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Module 00: Getting Started

Level: Beginner · Time: ~1.5 hours · Exam relevance: orientation for CCAO-F and CCAR-P

Welcome. This repository takes you from your very first prompt to designing production-ready systems with Claude, and prepares you for Anthropic's Claude certifications along the way. You do not need any prior experience with AI. You do not need to be a programmer, either, unless you choose the architect track.

This module helps you set up, pick a direction and plan your time. It takes about an hour and a half, and it will save you many hours of wandering later.

Unofficial resource. This is an independent, community-written study repository. It is not produced or endorsed by Anthropic. Every explanation and practice question is original. Always read the official exam guide before you sit an exam; exam facts used here are recorded in registry.yaml and summarised in Exam facts.

Before you plan to sit an exam: as of 2026-10-24, Anthropic's certification exams are open only to people at organisations in the Claude Partner Network. Everything in this repository is free to use either way. See exam facts for eligibility and registration.

Learning objectives

After completing this module you will be able to:

  1. Explain how the repository is organised and how modules, labs, practice questions, mock exams and flashcards fit together.
  2. Set up a working environment that runs every lab offline at no cost, and optionally against the real Claude API.
  3. Choose between the three supported certification tracks, CCAO-F for business users, CCAR-F for builders and CCAR-P for architects, or a non-exam learning path.
  4. Pick a study roadmap that matches your experience and the time you have, from 7 to 90 days.

Page order

# Page What you get Time
1 How to use this repository A map of the folders and a study method that works 20 min
2 Choose your path Which certification (if any) suits you, and the modules for each 20 min
3 Environment setup Python, the labs in mock mode, and optional live API access 30 min
4 Study roadmaps Day-by-day plans of 7, 15, 30, 60 and 90 days 20 min

Business users who will not write code can skim the environment page: you can complete the CCAO-F track using the Claude apps alone, and run labs only if you are curious.

Prerequisites

None. If you can use a web browser, you can start.

Helpful but optional:

  • A Claude account (the Free plan is enough for Modules 01 and 02; some features in Module 05 need a paid plan).
  • Python 3.10 or later, if you want to run the labs. Environment setup explains how to install it.

What this repository covers

flowchart LR
    subgraph Foundations
        M00[00 Getting started] --> M01[01 AI and LLM fundamentals] --> M02[02 Claude fundamentals]
    end
    subgraph Core
        M03[03 Prompt engineering] --> M04[04 Context engineering] --> M05[05 Products and models]
    end
    subgraph Build
        M06[06 Claude API] --> M07[07 Tool use] --> M08[08 MCP] --> M09[09 Claude Code] --> M10[10 Agentic AI] --> M11[11 RAG]
    end
    subgraph Production
        M12[12 AI security] --> M13[13 Enterprise architecture] --> M14[14 Evaluation] --> M15[15 Production operations]
    end
    subgraph Practice
        P16[16 Certification tracks] --- P17[17 Practice questions] --- P18[18 Mock exams] --- P19[19 Labs] --- P20[20 Projects]
    end
    Foundations --> Core --> Build --> Production
    Core -. CCAO-F focus .-> Practice
    Production -. CCAR-P focus .-> Practice

Exam relevance

This module teaches no exam content directly. It points you at the right content for:

  • CCAO-F (Claude Certified Associate – Foundations): for business and knowledge workers who use Claude as a productivity tool and build Claude Projects. See the CCAO-F track.
  • CCAR-P (Claude Certified Architect – Professional): for solution architects, AI/ML engineers and senior engineers who design production Claude solutions. See the CCAR-P track.

The registry also records other Anthropic certifications whose facts are known but for which this repository does not yet provide a full track.

Next module

Once you have chosen a path and a roadmap, start Module 01: AI and LLM fundamentals.