Anthropic Claude Developer Foundations Certification Exam Syllabus

Anthropic CCDV-F certification syllabus and exam preparation guideThis Anthropic CCDV-F exam preparation guide brings together what you need to plan your Anthropic Claude Certified Developer - Foundations (CCDV-F) study: the exam summary, the full list of syllabus objectives, recommended training, sample questions and the practice exam. Knowing exactly what the Claude Developer Foundations exam assesses is the first step in a sound study plan, because it tells you what to learn and what kind of questions to expect.

The Anthropic Claude Developer Foundations certification is for developers who build, integrate and ship production-grade applications, agents and workflows on Claude. Start with the official Anthropic exam guide, then work through the recommended Anthropic training and documentation. Add hands-on building wherever you can, since the exam objectives describe real development tasks such as integrating the API, constructing agents, engineering prompts and context, running evals and implementing guardrails. Once the main topics are covered, the sample questions and practice exam in this guide help you test what you have learned and find the areas that need more work before you sit the Anthropic Claude Certified Developer - Foundations exam.

Anthropic CCDV-F Exam Summary and Key Details

Exam Name
 Anthropic Claude Certified Developer - Foundations
Exam Code CCDV-F
Exam Price $125 USD
Duration 120 minutes
Number of Questions 53
Passing Score Scaled score of 720 on a scale of 100–1,000
Recommended Training / Books Anthropic Partner Academy – Claude Certified Developer – Foundations
Claude Certified Developer – Foundations Prep Course
Claude Certified Developer – Foundations Exam Guide (PDF)
Schedule Exam Pearson Vue
Sample Questions Anthropic CCDV-F Sample Questions
Recommended Practice Anthropic Claude Certified Developer - Foundations (CCDV-F) Practice Test

Anthropic Claude Developer Foundations Exam Syllabus Topics

Section Objectives
Agents and Workflows
(14.7%)		 - Apply the decision criteria for choosing a workflow versus an agent, and structure manager/supervisor hierarchies and subagents to improve task execution
- Construct Claude agents with the Claude Agent SDK, custom agent loops and harnesses, and managed deployment models (self-hosted vs. Anthropic-hosted)
- Use hooks for deterministic actions within agent loops
- Apply common agent patterns (tool-use loops, sub-agents, memory, context-window management) and agentic frameworks such as Strands, LangGraph and PydanticAI
Applications and Integration
(33.1%)		 - Translate business requirements into functional and infrastructure requirements and solution architecture
- Apply systems life-cycle concepts to develop, implement, operate and maintain Claude-based systems
- Work with Claude API mechanics: messages, tools, streaming, vision, thinking, caching, third-party vendors, the Batch API and realtime-vs-batch tradeoffs
- Apply software-engineering foundations: REST APIs, JSON, asynchronous programming, version control, SDLC integration, code review and refactoring
- Design Claude applications across interfaces (Claude Code, Desktop, claude.ai, API, SDKs) with sound content boundaries, schema design, session hygiene and plugin management
- Manage configuration: CLAUDE.md files, settings.json, model version pinning, prompt versioning and plugin dependencies
Claude Code
(3.1%)		 - Operate Claude Code core components (Rules, Skills, Commands, Agents, Agent Memory) and features (session management, built-in and custom slash commands, headless, streaming and auto mode)
- Apply the CLAUDE.md hierarchy, repository initialization and settings.json configuration
Eval, Testing, and Debugging
(2.6%)		 - Identify error types and select recovery strategies for Claude applications
- Use trace analysis to identify failure modes and isolate problems between the integration layer and model output
Model Selection and Optimization
(16.8%)		 - Apply LLM fundamentals: tokens, context windows, sampling, non-determinism, model options (fast mode, extended/adaptive thinking, effort levels) and zero-/single-/multi-shot prompting
- Apply foundational technical concepts, including integrating with SDKs that wrap REST APIs and websockets
- Select Claude models (Opus vs. Sonnet vs. Haiku, adaptive-thinking support) and weigh quality/latency/cost tradeoffs and breaking changes across releases
- Manage cost and tokens: usage tracking, cost modeling and caching (prompt caching, cache check-pointing)
Prompt and Context Engineering
(11.0%)		 - Manage context and memory: context-window management, preventing context drift and bloat (tool-output pruning, compaction) and context isolation via subagents or multi-step workflows
- Apply prompt-engineering methods: instruction clarity, few-shot examples, system-vs-user placement, output constraints, iterative refinement and input sanitization
- Produce, validate and consume Claude output with structured-output patterns, response validation, defensive parsing and healthy skepticism toward confident output
Security and Safety
(8.1%)		 - Apply AI application security: prompt-injection awareness and mitigation, jailbreak defense, untrusted-input handling, data-leakage prevention, PII handling and auth/confidentiality/integrity
- Apply guardrails and secure-by-design deployment (content policy, guardrail layering, least privilege)
- Leverage Claude hooks for guardrails and to prevent destructive actions
- Manage identity, secrets and API keys across development and production, including authentication and authorized-access monitoring
Tools and MCPs
(10.6%)		 - Implement tools: tool use and function calling, external-system configuration, tool-description writing, error handling and tool-set construction best practices
- Develop MCP servers: authoring, deployment, integration, MCP resources/tools/prompts and communication patterns (stdio, sockets, client vs. server)
- Weigh tradeoffs among built-in Tools, custom Tools, Skills and MCPs to select the right approach for a use case

How to Use the Anthropic CCDV-F Syllabus in Your Preparation

Treat the objectives above as your study checklist. For each one, ask yourself whether you could explain it and apply it to a real development situation, not just recognize the term. Official Anthropic training and documentation build the knowledge, and building and operating at least one Claude application turns it into practical skill.

When most objectives feel familiar, test them. The sample questions show you the question style, and a timed practice exam shows how well you apply your knowledge under exam conditions and which objectives you should revisit. Practice exams work best alongside official training, documentation and hands-on experience, not in place of them.

For more on the exam format, difficulty and preparation, read the Anthropic CCDV-F certification FAQs. When you are ready to move from syllabus review to repeated timed practice, start the premium Anthropic Claude Certified Developer - Foundations practice exam.

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