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    Free Practice Questions for Anthropic Claude Certified Architect – Professional (CCAR-P) Certification

    🔄 Last checked for updates August 3rd, 2026

    Study with 456 exam-style practice questions designed to help you prepare for the Anthropic Claude Certified Architect – Professional (CCAR-P). All questions are aligned with the latest exam guide and include detailed explanations to help you master the material.

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    Exam Details

    Key information about Anthropic Claude Certified Architect – Professional (CCAR-P)

    Official study guide

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    Question formats CertSafari offers
    • Multiple choice
    renewal:

    Free, non-proctored assessment

    exam code:

    CCAR-P

    exam format:

    Multiple-choice and multiple-response

    exam fee usd:

    175

    passing score:

    720 out of 1000

    prerequisites:

    Recommended: 3+ years in systems architecture/platform engineering, 6+ months hands-on with Claude/LLMs in production, software engineering best practices.

    delivery method:

    Online proctored or test center

    target audience:

    Mid- to senior-level solution architects, AI/ML engineers, technical leads, senior software engineers.

    time limit minutes:

    120

    number of questions:

    63

    certification validity months:

    12

    Exam Topics & Skills Assessed

    Skills measured (from the official study guide)

    Domain 1: Solution Design & Architecture

    Subdomain 1.1: Translate business problems into Claude-based AI solutions

    Translate business problems into Claude-based AI solutions

    Subdomain 1.2: Design end-to-end architectures

    Design end-to-end architectures (input → processing → output → feedback loops)

    Subdomain 1.3: Select appropriate architectural patterns

    Select appropriate architectural patterns (workflow, agentic, augmented LLM)

    Subdomain 1.4: Design multi-agent systems and orchestration strategies

    Design multi-agent systems and orchestration strategies

    Subdomain 1.5: Apply decomposition techniques for complex problem solving

    Apply decomposition techniques for complex problem solving

    Subdomain 1.6: Align solutions to business value pillars

    Align solutions to business value pillars (efficiency, transformation, productivity, cost, performance SLAs)

    Domain 2: Claude Models, Prompting & Context Engineering

    Subdomain 2.1: Select appropriate Claude models based on trade-offs

    Select appropriate Claude models based on trade-offs

    Subdomain 2.2: Design system prompts, templates, and guardrails

    Design system prompts, templates, and guardrails

    Subdomain 2.3: Apply prompt engineering techniques

    Apply prompt engineering techniques (zero-shot, few-shot, chain-of-thought)

    Subdomain 2.4: Optimize context windows and manage token usage

    Optimize context windows and manage token usage

    Subdomain 2.5: Implement prompt reuse strategies

    Implement prompt reuse strategies (caching, modular prompts, Skills)

    Domain 3: Integration

    Subdomain 3.1: Evaluate tool/agent configuration for capability bloat

    Evaluate tool/agent configuration for capability bloat

    Subdomain 3.2: Analyze authentication and authorization requirements to identify security gaps

    Analyze authentication and authorization requirements to identify security gaps

    Subdomain 3.3: Evaluate accuracy-latency trade-offs and justify configuration decisions

    Evaluate accuracy-latency trade-offs and justify configuration decisions

    Subdomain 3.4: Analyze observability challenges and select monitoring strategies at scale

    Analyze observability challenges and select monitoring strategies at scale

    Subdomain 3.5: Design a RAG pipeline with appropriate chunking and indexing strategies

    Design a RAG pipeline with appropriate chunking and indexing strategies

    Subdomain 3.6: Apply retrieval strategies matched to data shape and query pattern

    Apply retrieval strategies matched to data shape and query pattern

    Subdomain 3.7: Evaluate connection protocols and select the appropriate integration mechanism

    Evaluate connection protocols and select the appropriate integration mechanism (MCP, API/CLI, agent-to-agent)

    Subdomain 3.8: Evaluate progressive discovery vs. monolithic context strategy

    Evaluate progressive discovery vs. monolithic context strategy

    Domain 4: Evaluation, Testing & Optimization

    Subdomain 4.1: Define evaluation metrics

    Define evaluation metrics (accuracy, latency, cost, safety, security)

    Subdomain 4.2: Design evaluation datasets and test frameworks using mixed methodologies

    Design evaluation datasets and test frameworks using mixed methodologies

    Subdomain 4.3: Conduct A/B testing and iterative improvements

    Conduct A/B testing and iterative improvements

    Subdomain 4.4: Diagnose system issues

    Diagnose system issues (prompt failure, hallucinations, model mismatch)

    Subdomain 4.5: Optimize token usage, latency, and cost-performance trade-offs

    Optimize token usage, latency, and cost-performance trade-offs

    Subdomain 4.6: Monitor system performance using logging and observability tools

    Monitor system performance using logging and observability tools

    Domain 5: Governance, Safety & Risk Management

    Subdomain 5.1: Implement guardrails and safety controls

    Implement guardrails and safety controls

    Subdomain 5.2: Identify risks, limitations, and failure modes of LLM systems

    Identify risks, limitations, and failure modes of LLM systems

    Subdomain 5.3: Apply human-in-the-loop validation strategies

    Apply human-in-the-loop validation strategies

    Subdomain 5.4: Ensure compliance with regulations

    Ensure compliance with regulations (e.g., GDPR, HIPAA, FedRAMP)

    Subdomain 5.5: Address ethical AI considerations

    Address ethical AI considerations (bias, fairness, transparency)

    Domain 6: Stakeholder Communication & Lifecycle Management

    Subdomain 6.1: Conduct structured discovery and requirement gathering

    Conduct structured discovery and requirement gathering

    Subdomain 6.2: Communicate architectural decisions and trade-offs

    Communicate architectural decisions and trade-offs

    Subdomain 6.3: Manage stakeholder feedback loops and expectation alignment

    Manage stakeholder feedback loops and expectation alignment (including SLAs)

    Subdomain 6.4: Document architectures and provide implementation guidance

    Document architectures and provide implementation guidance

    Subdomain 6.5: Support lifecycle phases

    Support lifecycle phases (discovery, design, handoff, monitoring, iteration)

    Domain 7: Developer Productivity & Operational Enablement

    Subdomain 7.1: Configure Claude tools and environments for teams

    Configure Claude tools and environments for teams (e.g., Claude Code)

    Subdomain 7.2: Improve developer workflows using AI-assisted tooling

    Improve developer workflows using AI-assisted tooling

    Subdomain 7.3: Support debugging and operational issue resolution

    Support debugging and operational issue resolution

    Techniques & products

    Claude platform
    Claude API
    Claude models
    LLM-based systems
    AI solutions
    AI/ML
    RAG pipeline
    prompt engineering
    context engineering
    multi-agent systems
    orchestration
    system prompts
    prompt templates
    guardrails
    zero-shot prompting
    few-shot prompting
    chain-of-thought prompting
    context windows
    token usage
    prompt caching
    modular prompts
    Skills
    tool/agent configuration
    authentication
    authorization
    security
    observability
    monitoring
    chunking
    indexing
    retrieval strategies
    connection protocols
    MCP
    API/CLI
    agent-to-agent
    progressive discovery
    monolithic context strategy
    evaluation metrics
    accuracy
    latency
    cost
    safety
    evaluation datasets
    test frameworks
    A/B testing
    logging
    GDPR
    HIPAA
    FedRAMP
    ethical AI
    bias
    fairness
    transparency
    Claude Code

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