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| Section | Weight | Objectives |
|---|---|---|
| Topic 1: Configuration and Knowledge Management | 12% | - Managing instructions and knowledge sources - Configuring Claude Projects - Maintaining configuration and knowledge sources - Managing uploaded knowledge and connectors |
| Topic 2: Output Evaluation and Validation | 21% | - Identifying hallucinations, inconsistencies, and bias - Editing, adapting, and refining outputs - Fact-checking and validation - Evaluating output accuracy and completeness - Determining when human review or verification is required |
| Topic 3: Troubleshooting and Optimization | 10% | - Diagnosing underperforming prompts and outputs - Adjusting approaches based on feedback and results - Optimizing workflows for efficiency and effectiveness |
| Topic 4: Prompting and Task Execution | 14% | - Adapting prompting strategies to task types - Iterating prompts to improve output - Creating effective prompts - Task decomposition |
| Topic 5: Governance, Risk, and Responsible Use | 15% | - Ethical and responsible AI use - Data sensitivity, privacy, and regulatory considerations - Organizational AI governance and policies - Identifying appropriate and inappropriate AI use cases |
| Topic 6: Product and Model Selection | 12% | - Selecting appropriate Claude product features - Selecting Claude models - Managing context limitations and memory - Balancing quality, speed, and cost |
| Topic 7: Workflow Integration and Solution Design | 16% | - Integrating Claude into existing workflows - Analyzing requirements and use cases - Research, planning, and process optimization - Communicating Claude's value and limitations - Solution design and iteration |
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NEW QUESTION # 111
You are a business analyst evaluating a Claude-generated business case against the agreed acceptance criteria.
Which is the correct order of evaluation steps?
(1) Compare the business case with the source data and required topics.
(2) Document gaps and inaccuracies for follow-up or correction.
(3) Restate the acceptance criteria for the business case.
(4) Decide whether to use the business case, iterate, or escalate.
(5) Read the business case from beginning to end to form an initial impression.
Answer: D
Explanation:
Answer B is correct. Evaluation begins by restating the agreed acceptance criteria (3), because the reviewer needs an explicit standard before judging the business case. The reviewer then reads the document from beginning to end (5) to understand its argument, scope, and apparent completeness. After that initial pass, the reviewer performs an evidence-based comparison against the source data and required topics (1). Discovered omissions, inaccuracies, and criterion failures are documented for correction or follow-up (2). Only when those findings are available should the reviewer decide whether the business case can be used, needs another iteration, or must be escalated (4). The sequence is therefore 3, 5, 1, 2, 4. Option A compares details before completing the holistic reading; Option C reads before re-establishing the evaluation standard; Option D starts detailed comparison without a clear rubric. Anthropic's evaluation guidance states that successful Claude applications begin with specific, measurable, achievable, and relevant success criteria and normally require multidimensional evaluation. It also emphasizes task-specific tests and clear rubrics. Applying that logic to a business document means establishing the criteria first, gathering evidence second, recording defects third, and making the disposition decision last. Anthropic evaluation guidance
NEW QUESTION # 112
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?
Answer: A
Explanation:
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
NEW QUESTION # 113
You are an operations lead sorting proposed Claude use cases according to whether they are acceptable for your team to pursue.
Which two proposed use cases are acceptable for the team to pursue with Claude? (Select two.) Each correct answer presents a complete solution.
Answer: A,E
Explanation:
Answers B and C are the two acceptable use cases as written. Drafting an internal training summary from approved documentation is a bounded synthesis task grounded in authorized sources. Synthesizing themes from approved customer feedback under established aggregation rules is likewise a controlled analysis task, provided the data handling follows organizational privacy requirements. Both activities support human work without assigning Claude a consequential decision about an individual. Option D feeds performance-review information into a promotion process, an employment-related high-risk domain requiring formal controls and accountable human judgment. Options A and E involve healthcare and legal work. Anthropic's current Usage Policy does not categorically ban those domains, but it requires qualified professional review for high-risk advice or decisions and requires disclosure when outputs are presented directly to consumers. The brief wording in A and E mentions professional review but does not establish the complete safeguards, authorization, privacy handling, or disclosure needed to treat the workflow as approved. Therefore, they are not unconditionally acceptable "as stated." Anthropic's AI Fluency Delegation principle also requires considering consequences, reversibility, and the human capabilities that must remain in the process. B and C are the only choices that fully specify low-risk, policy-bounded knowledge work without relying on unstated safeguards. Anthropic Usage Policy
NEW QUESTION # 114
A knowledge worker is adjusting an approach after a successful pilot revealed two opportunities for further improvement. The pilot's core results were positive, and the team is preparing for a broader rollout.
Which adjustment is most appropriate?
Answer: A
Explanation:
Answer B is correct. The pilot has already demonstrated that the core approach is effective, so the team should retain the successful elements while making targeted changes for the two identified improvement opportunities. A controlled comparison before full rollout then provides evidence that the revised approach performs at least as well as the original pilot and that the modifications produce the expected improvement.
Option A ignores known improvement opportunities and unnecessarily carries identified weaknesses into production. Option C implements the changes during the broader rollout without validating them first.
Monitoring is necessary, but it is not a substitute for controlled pre-rollout testing because defects could affect many more users. Option D tests only the two opportunities in isolation. This may fail to evaluate how the new changes interact with the rest of the successful workflow.
A controlled comparison can evaluate the pilot configuration and the revised configuration against the same acceptance criteria, representative cases, and quality measures. This preserves what worked while reducing the risk of unintended regression. Anthropic's evaluation guidance recommends measurable success criteria, task-specific tests, and evaluations that distinguish between competing approaches. Therefore, B represents the strongest evidence-based adjustment before scaling the workflow. Anthropic: Define success criteria and build evaluations
NEW QUESTION # 115
When refining a Claude output that does not meet expectations, which iterative refinement step should be performed first?
Answer: A
Explanation:
Answer D is correct. Iterative refinement should begin by diagnosing the current output against the original requirements. The reviewer must identify specific weaknesses such as missing information, unsupported claims, incorrect tone, poor organization, excessive length, or failure to follow the requested format. This diagnosis provides evidence for deciding what must change in the prompt.
After identifying the weaknesses, the reviewer can modify the prompt to address them, which corresponds to Option C. The revised prompt is then submitted and the resulting output captured, as described in Option A.
Finally, the new output is compared with the original criteria to determine whether the revision improved performance, as stated in Option B. The logical sequence is therefore D, C, A, and B.
Beginning with prompt modification before diagnosing the failure encourages random changes and makes it difficult to determine which revision produced an improvement. Similarly, a new output cannot be submitted or evaluated before a targeted revision has been created. Anthropic's guidance recommends defining clear success criteria, evaluating results against those criteria, and using a structured self-correction process:
generate a draft, review it, and then refine it based on identified deficiencies. Effective iteration is therefore diagnostic and evidence-based rather than trial and error. Anthropic prompting best practices
NEW QUESTION # 116
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