage user accounts, core Google Workspace services, data governance, security policies, endpoints, and common operational issues to help teams collaborate and communicate safely and effectively.

Validates the ability to design, build, deploy, monitor, maintain, optimize, and secure data processing systems on Google Cloud for collection, transformation, storage, delivery, and analysis of data to support business and regulatory requirements.

Validates the ability to implement processes and capabilities throughout the systems development lifecycle on Google Cloud by using Google-recommended methodologies and tools to balance reliability with delivery speed and to optimize production systems and services for performance and cost.

Validates the ability to design, develop, and manage secure solutions on Google Cloud by using Google security technologies to configure access, secure communications, protect data, manage operations, and support compliance requirements.

Validates the ability to design, implement, and manage Google Cloud network infrastructure for high availability, scalability, resiliency, security, hybrid and multi-cloud connectivity, network operations, and cloud network security by using Google Cloud networking services and best practices.

Validates the ability to build, evaluate, productionize, optimize, and monitor AI and machine learning solutions on Google Cloud, including low-code AI, data and model collaboration, scalable model serving, ML pipelines, generative AI, and responsible AI practices.

Validates the ability to detect, monitor, analyze, investigate, and respond to security threats against workloads, endpoints, and infrastructure on Google Cloud, including detection rules, log ingestion and prioritization, orchestration, response automation, posture management, and threat intelligence.

Validates foundational knowledge of core data concepts and related Microsoft Azure data services, including relational and non-relational data, analytics workloads, and data visualization with Power BI.

Validates foundational knowledge of security, compliance, and identity concepts and related cloud-based Microsoft solutions, including Microsoft Entra, Microsoft security solutions, and Microsoft compliance solutions.

Validates the skills needed to implement, manage, monitor, and secure an organization's Microsoft Azure environment, including identities, governance, storage, compute, networking, backup, and operational monitoring.

Validates the skills needed to design, build, test, secure, monitor, and maintain cloud applications and services on Microsoft Azure, including compute, storage, security, monitoring, APIs, messaging, and event-driven integrations.

Validates the skills needed to implement security controls, maintain security posture, and identify and remediate vulnerabilities across Azure, hybrid, and multi-cloud environments, including identity, networking, compute, storage, databases, governance, threat protection, and security operations.

Validates the skills needed to plan, build, manage, and deploy AI apps and agentic solutions on Azure by using Microsoft Foundry, including generative AI, multimodal and vision workloads, text and speech solutions, retrieval and grounding pipelines, and information extraction.

Validates the skills needed to implement, manage, secure, monitor, optimize, automate, and maintain Microsoft Azure SQL and SQL Server database solutions across cloud, on-premises, and hybrid environments, including migration and HA/DR planning.

Validates the skills needed to design, implement, and maintain Azure networking solutions, including core network infrastructure, hybrid connectivity, application delivery, private access to Azure services, and network security for performance, resiliency, scale, and secure operations.

Validates the skills needed to design, create, and manage analytical assets in Microsoft Fabric, including preparing data, securing and maintaining analytics assets, and implementing and optimizing semantic models for enterprise-scale analytics solutions.

Validates the skills needed to implement data engineering solutions in Microsoft Fabric, including ingesting and transforming data, securing and managing analytics solutions, and monitoring and optimizing data engineering workloads for enterprise-scale analytics.

Validates the skills needed to plan, deliver, manage, and monitor virtual desktop experiences and remote apps on Microsoft Azure, including Azure Virtual Desktop infrastructure, identity and security, user environments and apps, and operational monitoring and maintenance.

Validates the skills needed to design and implement Microsoft DevOps solutions, including processes and communications, source control, build and release pipelines, security and compliance, and instrumentation across Azure, GitHub, and Azure DevOps environments.

Validates the skills needed to design cloud and hybrid solutions on Azure, including identity, governance, monitoring, data storage, business continuity, and infrastructure solutions aligned to the Azure Well-Architected Framework and Cloud Adoption Framework for Azure.

Validates the skills needed to plan, design, and deploy AI-powered business solutions using Microsoft platforms, including agentic-first architectures, Copilot and Foundry-based solutions, governance, ALM, monitoring, testing, security, and responsible AI practices.

Validates foundational knowledge of Microsoft 365 services, Microsoft 365 Copilot, and agent administration, including core Microsoft 365 objects and security features, data protection and governance with Microsoft Purview and Copilot, and basic administrative tasks for Copilot and agents.

Validates foundational skills for using generative AI productivity tools such as Microsoft 365 Copilot, Researcher, and Analyst to improve daily work, manage prompts and conversations, and draft and analyze business content without coding or app development.

Validates the ability to recognize opportunities for AI transformation, identify appropriate Microsoft AI tools and resources, plan AI adoption, optimize business processes, and align responsible AI investments with business goals by using Microsoft 365 Copilot, Azure AI services, and Microsoft Foundry without requiring coding skills.

Validates foundational knowledge of artificial intelligence concepts and Azure AI solutions, including responsible AI principles, AI model capabilities, common AI workloads, and implementation of generative AI, text, speech, vision, and information extraction solutions by using Microsoft Foundry.

Validates the ability to design, implement, and operate identity and access management solutions by using Microsoft Entra, including user and external identities, authentication and access management, workload identities, and identity governance across hybrid and cloud environments.

Validates the ability to manage a security operations environment, respond to incidents, and perform threat hunting by using Microsoft Defender XDR, Microsoft Sentinel, Microsoft Defender for Cloud, Microsoft Purview, Microsoft Entra ID, Kusto Query Language, and automation across multi-cloud and on-premises environments.

Validates the ability to translate cybersecurity strategy into capabilities that protect an organization's assets, business, and operations by designing, guiding implementation of, and maintaining security solutions that follow Zero Trust principles across identity, devices, data, AI, applications, network, infrastructure, DevOps, governance, risk and compliance, security operations, and security posture management.

Validates the ability to design, implement, and operate AI operations solutions on Azure by building MLOps infrastructure with Azure Machine Learning, managing model training, deployment, and monitoring lifecycles, implementing GenAIOps infrastructure with Microsoft Foundry, and optimizing generative AI quality, observability, and model performance by using GitHub Actions, Bicep, and Azure CLI.

Validates foundational Vault knowledge and skills for practitioners using Vault 1.16, including authentication methods, policies, tokens, leases, secrets engines, encryption as a service, core architecture, deployment models, and access management patterns such as Vault Agent and Vault Secrets Operator.

Validates expertise in automating software development workflows with GitHub Actions, including creating and managing workflows and actions, managing GitHub Actions at scale, and ensuring secure and efficient automation for organizations and enterprises.

Validates expertise in GitHub Advanced Security, including security features and functionality, secret scanning, dependency management and review, code scanning with CodeQL, and security best practices and remediation.

Validates expertise in administering GitHub Enterprise environments, including enterprise support, identity and authentication, deployment and licensing models, access and permissions, secure software development and compliance, GitHub Actions administration, and GitHub Packages management.

Validates expertise in using GitHub Copilot to improve software development productivity, quality, and security, including responsible AI use, Copilot features across plans, prompt engineering, data handling, privacy safeguards, and developer workflows.

Validates foundational knowledge of Kubernetes and cloud native security, including core Kubernetes security concepts, platform protection, threat modeling, and compliance frameworks used to secure cloud native environments.

Validates foundational knowledge of observability and practical skills using Prometheus, including core Prometheus concepts, querying, instrumentation, exporters, alerting, and dashboarding for cloud native applications and infrastructure.

Validates foundational knowledge of connecting, securing, and observing Kubernetes clusters using Cilium, including Cilium architecture, policy, service mesh, observability, installation, cluster mesh, eBPF, and external networking concepts.

Validates foundational knowledge of Backstage for internal developer platforms, including local development workflows, infrastructure and deployment concepts, catalog management, and customization of Backstage applications and plugins.

Validates foundational knowledge of Kyverno for Kubernetes policy management, including installation, CLI usage, applying policies, writing policy rules, and managing policy-driven security and compliance workflows in Kubernetes environments.

Validates foundational knowledge of GitOps principles, terminology, patterns, related practices, and tooling used to implement and manage GitOps-driven software delivery in cloud native environments.

Validates foundational knowledge of cloud native platform engineering, including platform architecture, declarative resource management, GitOps, CI/CD pipelines, observability, security, and developer experience concepts required to build and manage modern internal developer platforms at scale.

Validates foundational knowledge of observability concepts and OpenTelemetry, including telemetry data, semantic conventions, instrumentation, the OpenTelemetry API and SDK, Collector configuration and pipelines, and maintaining and debugging observability systems.

Validates foundational FinOps knowledge, including cloud cost challenges, FinOps principles, team collaboration, capabilities, lifecycle phases, and cloud billing concepts used to improve business value from cloud spend.

Validates foundational knowledge of Microsoft Power Platform, including its business value, environment management, Dataverse, Power Apps, Power Automate, and Power Pages capabilities used to build low-code business solutions.

Validates the ability to plan, build, extend, integrate, test, and manage enterprise-grade AI agent solutions by using Microsoft Copilot Studio, Power Platform, Microsoft 365 Copilot, and Azure-connected services.

Validates the ability to design, develop, test, and troubleshoot Microsoft Power Platform solution components by creating technical designs, building solutions, improving Power Apps, extending the user experience and platform, and developing integrations using Dataverse, Power Automate, developer tools, and Azure services.

Validates the ability to deliver actionable insights by preparing, modeling, visualizing, and analyzing data in Power BI and by managing and securing Power BI assets to enable business value and self-service analytics.

Validates the ability to integrate and model data, build and deploy optimized pipelines, and troubleshoot and maintain workloads in Azure Databricks by setting up Azure Databricks environments, securing and governing Unity Catalog objects, preparing and processing data, and deploying and maintaining data pipelines and workloads with SQL, Python, Git, Azure Data Factory, Microsoft Entra, and Azure Monitor.

Validates the ability to design and develop AI-enabled database solutions across Microsoft SQL platforms, including Microsoft SQL Server, Azure SQL, and SQL databases in Microsoft Fabric, by building database objects and advanced T-SQL solutions, securing and deploying SQL solutions with CI/CD and Azure integrations, and implementing AI capabilities such as embeddings, vector search, hybrid search, and retrieval-augmented generation.

Validates expertise in designing, implementing, deploying, and maintaining machine learning solutions using AWS Cloud services and ML concepts, including data engineering, exploratory data analysis, modeling, and ML operations.

Validates ability to navigate the Argo Project ecosystem including Argo Workflows, Argo CD, Argo Rollouts, and Argo Events, demonstrating understanding of when and why to use each tool for DevOps, GitOps, platform engineering, and cloud-native automation.

Validates foundational Consul knowledge and skills for practitioners using Consul 1.15, covering service networking pillars, Consul architecture and cluster components, single-datacenter deployment on VMs and Kubernetes, service discovery and health checks, service mesh with Envoy proxies and intentions, TLS and gossip encryption, ACL policies and tokens, multi-datacenter connectivity using gateways and cluster peering, observability of control plane and data plane, and cluster operations including upgrades, snapshots, and troubleshooting.

Validates proficiency with the Databricks Data Intelligence Platform for introductory data analysis tasks, including managing and discovering data with Unity Catalog, importing data via multiple methods, executing and optimizing SQL queries with Databricks SQL Warehouses, analyzing queries using auditing and Liquid clustering, creating dashboards and visualizations, developing and maintaining AI/BI Genie spaces, data modeling with Databricks SQL, and securing data through best practices.

Validates proficiency with the Databricks Data Intelligence Platform for introductory data engineering tasks, including understanding the platform architecture and multi-cloud workspace, performing ETL using Apache Spark SQL and PySpark, handling complex data transformations and user-defined functions, deploying and orchestrating workloads with Databricks Workflows, and applying data governance and quality practices with Unity Catalog.

Validates advanced skills in building, optimising, and maintaining production-grade data engineering solutions on the Databricks Data Intelligence Platform. Covers Delta Lake, Unity Catalog, Auto Loader, Lakeflow Spark Declarative Pipelines, Databricks Compute (including serverless), Lakeflow Jobs, and the Medallion Architecture. Assesses the ability to design secure, reliable, and cost-effective ETL pipelines, process complex data using Python and SQL, and apply best practices in schema management, observability, governance, and performance optimization. Also covers streaming workloads, workflow orchestration, DevOps and CI/CD, and deploying with the Databricks CLI, REST API, and Asset Bundles.

Validates foundational machine learning skills on the Databricks Data Intelligence Platform. Covers Databricks ML capabilities including AutoML, Unity Catalog for ML governance, and core MLflow features such as experiment tracking, the Model Registry, and model serving. Assesses exploratory data analysis, feature engineering, model training, hyperparameter tuning, model evaluation and selection, and model deployment patterns. All machine learning code in this exam is in Python; data manipulation tasks may use SQL.

Assesses the ability to design, implement, and manage enterprise-scale machine learning solutions using advanced Databricks platform capabilities. Covers building scalable ML pipelines with SparkML, implementing distributed training and hyperparameter tuning, leveraging advanced MLflow features, and utilizing Feature Store concepts for automated feature pipelines. Evaluates MLOps practices including testing strategies, environment management with Databricks Asset Bundles, automated retraining workflows, and monitoring using Lakehouse Monitoring for drift detection. Assesses deployment strategies, custom model serving, and model rollout management. All machine learning code in this exam is in Python.

Assesses an individual's ability to design and implement LLM-enabled solutions using Databricks. Covers problem decomposition, model and tool selection, and building comprehensive generative AI solutions. Evaluates Databricks-specific tooling including Vector Search for semantic similarity, Model Serving for deployment, MLflow for solution lifecycle management, and Unity Catalog for data governance. Candidates who pass can build and deploy performant RAG applications and LLM chains on Databricks. All machine learning code in this exam is in Python.

Validates essential IT support skills in operating systems, security, software troubleshooting, and operational procedures aligned to the CompTIA A+ 220-1202 Core 2 V15 exam objectives.

Validates advanced cybersecurity skills in security architecture, engineering, automation, monitoring, and incident response for security architects and senior security engineers across complex on-premises, cloud, and hybrid environments. Aligned to the CompTIA SecurityX CAS-005 V5 exam objectives.

Validates cybersecurity analyst skills in security operations, vulnerability management, incident response, and reporting, aligned to the CompTIA CySA+ CS0-003 exam objectives.

Validates hands-on cloud infrastructure skills including architecture, deployment, operations, security, DevOps fundamentals, and troubleshooting across multi-cloud environments, aligned to the CompTIA Cloud+ CV0-004 V4 exam objectives.

Validates the ability to secure AI systems, defend against AI-driven threats, and leverage AI responsibly within cybersecurity operations, covering AI concepts, securing AI deployments, AI-assisted security operations, and AI governance, risk, and compliance aligned to the CompTIA SecAI+ CY0-001 V1 exam objectives.

Validates essential networking skills including network concepts, implementation, operations, security, and troubleshooting aligned to the CompTIA Network+ N10-009 (V9) exam objectives.

Validates entry-level project management skills covering project life cycle phases, project management concepts, tools and documentation, and IT governance fundamentals, aligned to the CompTIA Project+ PK0-005 (V5) exam objectives.

Validates intermediate-level penetration testing skills covering all stages of a penetration test, including engagement management, reconnaissance, vulnerability discovery, attacks and exploits, and post-exploitation across modern attack surfaces such as cloud, web applications, APIs, and IoT. Aligned to the CompTIA PenTest+ PT0-003 (V3) exam objectives.

Validates early-career cybersecurity skills required for core security functions, including securing networks, applications, and devices, managing threats and vulnerabilities, implementing security architecture, conducting security operations and incident response, and overseeing security program governance and compliance. Aligned to the CompTIA Security+ SY0-701 (V7) exam objectives.

Validates skills in managing, securing, automating, and troubleshooting Linux systems in cloud and hybrid environments, covering system administration, containers, scripting, and orchestration aligned to the CompTIA Linux+ XK0-006 (V8) exam objectives.

Validates expertise in designing and implementing production-grade Claude applications. Covers agentic architecture with the Agent SDK, tool design and MCP integration, Claude Code configuration, prompt engineering for structured output, and context management for reliable AI systems.

Validates the ability to operate, supervise, and govern autonomous AI agents within GitHub-driven SDLC workflows, ensuring safe, reliable, and efficient software delivery through configuration, evaluation, and orchestration of agentic systems in production environments.

Validates hands-on expertise with Docker container technologies, covering orchestration with Docker Swarm, image lifecycle management, engine installation and configuration, networking, security, and storage across Docker and Mirantis Kubernetes Engine environments.

Validates knowledge and skills to configure, implement, and maintain the ServiceNow platform, including navigation, instance configuration, application collaboration, self-service automation, database management, and data integration.

Validates knowledge and skills to design, develop, and deploy applications on the ServiceNow platform, including data model design, user interface creation, security implementation, process automation, and external data integration.

Validates knowledge and skills to configure, implement, and maintain ServiceNow ITSM applications, including incident, problem, and change lifecycle management, service catalog and request fulfillment configuration, knowledge management, and CMDB integration.

Validates knowledge and skills to configure, implement, and maintain the ServiceNow Discovery application, including designing and troubleshooting patterns, managing Discovery processes and schedules, maintaining the CMDB with accurate CI data, and ensuring operational readiness for Discovery implementations.

Validates knowledge and skills to configure, implement, and maintain the ServiceNow Event Management application, including event processing, alert configuration, event source integration, operator workspace, dependency maps, and metric intelligence.

Validates knowledge and skills to configure, implement, and maintain the ServiceNow Service Mapping application, including designing and troubleshooting patterns, configuring service maps, integrating with Discovery and Event Management, and maintaining the CMDB to provide accurate service visibility.

Validates knowledge and skills to design, implement, and operationalize a ServiceNow CMDB supporting the CSDM framework, including CI class configuration, data ingestion methods, CMDB governance, insight and reporting, and CSDM fundamentals.

Validates knowledge and skills to configure, implement, and maintain the ServiceNow Customer Service Management application, including managing CSM data models, configuring case routing and assignment, overseeing case processes and workflows, and utilizing CSM workspaces, portals, service catalog, and analytics.

Validates knowledge and skills to configure, implement, and maintain the ServiceNow HR Service Delivery application, including HR system architecture, plugins, table structure, core HR applications, Employee Center, HR journeys, lifecycle events, and platform and contextual security for protecting HR data.

Validates knowledge and skills to configure, implement, and maintain the ServiceNow Field Service Management solution, including managing work order lifecycles, workforce scheduling, inventory, mobile app usage, agent feedback, contextual knowledge, and targeted communications.

Validates knowledge and skills to configure, implement, and maintain the ServiceNow Software Asset Management application, including managing software discovery, ensuring data integrity, reconciling license usage, maintaining compliance, and integrating software asset management processes.

Validates knowledge and skills to configure, implement, and maintain the ServiceNow Hardware Asset Management application, including managing hardware lifecycles, ensuring data integrity, automating asset processes, integrating IT asset management workflows, and overseeing hardware financial management.

Validates knowledge and skills to configure, implement, and maintain ServiceNow Risk, Policy and Compliance, and Audit Management applications, including managing entity frameworks, configuring compliance processes, supporting audits, and improving governance and risk operations.

Validates knowledge and skills to configure, implement, and maintain a ServiceNow Vulnerability Response instance, including managing vulnerability data, integrating with scanners, automating responses, and using workspaces, remediation workflows, and data visualization to enhance security operations.

Validates knowledge and skills to configure, implement, and maintain a ServiceNow Security Incident Response solution, including managing security incidents, integrating threat intelligence, automating responses, and using visualization tools to streamline incident response and post-incident reviews.

Validates knowledge and skills to configure, implement, and maintain the ServiceNow Third-party Risk Management application, including managing third-party risk processes, configuring assessments, setting up the third-party portal, and supporting workflows across broader GRC operations.

Validates knowledge and skills to configure, implement, and maintain ServiceNow Strategic Portfolio Management applications, including financials, resource planning, idea and demand processes, project management, portfolio planning, analytics, and integrated solutions to optimize decision-making and portfolio performance.

Validates knowledge and skills to administer a domain-separated ServiceNow instance, including domain configuration, data and process separation, foundational data management, and application support for effective multi-domain operations and governance.

Validates knowledge and skills to configure, implement, and maintain a ServiceNow Platform Analytics solution, including indicator and breakdown design, data collection, dashboard creation, and advanced analytics capabilities that support data-driven decision-making.

Validates knowledge and skills to support the development, management, and optimization of the Now Platform, including contributing to product roadmaps, integrating user feedback, and collaborating across functions to execute platform owner responsibilities under senior guidance.

Validates demonstrated mastery in designing scalable and sustainable architecture solutions on the ServiceNow platform, including CMDB and CSDM, technical governance, testing leading practices, go-live preparation, security architecture, data strategies, current and to-be architecture planning, platform data and integrations, and release and instance strategy.

Validates foundational knowledge of the Scrum framework, the Scrum Master accountabilities, and how to apply Scrum in Scrum Teams, aligned to the Professional Scrum Master I focus areas defined by Scrum.org.

Validates advanced ability as a Scrum Master to apply the Scrum framework, support Scrum Teams, and solve complex problems in the real world, requiring advanced Scrum knowledge and in-depth Scrum Master experience.

Validates knowledge of applying Artificial Intelligence as a Professional Scrum Master, including using AI tools and practices to enhance Scrum Team effectiveness, leveraging generative AI to facilitate collaboration and transparency, and applying AI responsibly and ethically, including its impact on the Definition of Done.

Validates knowledge of the Scrum framework and the ability to support and enable value creation and delivery as a Product Owner, bridging strategy and agile product management to create valuable products using Scrum, aligned to the Professional Scrum Product Owner I focus areas defined by Scrum.org.

Validates advanced knowledge of the Scrum framework, Product Owner accountabilities, and the ability to deliver value through agile product management, with emphasis on Managing Products with Agility and Evolving the Agile Organization, aligned to the Professional Scrum Product Owner II focus areas defined by Scrum.org.

Validates knowledge of applying Artificial Intelligence within the scope of Professional Scrum Product Ownership, including the ability to explore, evaluate, and integrate AI tools and practices to enhance product discovery, customer understanding, experimentation, and decision-making in a responsible and ethical manner.

Validates that a leader understands the value Agile can bring to a business and how to actively support agile teams, covering servant-leadership mindset, self-managing team enablement, organizational agility, and evidence-based management across the five Professional Scrum Competency focus areas defined by Scrum.org.

Validates that a leader has a fundamental understanding of the Evidence-Based Management (EBM) framework and can guide teams toward continuously improving customer outcomes, organizational capabilities and business results by identifying goals, using hypotheses to find improvement opportunities, performing experiments and applying the resulting learning, across the Professional Scrum Competency focus areas defined by Scrum.org.

Validates knowledge of how to deliver quality software using the Scrum framework while working in Scrum Teams, including self-managed development, design and architecture, programming, quality, testing, forecasting, release planning, and product value, with approximately 85% of questions drawn from the Developing and Delivering Products Professionally focus area.

Validates knowledge of the Nexus Framework as described in the Nexus Guide, including enabling multiple Scrum Teams to work from a single Product Backlog, coordinating cross-team dependencies, and delivering an Integrated Increment that meets a goal using the Nexus Integration Team, Nexus events, and Nexus artifacts.

Validates knowledge of how Scrum Teams can use Scrum with Kanban to support value creation and delivery, grounded in the Kanban Guide for Scrum Teams and the Scrum Guide.

Validates the ability to lead a Lean-Agile enterprise with SAFe, align strategy to execution, support product development flow and Lean Portfolio Management, and apply AI-empowered leadership to organizational change.

Validates the skills of individual team members working on an Agile Team in a SAFe organization to apply Lean-Agile principles and AI-empowered practices across the full delivery cycle: from team formation and PI Planning to iterating, delivering, and improving relentlessly on an Agile Release Train.

Validates the ability to serve as a SAFe Scrum Master / Team Coach who facilitates team and ART events, coaches Lean-Agile practices, removes impediments, supports high-performing Agile teams, and applies AI-empowered practices to improve flow and value delivery in a SAFe enterprise.

Validates the ability to maximize value delivery by defining and managing backlogs, driving PI Planning, aligning strategy with execution, supporting Team and ART events, and applying AI to accelerate product decision-making and value delivery in a SAFe enterprise.

Validates the ability to serve as a Release Train Engineer who facilitates ART events, aligns teams and stakeholders, supports PI Planning and execution, optimizes flow, fosters relentless improvement, coaches the ART, and applies AI-empowered practices to improve value delivery in a SAFe enterprise.

Validates the ability to serve as a SAFe Advanced Scrum Master who evolves the Scrum Master role, improves team flow, builds high-performing teams, addresses conflict, strengthens ART performance, and applies AI-empowered practices to support collaboration and value delivery in a SAFe enterprise.

Validates the ability to teach, coach, and guide enterprise-wide Lean-Agile transformations; implement SAFe across portfolios, Agile Release Trains, and large solutions; launch and coach ARTs; and apply AI-empowered practices to optimize flow, strategic insight, and change leadership at scale.

Validates the ability to deepen strategic transformation impact as an experienced SAFe Practice Consultant; engage and educate leaders, apply AI-native practices, accelerate portfolio flow, contextualize SAFe to enterprise needs, and lead sustainable organizational change.

This certification validates your ability to design, implement, and manage end-to-end security controls across Azure, hybrid, and AI-enabled environments to protect identities, data, applications, infrastructure, and maintain regulatory compliance.

Validates the ability to design, build, and implement AI solutions on Azure, with a focus on back-end services, scalable architectures, and the full development lifecycle, including containerized applications, Azure data services, eventing and messaging integration, security, monitoring, and troubleshooting.

Validates the ability of nontechnical business professionals to understand core cybersecurity concepts, recognize common cyber risks and threats, apply basic security practices to protect organizational data and systems, and report and respond appropriately to security incidents while maintaining privacy, accountability, and compliance in everyday work.

Validates the ability to deploy, configure, and validate advanced NVIDIA AI infrastructure across server bring-up, physical layer management, control plane installation, cluster verification, and system optimization.

Validates the ability to install, administer, manage workloads on, and troubleshoot NVIDIA AI infrastructure using Base Command Manager, Slurm, Kubernetes, Run:ai, and related system management tools.

Validates the ability to deploy, configure, optimize, troubleshoot, and automate NVIDIA AI networking infrastructure across Spectrum, InfiniBand, Kubernetes, and AI data center environments.

Validates foundational knowledge of AI concepts and of the infrastructure and operational considerations required to adopt NVIDIA accelerated computing solutions.

Validates the ability to use GPU-accelerated tools and libraries across end-to-end data science workflows, including data analysis, preparation, machine learning, GPU and cloud computing, and MLOps.

Validates foundational ability to use GPU-accelerated tools and libraries across end-to-end data science workflows from preparation and analysis through machine learning and introductory MLOps.

Validates the ability to design, train, fine-tune, optimize, deploy, and monitor large language models, applying distributed training techniques and acceleration strategies to deliver high-performance generative AI solutions responsibly.

Validates the ability to architect, develop, deploy, and govern advanced agentic AI solutions, with a focus on multi-agent interaction, distributed reasoning, scalability, and ethical safeguards.

Validates the foundational concepts for developing, integrating, and maintaining AI-driven applications using generative AI and large language models (LLMs) with NVIDIA solutions.

Validates the foundational skills needed to design, implement, and manage AI systems that synthesize and interpret data across text, image, and audio modalities.

Validates the ability to build, maintain, and optimize 3D content creation pipelines using OpenUSD across composition, content aggregation, customization, data exchange, data modeling, debugging, pipeline development, and visualization.

Validates foundational knowledge of cybersecurity concepts, network fundamentals, endpoint security, network security, cloud security, security operations, and identity security for individuals entering or transitioning into the cybersecurity field.

Validates knowledge and understanding of cybersecurity concepts and the skills required for basic application of the Palo Alto Networks portfolio of solutions and related technologies.

Validates knowledge and understanding of all products and services in the Palo Alto Networks network security solution and entry-level maintenance, configuration, installation, and deployment of these products.

Validates the knowledge and skills of experienced network security analysts and firewall administrators in object configuration creation and application, policy creation and application, centralized management, and operations using Strata Cloud Manager (SCM) and Strata Logging Service. The certification also validates the ability to improve security posture and perform troubleshooting.

Validates experienced network security engineers and firewall administrators on their knowledge and skills in configuration of PAN-OS networking, configuration of device settings, integration and automation, creation of object configurations, creation of policies, and management and operation of next-generation firewalls in network security environments.

This certification validates the knowledge and skills of experienced SD-WAN and SASE engineers across the Prisma SD-WAN lifecycle, and covers pre-deployment planning and architectural design, deployment, configuration, ongoing management, and advanced troubleshooting. The certification validates the ability to use Prisma SD-WAN components to achieve network transformation outcomes.

This certification validates experienced security service edge (SSE) engineers on their knowledge and skills in deployment configuration, post-deployment management and configuration, and their ability to participate in troubleshooting deployed Prisma Access environments. The certification also validates pre-deployment planning of Palo Alto Networks SSE component solutions and an understanding of their architecture to achieve network transformation outcomes.

This certification validates experienced network security architects on their skills and abilities in understanding technical and business requirements and architecting secure, highly available, and scalable systems with network security portfolio solutions and relevant third-party integrations. This certification goes beyond technical knowledge to confirm a candidate's ability to design, develop, and oversee complex security blueprints using industry frameworks that align to compliance requirements and business objectives.

Validates the knowledge, understanding, and job-ready skills required for basic application of the Palo Alto Networks Cortex portfolio of solutions and related technologies in a security operations center (SOC), including threats, alerts, incidents, vulnerability, and compliance.

Validates the knowledge and skills required to perform AI-driven incident investigation and response and perform alert handling using Cortex XSIAM. This certification validates incident investigation and response, use of automation playbooks, alert handling, threat hunting, vulnerability assessment, reporting, and compliance by using the Cortex XSIAM platform within a SOC, along with understanding the basic architecture, components, and operation of Cortex XSIAM.

Validates the job-ready skills required to demonstrate understanding of the basic architecture, components, and operation of Cortex XDR. This certification validates incident investigation and response, alert handling, threat hunting, vulnerability assessment, reporting, and compliance by using the Cortex XDR platform within a SOC.

Validates the knowledge and skills required to use the Palo Alto Networks XSIAM platform for installation, deployment configuration, post-deployment management and configuration, data source onboarding and integration configuration, playbook creation, and detection engineering.

Validates the knowledge and skills of experienced engineers in installation, deployment configuration, post-deployment management and configuration, data source onboarding, integration configuration, and detection engineering using Cortex XDR. The certification also validates the application of Cortex XDR architecture.

Validates the knowledge and skills required for skilled engineers to deploy, configure, manage, integrate, and troubleshoot Cortex XSOAR solutions in security operations environments.

Validates experienced security operations architects on their skills and abilities in understanding technical and business requirements and architecting secure, highly available, and scalable AI-driven security operations center systems with security operations portfolio solutions and relevant third-party integrations.

Validates the knowledge, skills, and abilities necessary for securing cloud environments with the Cortex Cloud platform. It is designed for current or aspiring Cloud Security administrators or SOC analysts who focus on key areas such as the Cortex Cloud platform, Cloud Runtime Security, Application Security, Cloud Posture Security, and SOC processes.

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