Full-Stack + GenAI

Month 1 – Programming & Computer Science Foundations

Objective: Build a solid foundation in Python, logic, data structures, and Git.

Week 1: Developer Setup & Programming Basics

• Python fundamentals (syntax, data types, loops, functions)

• Command-line basics & IDE setup

• Git & GitHub (init, commit, branch, pull request) Deliverables:

• 3 mini projects: Calculator, File Organizer, Palindrome Checker

• GitHub repo with 3 commits and a proper README

• Week 2: Data Structures – Arrays & Strings

• Arrays, lists, tuples, dictionaries

• String slicing, searching, and sorting

• Big O Notation (intro) Deliverables:

• 5 LeetCode Easy problems

• Student Record Organizer CLI App

• Week 3: Functions, OOP & Modular Programming

• OOP concepts: classes, inheritance, encapsulation

• Exception handling & modular code Deliverables:

• Library Management System (Class-based design)

• Week 4: Stacks, Queues, and File Handling

• Stack & Queue implementation using lists

• File I/O, JSON serialization Capstone Project: CLI Expense Tracker

• Month Outcome: Strong Python + OOP foundation and first project on GitHub.

Month 2 – Frontend Development (HTML, CSS, JavaScript, React)

Objective: Learn to build professional, interactive, and responsive web apps.

• Week 5: HTML & CSS Fundamentals

• HTML structure, tags, forms, accessibility

• CSS basics, Flexbox, Grid, media queries Deliverables:

• Portfolio landing page (static HTML + CSS)

• Week 6: JavaScript Basics

• Variables, functions, loops, conditionals

• DOM Manipulation & Event Handling Project: Weather Dashboard using OpenWeather API

• Week 7: Modern JavaScript

• ES6+, async/await, promises

• API fetching, error handling, modular scripts Project: Movie Search App (TMDB API)

• Week 8: React Basics

• Components, JSX, Props, State, Hooks

• React Router, forms, and conditional rendering Capstone: Dynamic React Portfolio (Deployed on

• Netlify)

• Month Outcome: Proficient in React & JS; deployed portfolio website.

Month 3 – Backend Development (Node.js, Express, MongoDB)

Objective: Master backend development and REST API design.

• Week 9: Node.js + Express.js

• Server creation, routes, middlewares

• REST API fundamentals Deliverables: To-Do API (CRUD Operations)

• Week 10: MongoDB + Mongoose ORM

• Schemas, models, CRUD operations

• Validation and error handling Deliverables: User Management API

• Week 11: Authentication & Security

• JWT tokens, password hashing, roles

• Environment variables, rate-limiting, CORS Deliverables: Notes App API with JWT auth

• Week 12: Backend Testing + Deployment

• Postman API testing, error handling

• Deploy to Render or Railway Capstone Project: Blogify API (Auth + Mongo + CRUD)

• Month Outcome: Full backend developer skills with deployed REST API.

Month 4 – Full Stack Integration (MERN)

Objective: Build and deploy complete full-stack web applications.

• Week 13: Frontend-Backend Integration

• Fetching data using Axios

• CORS handling, error boundaries Deliverables: Blogify full stack integration

• Week 14: State Management

• Context API or Redux Toolkit

• User authentication and protected routes Deliverables: Enhanced Blogify (Login/Logout flows)

• Week 15: Advanced Full Stack Features

• File uploads, search, pagination, real-time updates (Socket.io) Deliverables: Image Gallery / Task Tracker App

• Week 16: CI/CD & Cloud Deployment

• .env management, GitHub Actions, Vercel deployment Capstone Project: ProjectHub App – Project Management Tool

• Month Outcome: Full stack MERN developer with production-ready deployment.

Month 5 – Data Structures & Algorithms (Intermediate–Advanced)

Objective: Master algorithmic problem solving and core interview skills.

• Week 17: Recursion & Backtracking

• Subsets, permutations, backtracking strategies Deliverables: 10 recursion problems + visualization tool

• Week 18: Linked Lists & Trees

• Singly/Doubly Linked Lists, Tree Traversals Project: Binary Tree Visualizer

• Week 19: Graphs & Greedy Algorithms

• BFS/DFS, Dijkstra’s, Prim’s, Kruskal’s Project: Graph Path Visualizer

• Week 20: Dynamic Programming

• Tabulation, memoization, subsequences Capstone: Algorithm Playground (Interactive Visualizer)

• Month Outcome: Advanced DSA proficiency with interactive visualization project.

Month 6 – AI for Developers

Objective: Build AI-powered web applications and integrate LLMs.

• Week 21: AI/ML Fundamentals

• Overview of ML concepts for developers Project: Sentiment Analysis (HuggingFace Pipeline)

• Week 22: AI API Integration

• OpenAI, HuggingFace APIs, prompt design Project: AI Blog Generator

• Week 23: Building AI Chatbots

• React + OpenAI API integration, context memory Project: AI Support Chatbot (ChatGPT-style)

• Week 24: LangChain + RAG Concepts

• LangChain, memory, chaining, model integration Capstone: Resume Reviewer AI (LLM + MERN)

• Month Outcome: Proficient in AI integration; deployed AI app.

Month 7 – Cloud, Testing & System Design

Objective: Learn scalable architectures, Docker, and testing for reliability.

• Week 25: Cloud Basics

• Docker, AWS EC2/S3 basics Deliverables: Dockerized Node.js app on AWS

• Week 26: Testing & CI/CD

• Unit testing, Jest, integration tests, GitHub Actions Deliverables: Automated CI/CD pipeline

• Week 27: System Design Basics

• Caching, load balancing, microservices design Deliverables: System Design Document for Twitter Clone

• Week 28: Microservices Architecture

• Event-driven design, message queues, Kafka basics Capstone: URL Shortener + Analytics Microservice

• Month Outcome: Cloud and system design readiness + deployed microservice.

Month 8 – Final Capstone & Career Launch

Objective: Build an AI SaaS product and prepare for job interviews.

• Week 29: Product Ideation & Design

• Wireframes, feature scoping, API planning

• Week 30: Core Development Sprint

• Build main backend and frontend components

• Week 31: AI Integration + Testing

• Add AI microservice, test & optimize

• Week 32: Demo & Career Prep

• Resume workshop, LinkedIn optimization

• Mock interviews: DSA + System Design + HR

• Final Capstone Options: 1. AI Interview Coach 2. Code Explainer AI 3. AI Productivity Dashboard

• Month Outcome: Fully deployed AI SaaS + career-ready portfolio.

Job Readiness Add-on Track (Parallel)

1. DSA: 2 problems/day, 200+ solved by end of course

2. Resume: Month 3 & 8 revisions

3. Portfolio: 8+ projects, polished README

4. Mock Interviews: Month 7–8, 3 rounds

5. Hackathons: Every 2 months, team-based

6. Final Outcome: - 8 Projects (6 Major + 2 Capstone) - DSA mastery + AI/Cloud + Full Stack skills Resume,LinkedIn, GitHub portfolio ready - Job/interview preparation done