AI + Full Stack Career Program: the AI full stack developer roadmap

1. Python

Variables & Data Types

Numbers, strings, booleans and how Python decides what a value is. You will write and run code from the first class rather than reading about it.

Functions

Packaging logic so it can be reused and tested. Arguments, return values, scope, and why small functions beat long ones.

File Handling

Reading and writing files, working with paths, and handling CSV and JSON — the formats real data actually arrives in.

Control Flow

if/else, loops, and the logic that turns a list of statements into a program that makes decisions.

Lists & Dictionaries

The two data structures you will use every day. Indexing, slicing, iteration, and choosing between them.

Error Handling

try/except, reading a traceback properly, and why failing loudly beats failing silently.

2. Projects

Git & GitHub

Commits, branches, pull requests. Your GitHub profile is the portfolio an interviewer actually opens.

Build a CLI Tool

Your first real project: something you use yourself, with arguments, output and a readme.

Debugging

Print statements, breakpoints, and forming a hypothesis before changing code. Debugging is the job.

Command Line

Navigating a filesystem, piping, and running your own tools. Every engineering job assumes this.

Reading Documentation

Finding the answer in official docs instead of a video. The single highest-leverage habit in this course.

3. Web

HTML5

Semantic structure, forms and accessibility basics. The document is the foundation everything else styles.

Responsive Design

Media queries, relative units and testing at 320px. Most of your users are on a phone.

DOM Manipulation

Selecting elements, handling events, and updating the page without a framework — so you understand what frameworks do for you.

CSS3 & Flexbox

The box model, flexbox and grid. Layout stops being guesswork once these click.

JavaScript ES6+

let/const, arrow functions, destructuring, modules, promises and async/await.

Deploy a Live Site

Get it on the internet with a real URL you can send to someone. Nothing is finished until it is deployed.

4. React

Components & Props

Breaking an interface into pieces that compose. Props flow down; that constraint is the whole model.

Fetching APIs

Loading real data, handling loading and error states, and never showing a blank screen.

Tailwind CSS

Utility-first styling and design tokens. Fast to write, and consistent when constrained by a system.

State & Hooks

useState, useEffect and the rules of hooks. When to hold state and when to derive it.

Routing

Multiple pages, URL parameters, and why every view should have its own address.

Forms & Validation

Controlled inputs, validation, and error messages that say what to fix.

5. Backend

REST APIs

Resources, verbs, status codes and designing an endpoint someone else can use without asking you.

SQL & Databases

Tables, joins, indexes and writing a query that stays fast when the table grows.

Docker

Containers, images and why 'works on my machine' stops being a problem.

Node.js & FastAPI

Building a server in both stacks. Routing, middleware, request handling and JSON.

Authentication

Password hashing, sessions and tokens. Why you never store a password and never roll your own crypto.

Deployment

Environment variables, logs, health checks and shipping a backend that stays up.

6. AI

How LLMs Work

Tokens, context windows, sampling and why a model produces different output each time.

Embeddings

Turning text into vectors, measuring similarity, and the idea that powers search and retrieval.

Build a Chatbot

Streaming responses, conversation history and handling failure. Your first shipped AI feature.

Prompt Engineering

System prompts, few-shot examples, structured output, and getting reliable results rather than lucky ones.

RAG

Retrieval-augmented generation — grounding a model in your own documents so answers are citable.

Working with Model APIs

Keys, rate limits, cost, streaming and swapping providers behind one interface.

7. Agents

Tool Use & Function Calling

Letting a model call your code. Schemas, validation and keeping the loop safe.

Automation Workflows

Removing repetitive work from a business. Triggers, steps and failure handling.

Model Context Protocol

A standard way to connect models to tools and data sources.

AI Voice Agents

Speech to text, text to speech and holding a real conversation. This is a live product line at Bibha AI.

Evals & Testing

Measuring whether your AI feature actually works, instead of trusting a demo that went well once.

8. Portfolio

Capstone Project

One substantial project built end to end, deployed, with a readme that explains the decisions you made.

Resume & GitHub Profile

What a hiring manager actually scans for, and how to make thirty seconds count.

Mock Interviews

Practice with working engineers from Bibha AI, with direct feedback.

Portfolio Site

A site that shows the work rather than describing it. Live links, source code, screenshots.

Interview Preparation

Data structures, system design basics and explaining your own project clearly under pressure.