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Ruhaan Kumar
Ruhaan Kumar

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The Complete Open-Source LLM Developer Curriculum (Beginner to Production)

The Complete Open-Source LLM Developer Curriculum — Now Free Forever
If you're learning to build with LLMs, you've probably noticed:

🔴 Most tutorials are too shallow ("just call the API!")
🔴 Others are too academic (dense math, no runnable code)
🔴 Some are locked into one framework or tool
🔴 And worst — they're outdated (written in 2023, never touched since)
We built something different.

Introducing: Practical AI Engineering
An open-source, community-driven curriculum that takes you from "Hello, GPT" all the way to shipping production AI systems.

🔗 (https://github.com/ruhaankumar2013-debug/Practical-AI-engineering) | ⭐ Star it to help others discover it

What You Get
✅ Beginner → Production — Start with zero ML knowledge. End with a deployed, monitored AI system.

✅ Framework-agnostic — Learn OpenAI, Anthropic, HuggingFace, open-weight models. Your choice.

✅ Hands-on first — Every concept has code. Every phase has a capstone project you can add to your portfolio.

✅ Community-maintained — Updated by practitioners, not just educators.

✅ Clearly leveled — Every module is tagged Beginner · Intermediate · Advanced — no surprises.

The Curriculum at a Glance

Phase 0 · Foundations (🟢 Beginner)

Phase 1 · Prompt Engineering (🟢 Beginner)

Phase 2 · APIs & Integrations (🟢 Beginner)

Phase 3 · RAG (🟡 Intermediate) + Phase 4 · Fine-Tuning (🟡 Intermediate)

Phase 5 · Agents (🟡 Intermediate)

Phase 6 · Evaluation (🟡 Intermediate)

Phase 7 · Production (🔴 Advanced)

Phase 8 · Advanced Topics (🔴 Advanced)
Pick Your Starting Point
🟢 New to LLMs?

Start → What Are LLMs? (20 min)
🟢 Know ML, new to LLMs?

Start → Prompt Engineering (1 hour)
🟢 Developer who wants to build NOW?

Start → OpenAI API Quickstart (1 hour)
🟡 Want to use your own data?

Code
Start → Building a RAG Pipeline (2 hours)
🔴 Ready for production?

Start → Safety, Guardrails & Content Filtering (1.5 hours)
What's Included
📖 Written Guides — Clear explanations with examples
🧪 Jupyter Notebooks — Runnable code you can execute
💻 Standalone Projects — Full applications you can deploy
🏗️ Capstone Projects — Portfolio-worthy work

Each phase ends with a project you can actually ship.

Why You Should Care
Free forever — MIT licensed, no paywall
Up-to-date — Created in 2026, actively maintained
Community-driven — PRs welcome. Your improvements help everyone
Practical — No fluff. Every line of code teaches you something
Leveled — Know exactly when you're ready for the next challenge
Get Started Now
👉 ruhaankumar2013-debug/Practical-AI-engineering

⭐ Star the repo — it helps others find it and motivates us to keep it updated!

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