Claude Certified Architect – Professional
9 chapters and 1,074 original practice questions, with explanations, mock exams and mistake review. These are one study product, not separate purchases.
Professional 不是 Foundations 的加难版,是另一门考试。RAG、合规(GDPR/HIPAA/FedRAMP)、干系人沟通——这三块在 Foundations 的考纲里一个字都没出现,在这里合计超过 40%。考的不是你会不会造,是你怎么做架构决策、集成、评估、治理与交付。
Certification orientation, course guidance and applied learning across the exam domains.
Practise topics and scenarios rather than memorising answers. Bank size is separate from the official exam length.
Understand why the correct answer works and which conditions the alternatives fail to meet.
Check knowledge and pacing through a complete exam flow, then use the results to plan revision.
Revisit incorrect answers and their underlying concepts, organised by exam domain.
Review learning and practice records to see what is complete and what needs reinforcement.
A sample of the study product, not official exam questions or a guarantee of passing.
63 题 120 分钟,720 量表分及格(不是答对 72%),四门里题量最多、节奏最紧。官方不设前置,不要求先考 CCAR-F。RAG、合规、干系人沟通在 F 的考纲里出现 0 次,在这里合计超 40%。证书 12 个月有效期,报名走 Partner Academy,个人无法自助注册,考试费需自付。
17% 权重。把业务问题翻译成端到端 Claude 方案,在 workflow / agentic / augmented LLM 之间选对模式,设计多 agent 编排,并把方案对齐业务价值支柱(效率、成本、性能 SLA)。CCAR-F 也讲架构,但这里的重点是"选型与对齐业务价值"的决策角度,不是"怎么把 agentic loop 写对"。
Solution Design & Architecture
13% 权重。在 CCAR-F 里 Prompt 是一整个域(20%),这里被压缩进"模型选型 + prompt + 上下文工程"合并的 13%。考的是按取舍选 Claude 模型、设计 system prompt 与护栏、优化上下文窗口与 token 用量、用 caching / 模块化 prompt / Skills 做复用——从架构决策而非 prompt 技巧的角度。
Claude Models, Prompting & Context Engineering
19% 权重,七域之首。核心是 CCAR-F 完全不考的 RAG 流水线设计(chunking / indexing / 检索策略),CCAR-F 甚至把向量库实现列进 out-of-scope。还考评估工具配置的能力膨胀、认证授权的安全缺口、准确率与延迟取舍、规模化下的可观测性,以及在 MCP / API-CLI / agent-to-agent 之间选对集成机制。从 F 过来的人这一整块几乎要从零学。
Integration
16% 权重。定义评估指标(准确率、延迟、成本、安全),用混合方法设计评估数据集与测试框架,做 A/B 测试与迭代改进,诊断 prompt 失败 / 幻觉 / 模型不匹配,并用日志与可观测性工具监控表现。A/B 测试在 CCAR-F 里 0 次出现,可观测性也只提过一次——这里是系统化考点,F 过来的人没练过。
Evaluation, Testing & Optimization
14% 权重。护栏与安全控制、识别 LLM 系统的风险与失败模式、human-in-the-loop 校验,以及合规(GDPR、HIPAA、FedRAMP)与 AI 伦理(偏见、公平性、透明度)。GDPR / HIPAA / FedRAMP 三个词在 CCAR-F 的考纲里全部 0 次出现——这是 F 完全不覆盖、却决定能不能在受监管行业落地的一块。
Governance, Safety & Risk Management
14% 权重,几乎是一整块纯软技能:结构化需求发现、把架构取舍讲清楚、管理反馈闭环与 SLA 期望、写架构文档、支撑 discovery → design → handoff → monitoring → iteration 全周期。"stakeholder" 在 CCAR-F 的考纲里 0 次出现。这是技术考生最容易丢分、中文备考材料几乎空白的一域——CCAR-F 持证人在这里完全没有既有积累,也是最值得专门练的地方。
Stakeholder Communication & Lifecycle Management
7% 权重,七域里最轻。为团队配置 Claude 工具与环境(如 Claude Code)、用 AI 辅助工具改进开发者工作流、支持调试与运维排障。注意反差:Claude Code 在 CCAR-F 是一整个域(20%),到了 CCAR-P 只剩这 7% 的一部分。按 F 的比重在这上面花时间就本末倒置了。
Developer Productivity & Operational Enablement
"从 F 过来要重学什么"的权重地图、常见错误答案类型(过度工程、事后补救代替最小权限、根因错归),63 题 / 120 分钟的时间预算与排除法策略,以及 OnVUE 考场自检。两套全真模拟(63 题 / 120 分钟)+ 逐题详解 + 七域得分分布,稳定 720+ 再进考场。
"It's midnight and I've read this explanation three times without getting it. There's no one to ask, and the answers I find online don't match…"
The Claude 架构师 Professional AI tutor is always on, ready wherever you're stuck. Not generic ChatGPT — it explains this exact question and this exam domain precisely.
When the explanation still doesn't click
Ask about the wording of your chosen option and the constraint it misses.
When concepts blur together
The AI uses comparisons and real scenarios to clear it up. Not memorising definitions — truly understanding.
When prep hits the final sprint
The AI reads your mistake patterns and tells you which domains are weakest and what to review first.
Preset conversation examples. No live AI request and no credits used. Full AI Tutor requires access and uses credits.
CCAR-P 面向做端到端交付的技术负责人——解决方案架构师、AI/ML 工程师、资深工程师。官方建议 3+ 年系统架构或平台工程经验、至少 6 个月在生产环境跑过 Claude 或同类 LLM 系统,交付过从 discovery 到运营化的完整方案。日常要跟安全、法务、高管过会。
考的是决策与交付,不是"怎么造"。同一个客服 agent,能读工单、起草回复、发起退款、删除账号,但客服人员只需要读工单和起草回复——按最小权限该怎么改?正确答案是把退款和删除工具从 agent 配置里彻底移除,而不是加日志、加确认弹窗、换个更听话的模型。
| 域 | 权重 |
|---|---|
| Integration(含 RAG、MCP、认证授权、可观测性) | 19% |
| Solution Design & Architecture | 17% |
| Evaluation, Testing & Optimization | 16% |
| Governance, Safety & Risk Management | 14% |
| Stakeholder Communication & Lifecycle Management | 14% |
| Claude Models, Prompting & Context Engineering | 13% |
| Developer Productivity & Operational Enablement | 7% |
我们把两份官方 Exam Guide 逐词比对过(区分大小写、加词边界):
Integration 19% + Governance 14% + Stakeholder 14% = 47%,全是 CCAR-F 不考的东西。反过来,Claude Code 在 CCAR-F 是一整个域(20%),在 CCAR-P 只占 7%。按 F 的方法复习 P,等于把近一半考点当空气。
结构化需求发现、把架构取舍讲清楚、管理反馈闭环与 SLA 期望、写架构文档、支撑 discovery → design → handoff → monitoring → iteration 全周期。这在技术认证里很罕见,也是华人技术考生最容易轻视、中文备考材料几乎空白的一块。
63 题 / 120 分钟,每题不到 2 分钟,是四门 Claude 认证里节奏最紧的。时间预算与排除法在这门里价值最大。
Anthropic Partner Academy 不对个人开放自助注册,需由 Claude Partner Network 成员开通账号。账号开通后,由你本人在 Partner Academy 注册考试并直接向 Anthropic 支付官方考试费,再建 Pearson VUE 账号约考。考试费不包含在任何课程价格内。
63 道题,120 分钟——是四门 Claude 认证里题量最多、节奏最紧的一门,平均每题不到 2 分钟。题型是单选与多选混合,每道多选题会标明该选几个。满分制为 100–1000 的量表分,720 分及格。注意:720 是量表分,不是"答对 72%",它由正式的 standard-setting 研究定出。成绩单会附各 domain 的答对百分比,但那只用于诊断,不参与判定通过与否,所以不存在"每个域都要过线"这回事。
不需要。官方原话是"There are no mandatory prerequisites or courses required to sit this exam"——四门 Claude 认证互不设前置,Professional 不要求先考 Foundations。任何"必须先考 F 才能考 P"的说法都不准确。真实的分流依据是经验与岗位,见下一条。
看你的岗位,不看难度阶梯。CCAR-F 考的是"怎么造"——agentic loop、多 agent 编排、MCP 工具设计、Claude Code 配置;面向用 Claude 搭生产应用的架构师。CCAR-P 考的是"怎么决策与交付"——架构选型、集成(含 RAG)、评估、治理、干系人沟通;面向 3+ 年架构经验、做端到端交付、要跟安全法务高管过会的技术负责人。两门的考纲差异比想象中大:RAG、合规、干系人沟通这些词在 CCAR-F 的考纲里一次都没出现过,在 CCAR-P 里合计超过 40% 的权重。如果你从没在生产环境跑过 Claude,两门都别急。
不能自助报名。Anthropic Partner Academy 不对个人开放自助注册,必须由已加入 Claude Partner Network 的伙伴在后台为你开通账号。账号开通后,由你本人在 Partner Academy 注册考试并直接向 Anthropic 支付官方考试费(结账价会反映所属 partner tier 的折扣),再建 Pearson VUE 账号选择线上监考或线下考场。考试费不包含在任何课程或会员价格里,需要你在结账时自行支付——这一点报名前就要清楚。
自授予日起 12 个月,不是终身有效。在到期之前,你只需复习考纲变更点并在 Partner Academy 完成一次免费的、非监考的续证评估即可续期,不收费。但一旦过期,就必须全价重考。如果考纲发生重大变更,Anthropic 也可以要求持证人重考而不是走续证评估。
可以,但有冷却期:第 1 次不通过后等 14 天,第 2 次后等 30 天,第 3 次后等 90 天。滚动 12 个月内同一门最多考 4 次,且每次都要重新支付考试费。这个限制按单门计算——这门没过不影响你报考另外三门中的任何一门。
全部原创。官方考纲里附了若干道带解析的样题,那是 Anthropic 的版权内容,我们不会把它们(原文或翻译)放进题库,也不照抄题干情境、选项措辞和干扰项设计。它们只被用作难度与命题风格的校准样本。我们的题按官方七域权重分布出卷,考的是"最小权限该怎么改""这个集成协议选哪个更合理"这类架构决策判断题,而不是背 API 名字。
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