Anthropic Claude Certified Developer-Foundations - CCDV-F certification

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Anthropic CCDV-F Exam Syllabus Topics:

Anthropic Claude Certified Developer-Foundations Sample Questions:

Question 1

The Claude application your team built has grown over six months, and the prompt-handling code has accumulated duplication and tangled control flow. The functionality is working, but new features are getting harder to add.
How would you address this?

A. Refactor the prompt-handling code in small increments as part of each new feature ticket, treating the cleanup as a side effect of feature work.
B. Continue adding features and plan a refactoring pass after the next two release cycles when the team has more bandwidth for internal work.
C. Plan a refactoring pass to consolidate duplicated logic, separate concerns, and simplify control flow before adding new features.
D. Move all the prompt-handling code into a single large function to reduce the number of files developers have to navigate when reading the code.

Question 2

A Claude application that worked well in testing is now occasionally returning outputs that mention information not present in the input. The development team initially assumed the model was hallucinating, so they asked you to troubleshoot.
What would you do first?

A. Apply a retrieval-augmented generation pattern to ground the responses in source content before any further investigation of the production traces.
B. Examine production traces to identify whether the issue is hallucination by the model, context loss, prompt injection, or another failure mode before recommending a fix.
C. Replace the current model with a larger one to reduce the chance of hallucination, on the grounds that larger models tend to hallucinate less in typical applications.
D. Add a system prompt instruction telling the model not to invent information, on the grounds that prompt-level instructions are the fastest fix for hallucination concerns.

Question 3

You are integrating Claude into an application written in Python. The Claude SDK provides a Python client that wraps the underlying REST API.
How would you integrate the SDK?

A. Use a different LLM provider's SDK and translate the responses into Claude's API shape so the application can switch providers in the future.
B. Use the Claude Python SDK and let it handle authentication, retries, and response parsing through its standard documented patterns for Python integrations.
C. Skip the SDK and embed Claude calls in shell commands invoked from Python, so that the application runs the calls outside the main Python process.
D. Call the REST API directly with raw HTTP requests so the application avoids the SDK's abstraction between the application code and the API.

Question 4

You are setting up the configuration management approach for a new Claude Code project. Your team will use CLAUDE.md files and settings.json files to control behavior, and you want to make sure changes are tracked and reviewable.
The configuration management approach would...

A. Duplicate CLAUDE.md and settings.json files in multiple repositories to provide redundancy, on the grounds that a single source of truth is risky for project configuration.
B. Version-control CLAUDE.md and settings.json files in a separate repository from the project's source code, so configuration evolves independently from the application code over time.
C. Version-control CLAUDE.md and settings.json files alongside the project's source code, with changes reviewed through standard pull request workflows the team applies.
D. Version-control CLAUDE.md alongside the project's source code and settings.json files in a separate repository from the project's source code.

Question 5

A teammate has submitted a pull request that adds a Claude-powered feature to your service. The code works, but the prompt and model selection are hard-coded inline, error handling is missing, and there are no tests for the integration.
What would you request during code review?

A. Approve the pull request as-is, on the grounds that the feature works in the happy path and the missing pieces can be added in follow-up commits.
B. Approve the pull request and add the missing pieces yourself in a follow-up commit so the teammate can move on to other work immediately.
C. Request changes that move prompt and model configuration to a configurable location and add tests, treating the missing error handling as a follow-up release item.
D. Request changes that move prompt and model configuration to a configurable location, add error handling for Claude API failures, and add tests for the integration.

Solutions: