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Claude Certification Zero to Hero, an unofficial open-source study guide: from your first prompt to production-ready AI architecture. Modules, practice questions, flashcards, labs, projects and three exam tracks.

An open, original learning path that takes you from never having used Claude to preparing for Anthropic's certification exams, and to building secure, production-grade AI systems.

CI Website Release Content: CC BY 4.0 Code: MIT Exam guides verified Unofficial


  • New to AI?


    Start from zero: what LLMs are, how Claude works, and how to use this guide.

    Start with Module 00 →

  • Business user: CCAO-F


    Claude Certified Associate – Foundations, for people who use the Claude apps at work.

    Open the CCAO-F track →

  • Builder: CCAR-F


    Claude Certified Architect – Foundations: agents, the Agent SDK, Claude Code and MCP.

    Open the CCAR-F track →

  • Architect: CCAR-P


    Claude Certified Architect – Professional, for production and enterprise designs.

    Open the CCAR-P track →

  • Practise now


    Timed or learning-mode mock exams in your browser, with domain breakdowns.

    Open the practice app →

  • Build something


    Twenty hands-on labs that run free and offline, and five real-world projects.

    Browse the labs →

Why this repository exists

Anthropic now runs a formal Claude Certification Program. The official exam guides list what is tested; they do not teach it. This repository fills that gap with:

  • a zero-to-hero curriculum (16 modules) that assumes no prior AI knowledge,
  • certification tracks that map every official exam objective to a lesson, a lab and practice questions,
  • hands-on labs and projects that run free and offline by default,
  • a dedicated AI security track for engineers who must ship safely,
  • an offline mock-exam engine for independent practice.

It is also designed to be a practical reference long after the exam.

Who it's for

Find your path: new to AI, start with modules 00–02 and aim for CCAO-F; business or knowledge worker, modules 03–05 and CCAO-F; software or DevOps engineer, modules 03–06 and CCAR-F; security or DevSecOps engineer, module 12 and the skills path; solution or enterprise architect, module 13 and CCAR-P; technical leader, modules 13 and 15 and the skills path.

You are… Start here Then
New to AI entirely 00 Getting started → 01 AI & LLM fundamentals The 30- or 60-day roadmap
A business or knowledge worker using Claude 03 Prompt engineering → 05 Products & models The CCAO-F track
A software, DevOps or cloud engineer 03 Prompt engineering → 04 Context → 06 Claude API Labs 07–12, then the CCAR-F track
A security or DevSecOps engineer 12 AI security Labs 13–15 and 18–20, projects 03–05
A solution or enterprise architect 13 Enterprise AI architecture The CCAR-P track
A technical leader 13 Architecture, 15 Production operations Interview & stakeholder prep

Not sure? Take the two-minute choose-your-path guide.

If this guide helps you, a ⭐ on GitHub helps other learners find it.

Certification tracks

Three supported tracks with their exam format and domain weights: CCAO-F (60 items, 120 minutes, 7 domains), CCAR-F (60 items, 120 minutes, 4 of 6 scenarios across 5 domains) and CCAR-P (63 items, 120 minutes, 7 domains). CCDV-F is planned.

Certification Code Audience Track
Claude Certified Associate – Foundations CCAO-F Business users of the Claude apps Full track
Claude Certified Architect – Professional CCAR-P Architects delivering production systems Full track
Claude Certified Architect – Foundations CCAR-F Developers building agentic systems with the Agent SDK, Claude Code and MCP Full track
Claude Certified Developer – Foundations CCDV-F Developers building on the API Planned (roadmap)

Who can take the exams: as of 2026-10-24, registration is open only to people at organisations in the Claude Partner Network (you register with a partner work email). Anyone can use this repository and Anthropic's free Claude Academy courses to learn; check eligibility before planning to sit an exam.

Exam formats, fees, eligibility and blueprints were verified against the official exam guides on 2026-10-24. See exam facts and the machine-readable registry. Anthropic plans updated guides on 2026-11-17.

The learning journey

Learning journey in seven stages: Foundations (modules 00–02), Prompting and context (03–05), Building (06–09), Systems (10–11), Secure and govern (12–13), Operate (14–15) and Certify (16–18). Labs 01–20 branch from Building and Projects 01–05 from Secure and govern.

Stage Modules You'll be able to…
1. Foundations 00 · 01 · 02 Explain how LLMs work, what tokens and context windows are, and why hallucinations happen
2. Prompting & context 03 · 04 · 05 Write reliable prompts, manage context and caching, choose the right model and product feature
3. Building 06 · 07 · 08 · 09 Integrate the API, build tool-using apps, write MCP servers and roll out Claude Code
4. Systems 10 · 11 Design workflows, agents, multi-agent systems and RAG pipelines
5. Secure & govern 12 · 13 Threat-model LLM apps, defend against prompt injection and design compliant enterprise architectures
6. Operate 14 · 15 Build evals, observe, optimise cost and latency, and run AI in production
7. Certify 16 · 17 · 18 Prepare objective by objective and practise under exam conditions

Study plans

Study plans compared as bars of 7, 15, 30, 60 and 90 days. The three CCAO-F plans total about 25, 30 and 38 hours; the 30-day plan is best for beginners. The two CCAR-P plans total about 110 and 170 hours.

Plan Track Assumes Daily time Link
7-day accelerated CCAO-F Months of hands-on Claude use at work, including Projects 3–4 h 7-day
15-day preparation CCAO-F Some hands-on use of Claude or a similar assistant; no coding 2 h 15-day
30-day structured CCAO-F Nothing beyond basic computer use: best for complete beginners 1–1.5 h 30-day
60-day comprehensive CCAR-P Several years of software or systems experience; reads Python 1.5–2 h 60-day
90-day enterprise engineering CCAR-P Working developer, engineer or architect; no AI knowledge needed 1.5–2 h + weekend labs 90-day

The roadmaps guide explains how to pick a plan. Anthropic publishes updated exam guides on 2026-11-17; plans will be refreshed after that (see exam facts).

Practise

Practice exam demo: a CCAR-F question is answered, the correct option turns green with an explanation, and a results panel shows the score, per-domain bars and the weakest domain to review next.

python3 -m venv .venv && source .venv/bin/activate
pip install -r requirements-dev.txt

# Mock exams in the terminal (timed or learning mode)
python 18-mock-examinations/run_mock_exam.py --track CCAO-F --mode learn

# ...or in the browser
python3 -m http.server 8000     # then open http://localhost:8000/18-mock-examinations/web/

# Run a lab offline (no API key, no cost)
python 19-hands-on-labs/lab-01-first-claude-interaction/lab.py
  • Practice questions: unofficial, schema-validated, every distractor explained
  • Mock examinations: timed and learning modes, domain breakdowns, weak-area advice
  • Flashcards: YAML decks, exportable to Anki
  • Cheat sheets: one-page summaries for the API, prompting, Claude Code, MCP, security and each exam

The real practice app, recorded in learning mode (try it online):

Recording of the practice app: setting up a five-question CCAR-F session in learning mode, answering one question correctly and one incorrectly with the explanation of every option, then the results page with per-domain scores and recommended study.

Read it as a website

Website preview: the study guide as a searchable site with navigation; a search for tool_choice shows matching pages, then the theme switch flips the site from light to dark.

Everything here is also published as a searchable website with light and dark themes and the interactive practice exam built in. The site is built from this repository with MkDocs and Material for MkDocs, and deployed to GitHub Pages on every push to main (see .github/workflows/pages.yml).

Preview it locally:

pip install -r requirements-docs.txt
python tools/build_site.py --serve      # http://127.0.0.1:8000

Hands-on

Lab modes: mock mode is the default, needs no API key, costs nothing and runs offline; live mode uses your own API key, calls the real Claude and uses API credits.

  • 20 labs, from a first API call to a secure AI gateway. Every lab runs in free, offline mock mode, and in live mode with your own API key (clearly marked when it costs credits).
  • 5 real-world projects of increasing difficulty: a document summariser, a knowledge-base Q&A assistant, a security alert triage assistant, a DevSecOps code-review assistant and an agentic investigation assistant. Each has requirements, an architecture, security design, tests and cost estimates.

The five projects as a staircase from beginner to capstone: document summarisation, knowledge base Q&A assistant, security alert triage, DevSecOps code review and the agentic investigation assistant.

Repository map

# Section # Section
00 Getting started 13 Enterprise AI architecture
01 AI & LLM fundamentals 14 Evaluation & testing
02 Claude fundamentals 15 Production operations
03 Prompt engineering 16 Certification tracks
04 Context engineering 17 Practice questions
05 Claude products & models 18 Mock examinations
06 Claude API 19 Hands-on labs
07 Tool use & function calling 20 Real-world projects
08 Model Context Protocol 21 Interview preparation
09 Claude Code 22 Cheat sheets
10 Agentic AI 23 Flashcards
11 RAG & knowledge systems 24 Troubleshooting
12 AI security 25 Official resources

Also: Glossary · FAQ · Roadmap · Progress tracker · Changelog

Quality and integrity

Quality pipeline: every pull request passes automated checks for questions, links, coverage, exam facts, labs and secrets before it is ready to merge.

Every pull request is checked automatically:

  • practice-question schema, unique IDs, answer keys and distractor rationales, plus near-duplicate detection,
  • internal links and anchors, plus a weekly external link check,
  • objective coverage (every official objective → module → lab → questions),
  • exam facts consistent with the registry and linked to a source,
  • all labs executed in mock mode, repository and project tests,
  • secret scanning (gitleaks plus a local scanner) and markdown lint.

Run everything locally with python tools/validate_all.py --labs.

About the maintainer

This repository is maintained by Amol Bhure (@codedevloper).

I have been working with Claude for the last couple of years, alongside a range of other AI tools, including Microsoft Copilot, GitHub Copilot, ChatGPT, OpenAI Codex, Grok and Gemini. Using them side by side taught me that getting real value from AI depends less on which tool you pick and more on how well you prompt, check and design around it. That is what led me to pursue Anthropic's certifications, and I have been preparing for them since March 2026.

Earning these three Anthropic certifications between September and October 2026 was one of the most rewarding learning stretches of my career, and I am genuinely proud of it. Each exam pushed me past knowing what Claude can do and into judging how to use it well: when to trust an answer and when to check it, how to build security in from the start, and how to explain trade-offs to the people who depend on the system. Going from the Associate exam to the Architect Professional exam in a few weeks showed me how much there is to learn, and how much it pays off.

This repository is my way of paying that forward. It is the guide I wish I had had when I started. If it helps you pass an exam, or ship something you are proud of, it has done its job.

Certification timeline: started preparing in March 2026; earned CCAO-F and CCAR-F in September 2026 and CCAR-P in October 2026; published this guide in October 2026.

Claude Certified Associate – Foundations certificate issued to Amol Shivraj Bhure, September 2026
Claude Certified Associate – Foundations (CCAO-F) · earned Sep 2026 · Verify on Credly

Claude Certified Architect – Foundations certificate issued to Amol Shivraj Bhure, September 2026
Claude Certified Architect – Foundations (CCAR-F) · earned Sep 2026 · Verify on Credly

Claude Certified Architect – Professional certificate issued to Amol Shivraj Bhure, October 2026
Claude Certified Architect – Professional (CCAR-P) · earned Oct 2026 · Verify on Credly

Certification Code Earned Valid until Verify
Claude Certified Associate – Foundations CCAO-F Sep 2026 Sep 2027 Credly badge
Claude Certified Architect – Foundations CCAR-F Sep 2026 Sep 2027 Credly badge
Claude Certified Architect – Professional CCAR-P Oct 2026 Oct 2027 Credly badge

Holding these certifications does not make this guide official, sponsored or endorsed by Anthropic. Exam content is confidential, and none of it is used here: everything in this repository is written from public documentation and the published exam guides.

Contributing

How to contribute in five steps: fork the repository, write original content, run validate_all.py with labs, open a pull request where CI runs every check, and get merged after maintainer review.

Contributions are welcome. Read CONTRIBUTING.md and the documentation standards. The two non-negotiables: original work only, and no real exam content, ever.

Official resources

Use these as your source of truth: the Anthropic Partner Academy certifications page (exam guides and policies), Pearson VUE (scheduling), Claude Academy (free courses), the Claude docs, Claude Code docs and modelcontextprotocol.io. More in 25 · Official resources.

Disclaimer

This is an independent, community study resource. It is not affiliated with, sponsored by or endorsed by Anthropic. "Claude", "Anthropic" and the certification names are trademarks of Anthropic, PBC, and are used here only to identify the products and exams this guide is about. Apart from the maintainer's own issued certificates shown in About the maintainer, which display Anthropic's logo and badge artwork as issued, the repository uses no Anthropic logos or artwork.

  • The maintainer and contributors do not speak for Anthropic, and nothing here is official guidance or a promise about exam content or results.
  • All practice and mock-exam questions are original and unofficial. None comes from, or is reconstructed from, a real exam. Mock-exam percentages are not Anthropic scaled scores and do not predict official results.
  • Exam details can change. Always confirm with the official exam guide before you register or sit an exam.
  • Product facts, model names and prices are dated where stated, and may have changed since.
  • All organisations, people and data in examples are fictional. Several organisation names (such as Contoso, Fabrikam and Northwind) are fictional sample names popularised in Microsoft documentation; any resemblance to real organisations or people is coincidental.
  • Third-party names (Amazon Bedrock, Google Cloud, Microsoft Foundry, OWASP, NIST and others) are trademarks of their owners and appear only for identification and reference.

Licence

Code is released under the MIT License and educational content under CC BY 4.0. The certificate images are excluded from both. See LICENSE-CONTENT.md for the details, attribution wording and trademark notices.