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| Section | Weight | Objectives |
|---|---|---|
| Output Evaluation and Validation | 21% | - Edit and adapt outputs for the intended audience - Evaluate Claude-generated outputs for accuracy and completeness - Apply fact-checking and validation techniques - Determine when human review or additional verification is required - Identify hallucinations, inconsistencies, and biases in responses - Organize and curate information and select appropriate output formats |
| Product and Model Selection | 12% | - Differentiate between Claude model types - Select appropriate Claude product features - Align model selection with task requirements - Manage context limitations and memory |
| Governance, Risk, and Responsible Use | 15% | - Follow organizational AI policies and governance standards - Apply data sensitivity, regulatory, and privacy considerations - Understand ethical implications of Claude use - Identify appropriate and inappropriate use cases |
| Troubleshooting and Optimization | 10% | - Adjust approaches based on feedback and results - Identify and diagnose issues with underperforming prompts or poor outputs - Optimize workflows for efficiency and effectiveness |
| Prompting and Task Execution | 14% | - Create effective prompts for business and technical tasks - Apply task decomposition techniques to structure complex requests - Iterate prompts to improve output quality - Adapt prompting strategy by task type |
| Workflow Integration and Solution Design | 16% | - Use Claude for research, planning, and process optimization - Integrate Claude into existing workflows and communicate its value and limitations - Analyze requirements and use cases - Support solution design through iteration |
| Configuration and Knowledge Management | 12% | - Create effective system-level instructions - Maintain and update configurations - Manage uploaded knowledge and connectors - Configure Claude Projects with instructions and knowledge sources |
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質問 # 44
A finance manager must select a Claude feature for a task that requires deterministic calculations across a multi-tab spreadsheet.
Which selection best fits the requirement?
正解：D
解説：
Code Execution is the appropriate feature because it can run Python or shell-based computation in a sandboxed environment, process uploaded files, perform complex calculations, and generate analytical outputs. For a multi-tab spreadsheet, Claude can use code to read each worksheet, apply defined formulas or transformation logic, reconcile values, and return results that can be reproduced and inspected.
A normal chat response can describe calculations but does not necessarily execute them. Research mode is designed to gather and synthesize information from sources rather than serve as the primary calculation engine for an uploaded workbook. An Artifact can display or preserve an output, but the Artifact surface alone is not the computational mechanism.
Code execution improves reproducibility, but it does not guarantee that the formulas, assumptions, or source data are correct. The finance manager must review the generated code, validate important totals against known values, test edge cases, and reconcile outputs with the workbook's business rules. Anthropic's documentation explicitly states that Code Execution can analyze data, process uploaded files, perform complex calculations, and create visualizations in a secure sandbox. Therefore, D is the only feature selection aligned with deterministic spreadsheet computation. Anthropic's Code Execution documentation
質問 # 45
A business analyst has been asked to use Claude to extract requirements from a recorded stakeholder interview transcript. The transcript is approximately 90 minutes long and covers multiple topics.
Which approach is most likely to produce a usable structured output?
正解：D
解説：
Under the objective Create effective prompts for business and technical tasks , prompting Claude for complex analysis requires clear framing, explicit task decomposition, and structural schema constraints.
Transcripts from 90-minute interviews contain unstructured, conversational discussions spanning multiple priorities, assumptions, and debates. Providing the raw source material alongside a structured schema- specifying categories such as must-haves, nice-to-haves, unresolved open questions, and stakeholder conflicts (Option A)-enables Claude to parse and categorize information accurately without losing critical context. In contrast, forcing a single flat list (Option B) flattens priority nuances and obscures conflicts. Summarizing first (Option C) introduces unnecessary loss of detail and risks compounding omissions in the second pass.
Parsing every statement containing a verb (Option D) creates extreme token noise and unworkable overhead.
質問 # 46
You are reviewing a Claude-generated competitor brief for unsupported claims.
Which is the correct order of review steps?
(1) Cross-check each specific claim against the supplied source material or trusted external references.
(2) Decide whether to correct, re-prompt, or escalate based on the findings.
(3) Document each unsupported or inconsistent claim with its location and severity.
(4) Identify the specific factual claims, statistics, and citations in the brief.
(5) Read the brief from beginning to end and flag any claims that feel surprising.
正解：B
解説：
Answer C is correct. A defensible fact-check begins with a complete reading of the brief (5), which reveals its overall argument and flags surprising or unusually confident assertions. The reviewer then identifies the concrete factual claims, statistics, and citations that can actually be tested (4). Those items are checked against supplied evidence or trustworthy external sources (1). Any unsupported, contradictory, or inaccurate claim is then recorded with its location and severity (3), creating a usable audit trail. Only after the evidence is assembled should the reviewer decide whether to correct the text, re-prompt Claude, or escalate the issue (2).
This produces the sequence 5, 4, 1, 3, 2. Option D reverses the first two activities, while Options A and B attempt verification before a proper claim inventory exists. Anthropic's guidance recommends structured research, explicit success criteria, and verification across sources; the AI Fluency framework's Discernment and Diligence competencies also keep evaluation and accountability with the human reviewer. The PDF marks D, but that order is weaker and should be corrected to C. Anthropic prompting best practices
質問 # 47
You are a communications specialist preparing to describe Claude's role in a workflow to multiple stakeholder groups and must complete the preparation steps before drafting messages.
Which two preparation steps must be completed BEFORE drafting the stakeholder messages? (Select two.) Each correct answer presents part of the solution.
正解：C、E
解説：
Under the Claude objective Communicate Claude's value and limitations to stakeholders , crafting effective change-management and enablement communications requires establishing core positioning and audience segmentation prior to drafting content.
Before composing stakeholder updates, the specialist must first define the core ground truth: what specific operational role Claude plays, what tasks it augments, and what strict boundaries or limitations exist (Option C), including human review requirements and non-delegable tasks. Simultaneously, the specialist must segment audience cohorts (e.g., leadership, end users, compliance teams) to identify their distinct concerns, technical familiarity, and required takeaways (Option B). Establishing these two pillars ensures that communications are accurate, targeted, and set realistic expectations. Post-drafting activities such as sending materials (Option D), archiving (Option A), or hosting follow-up forums (Option E) occur only after foundational messaging is developed.
質問 # 48
A finance manager is about to discuss a confidential pre-announcement figure with Claude.
Which two settings best align with sound privacy practice for this conversation? (Select two.) Each correct answer presents a complete solution.
正解：B、C
解説：
Under the objective Apply data, privacy sensitivity, regulatory policies, and privacy considerations , managing confidential or market-sensitive figures requires controlling memory persistence and data retention settings.
Pre-announcement financial figures represent material non-public information (MNPI) that must not persist beyond the immediate analytical session. Option E applies privacy controls by utilizing Incognito mode, which ensures the session does not contribute to long-term memory or persist in chat history. Option B achieves the same data protection control in standard chat by explicitly toggling off Memory contributions, ensuring the sensitive number is not saved into persistent memory where it could leak into future unrelated prompts. Conversely, proceeding with default settings (Option A), assuming brief discussions avoid retention (Option C), or enabling persistent memory retention for confidential figures (Option D) creates serious compliance and insider data exposure risks.
質問 # 49
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