AI Pro Roadmap

AI user se AI professional tak

AI professional woh hai jo problem define kare, simplest capable system chune, usay evidence mein ground kare, failures test kare, data aur logon ko protect kare, ship kare, aur value explain kar sake. Tool familiarity finish line nahi hai.

18 complete free courses · 340 public lessons · no income or job guarantee

The sequence

Char stages — har stage pe reviewable proof

Courses randomly collect mat karo. Har stage aisi evidence ke saath khatam karo jo koi doosra insaan review kar sake.

1

Control the model

Ready now

Context, source boundaries, structured briefs, examples, task decomposition aur review seekho. Goal repeatable kaam hai — clever prompt tricks nahi.

Proof →Tested prompt package aur ek reusable assistant, ek real task ke liye.
2

Build reliable AI systems

Ready now

Chat se aage: APIs, JSON, tool contracts, data, multimodal inputs, retrieval, agents, evals, security, logs aur deployment.

Proof →Deployed workflow — README, test set, eval results, threat model, cost log aur demo.
4

Run an ethical earning experiment

★ Flagship

Ek useful outcome package karo, demand validate karo, written scope aur payment milestones use karo, human QA ke saath deliver karo.

Proof →Offer, portfolio sample, discovery notes, proposal, scope, delivery checklist aur 30-day review.

Professional core

Das competencies — das tool logos nahi

Builder core official API, retrieval, agent, evaluation aur safety guidance ki disciplines follow karta hai.

01Problem framing aur acceptance criteria
02Source verification, research, citation discipline
03Prompt, context aur reusable instruction design
04JSON, HTTP, APIs, structured outputs, tool contracts
05Spreadsheet, document, image aur audio workflows
06Retrieval, grounded answers, permissions, freshness
07Agents, state, retries, idempotency, human approval
08Evals, red-team cases, logging, cost, reliability
09Privacy, security, consent, copyright, disclosure
10Portfolio proof, discovery, scope, delivery, review
Primary professional referencesOpenAI agents guideOpenAI evals guide

Earning paths

Skill ko value mein kaise badlein

Income useful work, proof, fit, timing aur execution ka outcome hai. Curriculum controllable steps sikhata hai — guaranteed number nahi.

Employment

Proof to build

Role-specific evidence pack aur ek chhota workflow jo target job se relevant ho.

First honest test

Selectively apply karo, interviews practise karo, application quality measure karo — promised offer nahi.

AI service

Proof to build

Do honest samples, narrow offer, written scope aur human-QA checklist.

First honest test

Problem validate karo, chhota paid pilot propose karo, delivery evidence record karo.

Builder

Proof to build

Deployed workflow — tests, logs, permissions, cost notes aur clear handoff.

First honest test

Pehle ek bounded workflow solve karo — phir agents ya bara stack propose karo.

Creator

Proof to build

Content ya product sample jo real audience question se juda ho, transparent claims ke saath.

First honest test

Chhota experiment publish karo, first-party evidence review karo, phir expand karo.

First 90 days

Ek realistic sprint — apni raftar se

Days 1–30

Foundation

AI Fundamentals aur Advanced Prompt Engineering khatam karo. Tested outputs save karo — completion screenshots nahi.

Days 31–60

Build

Applied AI Builder aur ek specialty capstone complete karo. Do honest portfolio artifacts publish karo, limitations ke saath.

Days 61–90

Validate

Ek earning lane chuno. Interviews, applications, audience tests ya chhota paid-pilot proposal — evidence weekly review karo.

Pace ko kaam, parhai, bijli aur internet ke hisaab se adjust karo. Completion quality > calendar promise.

Not promised

What this roadmap does not promise

Ye roadmap salary, client, audience, certification equivalence ya fixed completion time promise nahi karta. Ye deta hai: sequenced practice, review criteria, aur portfolio proof. Employers, clients aur markets apne faisle khud karte hain.