amai-gmbh/ai-expert-roadmap

★ 30,972JavaScriptAudience · vibe coderComplexity · 1/5QuietLicenseSetup · easy

Mindmap

mindmap
  root((AI Expert Roadmap))
    What it covers
      Fundamentals
      Data Science
      Machine Learning
      Deep Learning
      Data Engineering
      Big Data Engineering
    Learning structure
      Topics in sequence
      Dependencies shown
      Recommended order
    Format
      SVG diagrams
      Interactive website
      Learning resources
    Who needs it
      Career switchers
      AI beginners
      Skill gap finders

mindmap root((AI Expert Roadmap)) What it covers Fundamentals Data Science Machine Learning Deep Learning Data Engineering Big Data Engineering Learning structure Topics in sequence Dependencies shown Recommended order Format SVG diagrams Interactive website Learning resources Who needs it Career switchers AI beginners Skill gap finders

Things people build with this

USE CASE 1

Map out a learning plan if you're starting a career in AI, machine learning, or data engineering.

USE CASE 2

Identify which foundational math and programming skills you need before diving into specialized topics.

USE CASE 3

Find gaps in your knowledge by comparing your current skills against the recommended learning sequence.

USE CASE 4

Discover the relationships between different AI disciplines and how they build on each other.

Tech stack

SVGJavaScript

Getting it running

Difficulty · easy Time to first run · 5min

Use freely for any purpose including commercial, as long as you keep the copyright notice.

In plain English

The AI Expert Roadmap is a visual curriculum guide, not a piece of software, that shows the skills and technologies a person needs to learn in order to work professionally in artificial intelligence, machine learning, or data engineering. The problem it solves is orientation: the AI field is vast and fast-moving, with dozens of tools, libraries, mathematics prerequisites, and sub-disciplines. A beginner or career-switcher trying to enter the field faces a confusing landscape and often doesn't know which things to learn in what order. This roadmap gives a structured, opinionated answer. The project presents a set of flowchart-style diagrams (stored as SVG image files in the repository) covering several distinct tracks: a Fundamentals track covering the mathematical and programming basics needed across all AI work, a Data Science roadmap, a Machine Learning roadmap, a Deep Learning roadmap, a Data Engineer roadmap, and a Big Data Engineer roadmap. Each chart shows topics arranged in a recommended learning sequence with dependencies between them. An interactive version hosted on a companion website links each item in the charts to learning resources. You would use this repository if you are new to AI and want a clear picture of what skills lead where, or if you are partway through learning and want to identify gaps. It was originally created by AMAI GmbH in Germany as an onboarding guide for new employees but was released publicly to benefit the wider developer community. There is no code to run. The repository contains SVG diagram files, a README linking to them, and supporting metadata. The JavaScript language tag reflects the interactive website tooling rather than any runnable content in the repository itself.

Copy-paste prompts

Prompt 1

I want to transition into machine learning. Using the AI Expert Roadmap, what are the foundational skills I should learn first?

Prompt 2

Show me the learning path for becoming a data engineer according to the AI Expert Roadmap.

Prompt 3

What's the difference between the Machine Learning and Deep Learning tracks in the AI Expert Roadmap?

Prompt 4

I know Python but I'm new to AI. Which roadmap track should I start with and why?

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Generated 2026-05-18 · Model: sonnet-4-6 · Verify against the repo before relying on details.