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Practice tests and hands-on labs for AI and cloud certifications

Exam-realistic mock tests, level-by-level courses, hands-on labs and graded projects for NVIDIA, Anthropic Claude, AWS and Google Cloud certifications. Fine-tune, serve, orchestrate and red-team on real GPUs, Kubernetes clusters and live LLM targets, graded as you go.

Built by working ML and platform engineers, and mapped to each exam’s official objectives.
37 certifications · 80 hands-on labs · no signup for samples
Practice mode65 questions · pass at 70%Immediate feedback
Claude Certified Architect - Practice Exam 1Question 12 of 65Submit Exam
Question 12

You are building a customer support resolution agent that autonomously handles ticket classification, response generation, and escalation. The agent uses Claude with tool calling in an agentic loop. How should the loop determine when to stop executing?

Continue the loop when stop_reason is 'tool_use' and terminate when stop_reason is 'end_turn'
Cap iterations at five and short-circuit even when stop_reason still says tool_use is requested
Run a sentiment classifier over recent turns and end the loop when sentiment becomes positive
Scan the assistant text for closing phrases like 'all set' or 'task complete' and treat them as a stop
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The GPU labs do: they run on NVIDIA GPU pods in the cloud with a full terminal in your browser. The Kubernetes labs run on a real cluster, and the red-team labs attack live LLM targets. Every lab has graded objectives that are checked automatically as you work, so you know exactly when you have met the target.

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