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AI Coding Skill Packs — 21 Curated Learning Paths

AI Coding Skill Packs is a roadmap.sh-style collection for AI coding: practical, stage-based AI Learning Paths for prompt engineering, RAG, agents, fine-tuning, production AI apps, and AI-native team workflows.

Use it as a self-paced curriculum, a team enablement library, or a source collection for hands-on AI coding practice.

Why These Skill Packs

Modern AI engineering is broader than learning one chat UI or one framework. Developers need repeatable paths for Prompt Engineering Tutorial foundations, RAG Tutorial projects, AI Agent Development, LLM Fine Tuning, evaluation, safety, production readiness, and organizational adoption.

This repository collects 21 non-zero2xxx learning paths from AIFlowLearn into a consistent structure:

  • skillpacks/<name>/knowledge/ for reference material
  • skillpacks/<name>/stages/ for progressive learning stages
  • optional skillpacks/<name>/docker/ for reproducible labs

Catalog

Name Topic Stages Docker Difficulty
prompt-engineering Prompt Engineering Tutorial 4 No Beginner
rag-knowledge-base RAG Tutorial and knowledge bases 4 No Intermediate
ai-agent-practice AI Agent Development practice 4 No Intermediate
multi-agent-systems Multi-agent architecture 4 No Advanced
llm-finetuning-new LLM Fine Tuning 4 No Advanced
ai-app-production Production AI applications 4 No Advanced
agent-engineering-skill-cli-aui Agent engineering with CLI/AUI 4 No Intermediate
agent-evaluation-safety Agent evaluation and safety 4 No Advanced
hermes-agent-fundamentals Agent fundamentals 4 No Beginner
ai-native-transform AI-native transformation 4 No Intermediate
spec-driven-dev Spec-driven development 4 No Intermediate
python-for-kids Python for kids 4 No Beginner
kids-programming-intro Programming intro for kids 4 No Beginner
scratch-game-dev Scratch game development 4 No Beginner
latepost-business-thinking Business thinking 4 No Intermediate
team-aios-manager Team AIOS management 4 No Intermediate
tech-manager-growth-path Tech manager growth 4 No Intermediate
tech-manager-growth-path-v2 Tech manager growth v2 4 No Intermediate
alh-sp-D01-skillpack AI literacy hands-on path D01 4 No Beginner
alh-sp-D03-skillpack AI literacy hands-on path D03 4 No Beginner
alh-sp-D06-skillpack AI literacy hands-on path D06 4 No Beginner

How to Use

git clone https://github.com/aiflowlearn/ai-coding-skillpacks.git
cd ai-coding-skillpacks
  1. Pick a skill pack from skillpacks/.
  2. Read the materials in knowledge/.
  3. Follow stages/ in order, starting from stage-01-*.
  4. Complete the exercises in tasks.md.
  5. If a docker/ folder exists, use it for the recommended local practice environment.

Online Practice

Practice these learning paths online at aiflowlearn.net/skillpacks.

FAQ

Is this for beginners or experienced developers?

Both. Beginner paths cover foundations, while agent, RAG, fine-tuning, safety, and production paths assume more engineering experience.

Is this a Prompt Engineering Tutorial repository?

Yes, prompt engineering is one core path, but the collection also covers RAG, agents, fine-tuning, production AI apps, and team adoption.

Can I use these paths for team training?

Yes for non-commercial learning and internal study, subject to the CC BY-NC-SA 4.0 license for learning content.

Are Docker environments included?

The structure supports Docker assets per skill pack. When a source skill pack includes Docker material, it is copied into that skill pack.

How is this different from zero2claude or zero2codex?

This collection intentionally excludes tool-specific zero2xxx paths and focuses on broader AI coding learning paths.

Can I contribute a new skill pack?

Yes. Keep it stage-based, practical, and aligned with the repository structure. See CONTRIBUTING.md.

Related Repos

License

This repository uses a split license:

  • skillpacks/: CC BY-NC-SA 4.0
  • docker/ and Docker/code assets: MIT

See LICENSE.md, LICENSE-MIT, and LICENSE-CC-BY-NC-SA.

Brand

AIFlowLearn builds practical AI learning paths for developers, teams, and builders. Learn more at aiflowlearn.net.

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21 curated AI coding learning paths — prompt engineering, RAG, agents, fine-tuning, and more

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