AI & machine learningAI & Machine Learning
Claude Certified Architect Professional: Practice Tests
专题练习与计时模拟
课程概览
题目及解析语言:American English
This course contains the use of artificial intelligence.
A Claude solution can look convincing and still fail at a crucial boundary: a tool result is attached to the wrong request, an approval is mistaken for execution, a subagent receives a conclusion without its evidence, or a valid JSON record contains the wrong business values. This course helps you practise recognizing those conditions and choosing a proportionate fix.
Prepare for Claude Certified Architect – Foundations, exam code CCAR-F, using the five domains and 30 task statements in Anthropic's Exam Guide v1.0, effective July 2026. The questions focus on the Claude Agent SDK, Claude Code, tool and MCP interfaces, structured extraction, context management, and production reliability.
What is included
The mocks use four production contexts each. The first combines customer support, code generation, continuous integration, and structured extraction. The second combines multi-agent research, developer productivity, continuous integration, and structured extraction. Both approximate the guide's domain weights with 16, 11, 12, 12, and 9 questions across the five domains. They include single-answer and multiple-response questions; every multiple-response item states how many answers to select.
How to study
Start with a focused set and work through short groups of questions. For each mistake, identify the condition that made your chosen option fail. Revisit the linked official material, then explain how the answer would change if the prerequisite, evidence, scope, or latency constraint changed. Complete the timed mocks after this review, and examine incorrect options as carefully as correct ones.
The 80% practice target is a learning goal. Anthropic reports a passing scaled score of 720 on a 100–1,000 scale; this course does not convert that score into a raw percentage. Notes distinguish the July guide's terminology from relevant current product behavior, including subagent context inheritance and skill tool permissions.
These are independent original practice questions. The course is not affiliated with or endorsed by Anthropic, does not reproduce live exam questions, and does not guarantee certification. It supplements hands-on experience rather than replacing it.
练习安排
60 道题120 分钟
60 道题120 分钟
60 道题120 分钟
60 道题120 分钟
60 道题120 分钟
60 道题120 分钟
免费课程体验
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AI & machine learningAI & Machine Learning
专题练习与计时模拟
AI & machine learningAI & Machine Learning
专题练习与计时模拟
AI & machine learningAI & Machine Learning
专题练习与计时模拟