L0 Graduation: What's Next?

🎉 Congratulations, you finished the L0 Primer.

After these 12 articles, you should now be able to:

• Distinguish AI / ML / DL / LLM
• Summarize 70 years of AI history in one sitting
• Judge what to delegate to AI
• Understand why AI hallucinates, know how to mitigate
• Write prompts that 10× AI output quality
• Plan your career around AI-era reality
• Choose intelligently among ChatGPT / Claude / Gemini
• Use AI safely, without leaking critical data
• Understand most AI jargon

This already puts you ahead of 80% of “AI users.” But the AI learning road has just begun.

Where You Are Now

Our learning map:

🥚 L0  Primer ──────── you are here
🐣 L1  Math & Python
🐥 L2  Classical ML
🧠 L3  Deep Learning Core
🦅 L4  LLM & Generative AI
🎨 L5  Multimodal & Frontier
🛡️ L6  Safety & Alignment
⚙️ L7  Systems & Engineering

From here, three main branches. You don’t have to walk all of them—pick the one most aligned with your interest.

🎯 Path A: “I want to really understand the tech” → L1 → L3

If you want to get how AI works—not surface, but deep—this path.

For:

• Students / career changers / engineers
• Not afraid of math
• Ready to invest 6-12 months

The route:

L1 Math & Python (18 articles · ~1 month)
   ↓
L2 Classical ML (20 articles · ~2 months)
   ↓
L3 Deep Learning Core (25 articles · ~3 months)
   ↓
   You can read 90% of AI papers now

After L1-L3, you’ll have first-principles understanding of “why AI is the way it is, and how it might change.” No other path replaces this.

⚡ Path B: “I want to build AI apps fast” → Jump to L4

If you want to skip foundations and go straight to AI apps—RAG, Agent, Prompt Engineering—take this path.

For:

• Already know programming
• Want to ship products
• OK with “knowing how, not knowing why”

The route:

L0 (done)
   ↓
L4 LLM & Generative AI (30 articles · ~2-3 months)
   ↓
   You can independently build AI apps

This is the most pragmatic path. L4 covers:

• Advanced Prompt Engineering
• Building RAG from scratch
• Agent construction
• Tool Use & MCP
• Fine-tuning basics
• Inference optimization

After it, you can ship real AI products.

🎨 Path C: “I’m into multimodal / creative” → Jump to L5

If your interest is image generation, video, music, 3D—this path.

For:

• Designers / content creators / artists
• Want to use AI for creation
• Less interested in LLM

The route:

L0 (done)
   ↓
L5 Multimodal & Frontier (15 articles · ~1-2 months)
   ↓
   You can wield mainstream multimodal tools

L5 covers: Stable Diffusion / Midjourney principles, Sora-style video, 3D generation, TTS/ASR.

🌳 Path D: “I’m interested in AI Safety” → L6

A small minority will take this. AI safety is increasingly critical.

For:

• Policy researchers / philosophy background
• Care about AI governance
• Want to do alignment research

L0 → L6 (10 articles · ~1 month)

You can skip middle technical layers. But I recommend at least skimming L3—understanding tech details makes safety discussions sharper.

FAQs

Q1: “I’m bad at math—can I take Path A?”

Yes. L1 is written specifically for “people scarred by high school math.” No intimidating Greek letters; instead, we use diagrams, animations, and Python to make math click.

Reality: L1 requires you to accept a bit of brain-stretching, not become a math whiz.

Q2: “I have no programming background”

L1 has 10 Python crash-course articles. From zero, 2-3 weeks to catch up.

If you really don’t want to learn code—take Path C; many multimodal tools have GUIs.

Q3: “I’ve studied ML before. Can I jump to L3?”

Yes. L0 is for non-technical readers. Skip if you’ve done ML.

Our paths aren’t linear—they’re a map, you choose your route by interest.

Q4: “How long to read it all?”

Full L1-L7: 12-18 months (5-10 hours/week).

Don’t stress this number—you don’t need to do all of it. Most working professionals do L0 + one main path, and that’s enough to make a name in their field.

A Softer Suggestion

Don’t treat AI as something you “should” learn. Treat it as curiosity.

• See a cool AI app—note it, dig into how it works
• See a new concept—look up its origin, skim the paper abstract
• See a hilarious AI fail—analyze why it happened

Long-term motivation never comes from plans. It comes from curiosity.

Do One Thing Right Now

After reading this, don’t go straight to L1. Do something small first:

Open an AI tool, ask it a question that actually troubles you—not “what can you do,” but a real question.

Then apply the 10 moves from L0-05, follow up at least 5 times.

See how far you can get.

This experience is worth more than 5 articles.

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🌟 L0 Primer complete. Confetti.

Next stops to consider:

• Math-curious → L1-01 · Math & Python Crash Course
• Build-first → L4-01 · How LLMs Are Trained
• Create-first → L5-01 · Multimodal Overview

Enjoy the rest of the journey. Stay curious.