The free Zero-to-CTO curriculum

Be the engineerAI can't replace.

Learn every layer of the stack, free — and become the engineer who can direct any of it.

  • Frontend
  • Backend
  • Data Science
  • Deep Learning
  • DevOps
  • Cloud
  • Product Design
  • Agentic AI

Free, forever. No card. No sales call.

The premise

The narrow developer is gone.The all-rounder takes their place.

CTO — Chief Technology Officer — is the most senior engineering role at a company. They write less code than anyone, and make more decisions than everyone. They architect systems they didn't build. They refuse suggestions that look right but aren't. They judge engineering work at every layer.

AI compressed the path to that chair. The decade of context your seniors needed to make CTO-grade decisions — you build it in a fraction of the time, if you ship widely enough to direct AI well. Time-to-CTO isn't measured in years served now; it's measured in projects shipped and layers covered. Twenty-two isn't too young. Narrow is too narrow.

The "just frontend" or "just backend" developer is the role AI absorbs first. The all-rounder — broad, decision-led, fluent across every layer — is what's left standing.

So this path is six phases wide.

The structure

Six phases. End to end.

Start anywhere. Skip what you already know. The school is yours.

Phase 1

Foundation

How software is actually written. Code, version control, the terminal — the workflow that ships everything else.

~6 weeks

Phase 2

Build

Build interfaces users can touch. The surfaces, the product layer, the front of the house.

~8 weeks

Phase 3

Power

Power what you built. Servers, data, authentication — the engine room users don't see.

~8 weeks

Phase 4

Intelligence

Make products that learn and reason. Data pipelines, machine learning, modern AI, agentic systems.

~6 weeks

Phase 5

Scale

Make products production-ready. Cloud, devops, observability, reliability at real-world scale.

~6 weeks

Phase 6

Lead

Lead the technical organisation. Architecture, code review, hiring, decisions. What the CTO actually does.

~6 weeks

All ~130 chapters

Open any module.

Tap to expand. Pick what you need.

19 modules · 135 chapters

Module 1

Full Stack Basics

2 chapters

Absolute basics of full stack development

Module 2

Consuming APIs In Python

4 chapters

We'll see how to consume api, access the json data from the api response through various examples like weather api, crypto api etc.

Module 3

Flask Basics

6 chapters

Module 4

Advanced Flask & Database

6 chapters

Module 5

Javascript Basics

6 chapters

Module 6

JavaScript Advance

8 chapters

Module 7

Capstone Project - Product Development - Phase 1

8 chapters

Module 8

Capstone Reference for Phase 1 - Building A Micro Product (To-Do List)

8 chapters

Module 9

Authentication - Production Ready Authentication in Python JS

12 chapters

Module 10

Capstone Reference Phase 2 - Movie Review Platform

4 chapters

This course teaches how to build a complete movie review platform from scratch. Students progress from static HTML templates to a full-stack application with user authentication, content moderation, and admin verification workflows. Target Audience: Students who completed Module 07 or know Flask basics Prerequisites: HTML/CSS, JavaScript, Python, Flask basics Total Parts: 4 modules building a complete movie review system

Module 11

Claude Deployment on Ubuntu

10 chapters

Module 12

Docker - From Zero to Production

12 chapters

Module 13

Tinkering

1 chapter

Module 14

React Basics

7 chapters

Module 15

React Advance

5 chapters

Module 16

Building React Apps with Vite

5 chapters

Module 17

Server-Side React with Next.js

10 chapters

Next.js takes your React skills to the next level by adding server-side rendering, file-based routing, and powerful data fetching — all built into a single framework. In this module, you'll migrate...

Module 18

Machine Learning 101

10 chapters

Go from zero to building real ML models. You train your first model before anything is explained — results first, theory second. Cover the full ML workflow: data prep, model training, evaluation, hyperparameter tuning, feature engineering, and shipping a model to production.

Module 19

Deep Learning 101

11 chapters

What this opens

One curriculum.Ten career doors.

By month twelve you've sat in the chair of every role at a tech company — and shipped real work in each. You finish ready to do the job across domains, not just interview for one — ten roles you can step into. And the same breadth lets you skip the job entirely and build your own.

Get hired — in any of these roles

  • Frontend Developer
  • Backend Engineer
  • Full Stack Developer
  • Python Developer
  • DevOps Engineer
  • Cloud Engineer
  • ML Engineer
  • Data Scientist
  • AI Engineer
  • Founding Engineer

Or build your own

  • Found a startup
  • Technical co-founder
  • Run a software agency
  • Freelance across domains
  • Ship for paying clients

And the public profile you build along the way is the proof that makes any of these believable — to a recruiter, an investor, or a client.

Pick a specialty later. Be general first.

For those who want the live version

A few times a year, we run a small live cohort — 30 seats, daily 8pm sessions, mentor review on every post, demo day at month twelve. Twelve months. By application.

See the cohort →

Start where you are.

Enrol free. Pick any module. Build at your pace.