Free Certification Practice Questions

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 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 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 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 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 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 everyday, practical use of Claude: prompting and task execution, evaluating and refining output, selecting the right products and models, integrating Claude into workflows, setting up Projects and knowledge sources, applying responsible AI principles, and troubleshooting.

Validates hands-on building with Claude: integrating the Claude API, building agents and workflows, engineering prompts and context, evaluating and debugging outputs, selecting models and optimizing cost, building custom tools and MCP servers, and applying security and safety practices.

Validates advanced architecture at scale: designing enterprise solutions, architecting integrations, evaluating and optimizing systems, applying governance and risk management, leading stakeholders across the solution lifecycle, and enabling developer productivity and operations.