Library / Artificial Intelligence
Claude Certified Architect Foundations - 2026 Practice Test
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About this course
Sitting the CCAR-F costs $125 per attempt, and the credential lasts 12 months. Find out whether you're ready before you book.
This course is 100 scenario questions across two timed practice exams, built to Anthropic's published exam blueprint and designed to tell you something specific: which of the five exam domains is actually costing you marks.
What you get
Two 50-question exams, 100 minutes each, matching the real exam's two-minutes-per-question pace. Each exam is independently weighted to the official blueprint — Agentic Architecture & Orchestration 27%, Claude Code Configuration & Workflows 20%, Prompt Engineering & Structured Output 20%, Tool Design & MCP Integration 18%, Context Management & Reliability 15% — so a score on either one means something on its own.
Every question carries a detailed explanation of why the correct answer works and why the alternatives fail, plus a pointer to the exact task statement it tests in the official exam guide. Every question is also tagged by domain, so you can use practice mode to drill one weak area at a time instead of retaking a whole exam.
Why scenario questions
The CCAR-F doesn't ask you to define MCP. It asks for judgement. Should this rule live in a hook or in a prompt? Is the root cause the coordinator, or the subagent it delegated to? Is the proportionate fix a better tool description, or an entire routing layer?
These questions put you in the architect's seat in realistic production contexts — customer support resolution agents, multi-agent research pipelines, Claude Code in CI/CD, structured document extraction — and make you choose. The explanations then walk through the reasoning, because on this exam most of the available marks come from recognising why a plausible option is wrong.
How to use itTake Exam 1 cold and timed, with nothing looked up. An unprepared score is the only honest read on where you stand.
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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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