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Ultimate Anthropic Claude Certified Architect - Foundations
Published 9/2026
Created by Sundog Education by Frank Kane, Puria Izady
MP4 | Video: h264, 2560x1440 | Audio: AAC, 44.1 KHz, 2 Ch
Level: All Levels | Genre: eLearning | Language: English | Duration: 112 Lectures ( 8h 32m ) | Size: 9.1 GB
CCAR-F prep with Claude Code, Agent SDK, MCP, orchestration, structured output, and 2 mock exams
What you'll learn
Pass the Anthropic Claude Certified Architect - Foundations exam (CCAR-F). Design agentic loops, subagents, sessions, hooks, and handoff patterns for production Claude systems. Build MCP tools and servers with clear schemas, scoped access, structured errors, and reliable tool routing. Configure Claude Code for team workflows using CLAUDE md, skills, commands, plan mode, permissions, and CI/CD. Engineer prompts for precision, few-shot consistency, JSON schemas, validation, retries, and structured output. Manage context windows, summaries, provenance, uncertainty, human review, and reliability tradeoffs. Apply architecture judgment to customer support agents, research pipelines, CI review, extraction, and developer tools. Practice CCAR-F scenario questions across all domains with quizzes and 2 full-length mock exams.Requirements
Python programming experience is recommended. Command-line experience is expected, including running tools, editing files, and working in developer environments. Some experience building with LLM APIs, Claude Code, Agent SDK, or MCP is helpful, but the course teaches from first principles. This is a technical architect-level course. It is not intended as a beginner introduction to Claude or generative AI.DescriptionThis course contains the use of artificial intelligence.
Ultimate Anthropic Claude Certified Architect - Foundations prepares you for the CCAR-F exam withhands-on labs, 2full-length practice exams, andin-depth video instruction.
Building with Claude in production takes more than knowing the API or writing a good prompt.
TheAnthropic Claude Certified Architect - Foundations exam tests sound architecture and implementation decisions for real-world Claude systems. That includes agentic loops, tool design, MCP integration, Claude Code configuration, structured output, context management, reliability, human review, and production tradeoffs.
Please note: Claude certifications are currently available only to employees of Anthropic partner organizations. (It's easy to sign your company up, though.)
This is not a trivia course. The exam is scenario-based, and this course is built the same way. You will learn how to reason through realistic production situations and choose the most appropriate architecture, configuration, or implementation pattern.
You will learn how to
Design agentic loops that use stop_reason, tool calls, tool results, and termination conditions correctly Build multi-agent systems using coordinator and subagent patterns Pass context between agents without losing attribution, constraints, or source metadata Use hooks, prerequisite gates, and structured handoff patterns when prompt guidance is not enough Design effective tools with clear descriptions, schemas, boundaries, and structured error responses Build and integrate MCP servers into Claude Code and agent workflows Configure Claude Code for team use with markdown files, path-specific rules, skills, slash commands, and permission modes Use plan mode, direct execution, iterative refinement, and CI/CD workflows appropriately Engineer prompts with explicit criteria, few-shot examples, structured output, JSON schemas, validation, retries, and feedback loops Design batch processing, multi-pass review, and multi-instance review strategies Manage context windows as a budget across long sessions, large codebases, documents, summaries, and handoffs Make reliability decisions around uncertainty, escalation, provenance, conflicting sources, and human reviewThe course includes6 hands-on labs,5 exam-style quizzes, andtwo full-length 60-question mock exams. The labs are technical and runnable, using Python, Claude Code, the Claude Agent SDK, the Claude API, and MCP.
The course follows the official CCAR-F exam blueprint, including
Agentic Architecture and Orchestration Tool Design and MCP Integration Claude Code Configuration and Workflows Prompt Engineering and Structured Output Context Management and ReliabilityYou will work through the same kinds of scenarios the exam emphasizes, including customer support resolution agents, multi-agent research systems, developer productivity tooling, Claude Code for CI/CD, structured data extraction, and code generation in real projects.
This course is intended for solution architects, senior engineers, developers, technical leads, and AI engineers who want to build production-grade Claude systems and prepare seriously for the CCAR-F exam.
Your instructors bring deep real-world experience in AI, cloud architecture, and software engineering.
Puria Izady is a Solutions Architect at AWS specializing in Generative AI and Machine Learning, and is the creator behind Pumping Code.
Frank Kane has taught AI and machine learning to over 1.2 million people around the world. He holds 26 patents in machine learning and spent 9 years at Amazon as a senior engineer and senior manager.
No course can guarantee a passing result. What this course gives you is a structured, blueprint-aligned path through the exam domains, hands-on experience with the core Claude architecture patterns, and the scenario practice you need to approach the exam with confidence.
By the end of this course, you will be prepared to reason through CCAR-F exam scenarios and make better architecture decisions when building real Claude-powered systems.
Who this course is for
Solution architects and senior engineers preparing for the Anthropic Claude Certified Architect - Foundations exam. Developers and technical leads building production applications with Claude, Claude Code, Agent SDK, Claude API, and MCP. AI engineers designing agentic systems, multi-agent workflows, tool integrations, structured output pipelines, or Claude-powered CI/CD. Technical learners who want runnable labs, exam-style practice, and production-oriented tradeoff guidance rather than a high-level overview.Homepage
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