Library / Artificial Intelligence
Claude CCAR-F Architect Foundations Exams (Unofficial)
On Udemy
About this course
Prepare for the Claude Certified Architect – Foundations (CCAR-F) certification with realistic practice exams designed to test architectural understanding, decision-making, and practical knowledge of building production solutions with Claude.
This course focuses on the major skills expected from candidates preparing for CCAR-F, including agentic architecture and orchestration, tool design and Model Context Protocol (MCP) integration, Claude Code workflows, prompt engineering, structured outputs, context management, and production reliability.
The practice questions are designed to go beyond simple memorization. You will work through architecture scenarios where you need to determine the most appropriate design, orchestration strategy, tool configuration, context-management approach, or reliability pattern.
What you will practice
- Agentic architecture, agent loops, orchestration, delegation, and multi-agent patterns
- Tools, tool schemas, tool selection, error handling, and integration design
- Model Context Protocol concepts including MCP clients, servers, tools, and resources
- Claude Code configuration, project instructions, subagents, skills, hooks, permissions, and workflows
- Prompt engineering and techniques for producing reliable structured outputs
- JSON Schema, validation, output constraints, and error-handling strategies
- Context management, prompt caching, context-window considerations, and long-running workflows
- Reliability patterns including retries, validation, failure recovery, guardrails, and observability
- Architecture trade-offs between deterministic workflows and autonomous agentic systems
- Scenario-based questions requiring you to choose the most appropriate production architecture
Each practice test is intended to help you identify knowledge gaps and improve your ability to reason through architecture decisions.
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Udemy: 2026-11-07 · Coursera: 2026-11-07 · O'Reilly: 2026-11-07 · 365 Data Science: 2026-11-07
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