Exam Prep: Claude Certified Architect Foundations (CCAR-F)

This course prepares developers to pass the CCAR-F (Claude Certified Architect — Foundations) exam and to apply what it tests in real work. Over three intensive days, learners cover every scored exam domain — from agentic architecture and orchestration through tool design, Claude Code configuration, prompt engineering, and context management — while building the practical fluency the exam expects. The emphasis is firmly practical — roughly 60% of each day is spent building — so every examinable concept is reinforced by a hands-on exercise. Time is allocated to match the exam’s own domain weightings, so no domain is over- or under-represented. Learners leave not only with working code and a clear playbook for driving productivity with Claude, but confident and ready to sit the CCAR-F.

The instructor provides fully configured lab environments for every candidate — preconfigured Anthropic API keys, all dependencies, sample data, and starter projects. Candidates need only a laptop and a browser; there is no setup for attendees.

Each day maps directly to CCAR-F exam domains, closes with exam-style checkpoint questions in the exact scenario-based, multiple-choice format used on the real exam, and the course finishes with a full mock exam and personalized readiness review.

Exam Prep: Claude Certified Architect Foundations (CCAR-F) Benefits

• Course Benefits

  • Demonstrate knowledge of the Anthropic API and apply core API concepts to build and manage Claude-powered applications.
  • Apply prompt engineering techniques and context-management strategies to improve the quality, reliability, and effectiveness of Claude interactions.
  • Implement scalable context strategies using multimodal capabilities, prompt caching, and retrieval techniques to optimize AI application performance.
  • Configure and apply tool use and agentic capabilities to enable Claude to interact with external systems, perform tasks, and execute multi-step workflows.
  • Apply Model Context Protocol (MCP) and Claude Skills concepts and identify strategies for securely deploying and scaling Claude capabilities across an organization.

  Prerequisites

  Writing basic Python and reading JSON - Using the command line and a code editor

Claude Architect Foundations Prep Course

Learning Objectives

Day 1 — Agentic Architecture & Orchestration

Exam domain 1 (27% of scored content). Build agents that decide and act — implement the agentic loop and orchestrate coordinator–subagent systems.

• The agentic loop: stop_reason control flow, executing tools, and returning results for the next iteration
• Model-driven decision-making vs pre-configured decision trees or fixed tool sequences
• Hub-and-spoke coordinator–subagent orchestration with isolated context; decomposition, delegation, and result aggregation
• Subagent spawning via the Task tool, parallel subagents and explicit context passing, sessions (--resume, fork_session), and hook-based enforcement

Exercises:

• The Agentic Loop
• Coordinator–Subagent Delegation with Task
• Parallel Subagents & Context Passing
• Build & Debug a Multi-Agent Research Pipeline

Exam checkpoint: scenario-based quiz on the agentic loop, coordinator decomposition, subagent context, and enforcement vs prompting.

Day 2 — Tools, MCP & Claude Code

Exam domains 2 (18%) and 3 (20%) — 38% combined. Design tools Claude selects reliably, wire in MCP servers, and configure Claude Code for a real team workflow.

• Tool-interface design and diagnosing misrouting from overlapping descriptions
• Structured MCP errors (isError, errorCategory, isRetryable) and scoping toolsets with tool_choice
• MCP integration — project- vs user-scoped servers, env-var secrets — and built-in tools (Grep, Glob, Read/Write/Edit)
• Claude Code configuration (CLAUDE.md hierarchy, path-specific rules, slash commands, skills) and workflows (plan mode, the Explore subagent, CI/CD)

Exercises:

• Fix Tool Misrouting with Descriptions
• Structured MCP Errors & Scoped tool_choice
• Configure Claude Code for a Team Dev Workflow
• Plan Mode vs Direct Execution

Exam checkpoint: scenario-based quiz on tool descriptions, MCP error/scoping, CLAUDE.md hierarchy, path rules, and plan mode.

Day 3 — Prompt Engineering, Structured Output, Context & Reliability

Exam domains 4 (20%) and 5 (15%) — 35% combined. Engineer precise, schema-compliant output and keep multi-step systems reliable — then sit a full mock exam.

• Precision prompting with explicit categorical criteria and few-shot examples for consistent, actionable output
• Guaranteed schema-compliance via tool_use; nullable fields, extensible enums, and validation–retry–feedback loops
• Batch & multi-pass review — the Message Batches API, SLA planning, and independent review instances
• Context management and reliability — trimming verbose output, persisting case facts, escalation triggers, error propagation, and provenance

Exercises:

• Explicit-Criteria Prompts to Cut False Positives
• Structured Extraction with tool_use + Validation-Retry
• Batch Processing & SLA Planning
• Escalation, Error Propagation & Provenance drills