AI & machine learning

Claude Architect Foundations CCAR-F: 360 Practice Questions

Train architectural judgment with 4 focused sets and 2 timed mocks for the July 2026 Foundations exam guide.

AI & Machine LearningAmerican English6 套练习

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Claude Architect Foundations CCAR-F: 360 Practice Questions

课程概览

你将练习的内容

题目及解析语言:American English

考试参考AI & machine learning
本课程版本发布日期
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  • Diagnose agent-loop control, tool-result linking, coordinator routing, and session-state problems.
  • Choose tool and MCP interfaces that expose clear inputs, outputs, failure semantics, and appropriate capabilities.
  • Apply Claude Code memory, skills, path rules, planning, iterative feedback, and CI output contracts.
  • Design evidence-faithful structured extraction, semantic validation, and appropriate batch-processing strategies.
  • Preserve critical facts and source mappings while routing uncertainty and unresolved cases to human review.
  • Apply the five-domain blueprint in two timed sets without confusing a practice percentage with the official scaled score.

了解完整课程

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

  • 360 original questions across six practice tests.
  • Four focused sets of 60 questions covering orchestration, tool contracts, Claude Code workflows, structured output, escalation, and review.
  • Two different timed mocks, each with 60 questions and a 120-minute limit.
  • An explanation for every answer option, an overall explanation, a study prompt, and an official source link for further reading.

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

6 套练习. 360 道题.

01

Agent Loops, Orchestration and Recovery

60 道题120 分钟

02

Tool Contracts, MCP and Evidence Handoffs

60 道题120 分钟

03

Claude Code Workflows and Review Design

60 道题120 分钟

04

Structured Output, Escalation and Calibration

60 道题120 分钟

05

Timed Mock 1: Support, Code, CI and Extraction

60 道题120 分钟

06

Timed Mock 2: Research, Productivity, CI and Extraction

60 道题120 分钟

免费课程体验

先作答,再理解。

本课程的三道原创单选样题。作答仅在当前页面保留,离开后清除。

选择一个答案1 / 3

A client-tool agent receives assistant text explaining its next step and a tool_use block. stop_reason is tool_use. What should the application do next?

开始前的准备

  • Practical familiarity with Claude APIs, Claude Code, the Agent SDK, and MCP concepts.
  • Ability to read basic JSON, configuration examples, and short code-related scenarios.
  • Access to the publicly available official exam guide and technical documentation for follow-up study.
  • No exam registration, API purchase, or paid cloud environment is required to answer these practice questions.

适合哪些学习者

  • Solution architects preparing for Claude Certified Architect – Foundations (CCAR-F).
  • Engineers building or reviewing Claude-based production workflows and tool integrations.
  • Developers who want to test their understanding of context, evidence, reliability, and configuration tradeoffs.

常见问题

迈出下一步之前。

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