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Master Claude agentic architecture, MCP tool integration, Claude Code workflows, prompt engineering, and context management. The definitive certification for building production AI systems with Claude.
New to CCA-F? Try the free CCA-F practice exam →
The CCA-F exam is a ~301 level assessment for practitioners at Anthropic partner companies. Our practice questions, flashcards, and study guides are open to everyone preparing for this certification.
Practice with 300 curated questions covering all exam domains. Each question includes detailed explanations.
Interactive flashcards for memorizing agentic patterns, MCP protocols, Claude Code commands, and prompt engineering techniques.
Simulate the real exam experience with timed, scenario-based practice tests and detailed performance analytics.
Detailed notes covering agentic architecture, MCP integration, Claude Code workflows, prompt engineering, and context management.
Curated collection of Anthropic documentation, Claude API references, and MCP specification resources.
Personalized study schedules and learning roadmaps to help you prepare for the CCA-F exam efficiently.
View your strengths, areas to improve, and performance by domain. Track your journey to certification.
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300+ questions • 3 practice exams
90 minutes
~60 questions
720 (scaled)
CCA-F
Anthropic
Agentic loop pattern and stop_reason handling, Multi-agent hub-and-spoke architecture, Coordinator-subagent communication patterns
MCP client-server architecture and JSON-RPC 2.0, MCP primitives: Tools, Resources, Prompts, Transport layers: stdio and SSE/HTTP
CLAUDE.md configuration hierarchy, Custom slash commands in .claude/commands/, Hooks: PreToolUse, PostToolUse, Notification
System prompt structure with XML tags, Response prefilling for format control, Structured output via tool use schemas
Context window optimization strategies, Prompt caching with cache_control markers, Context compaction and summarization
Design and implement Azure AI solutions
Foundational AI/ML concepts on AWS
Build and deploy generative AI applications
Design, implement, and maintain ML solutions on AWS
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