One membership, five tracks

Start anywhere — each track stands alone; together they build on each other.

5
Tracks
43
Lessons
$10
A month, or $100 a year
$0
In required tools

Understand · 16 lessons

See the machine clearly

How the machine actually works, in plain language. No code. The lens.

Start with Understand →

Create · 7 lessons

Make media in code

Make text, images, music, voice, and video — in Python notebooks handed to you. The craft.

Start with Create →

Engine · 5 lessons

The engine room

The ten lines behind every chat window — the engines, on your terms. The controls.

Start with Engine →

Research · 9 lessons

Evidence you can cite

Turn public archives into evidence you can cite. The record.

Start with Research →

Know · 6 lessons

Read the science yourself

Reach the scholarly record — reviewed, cited, contested — without a badge. The proof.

Start with Know →

Every lesson leaves something in your hands

Not just videos — real Python you keep.

A written companion from every lesson — the argument in full, the line worth keeping, one thing to try today. Working Python notebooks, annotated line by line and built to be changed: swap one variable and they run on your own data. The things you make along the way — generated images, music, narrated video, and cited datasets built from primary sources. And a library that grows: new lessons and new courses land inside your membership, no re-buying.

What these skills build

The editor's weekly practice, in public

Every Saturday, AI News Social — orchestrated by the same person who teaches every lesson here — evaluates ~4,000 sources on AI and society, scores them on a nine-criterion rubric, and turns the result into essays, category reports, podcasts, and thirty interactive analyses, in English and in Spanish. It runs on this membership's skills: Investigar's public-archive evidence, Motor's direct lines to the models, Crear's media made in code, Entender's judgment about what it all means. The courses won't hand you this pipeline on day one — they teach the pieces it's built from.

AI News Social — this week's thematic networkAI News Social — this week's lead illustrationAI News Social — this week's narrative frames

Images: AI News Social, this week's edition — they change every Saturday. See this week's edition, free →

Who it's for

Built for professionals — not hype-chasers.

For working professionals who need to understand and operate AI for real work — without enrolling in a degree to do it. For people tired of hype threads and demo reels who want to know how it actually works, and why. It's not a feed of the latest model news: TertulIA teaches the durable understanding underneath the headlines — the part that's still true next year.

Who teaches this

Dr. Diego Bonilla
Dr. Diego Bonilla
Full Professor of Communication · Sacramento State · UNAM

Dr. Diego Bonilla is a Full Professor of Communication Studies at Sacramento State and teaches graduate courses at UNAM in Mexico City. He created COMS 101 — Information Management and Privacy — and still teaches it; built a six-course digital-literacy minor approved unanimously by faculty; and directed the faculty learning community where these lessons were first taught to professors. He builds his own AI tools — fifteen and counting.

The full record →

Where it all runs

Everything on Google's free tier — even anonymously.

Everything in TertulIA runs on Google: Colab for the notebooks, AI Studio as the on-ramp, and Google's own generative models. You can do all of it on a free account — even an anonymous one: no credit card, no personal information you don't wish to give. If you're a US student, your .edu address currently unlocks Google's most advanced AI at no cost — most students never learn they have it. And nothing here is throwaway: the day you want to scale, the same notebook and the same code are one step from Google's paid tier.

Questions, answered

  • Do I need to know how to code?

    No — and you'll still leave running real Python. Understand uses no code at all. In Create, Engine, and Research you work in real Colab notebooks, but the code is handed to you: Google's AI Studio writes it when you click Get code, and in Research you describe what you want in plain words and Gemini writes it. When something breaks, you paste the error and Gemini fixes it. Every notebook runs by changing one line.

  • Do I have to pay for the AI tools?

    No. Everything runs on Google's free tier — Colab, AI Studio, and the generative models. An anonymous Google account works; and a US .edu address unlocks Google's advanced tier at no cost.

  • What do I actually keep?

    A written companion from every lesson, working Python notebooks that run on your own data forever, and the things the notebooks make — images, music, narrated video, and cited datasets built from primary sources.

  • Can I see inside a course before joining?

    Each course page lists every lesson by name — the full curriculum is public. The lessons themselves are for members; joining takes a minute, and you can cancel anytime.

  • ¿Prefieres español?

    The full library is also taught in Spanish — not translated, but built for Latin America: the same method aimed at Spanish-language records and Latin American scholarship. See TertulIA Completo (LATAM) ($5/mes).