Course Details

Courses Descriptions

🗓️ Month-Wise Learning Plan

🧩 Month 1: Programming Foundations & Problem Solving

▪ Core programming using Python / Java (choice-based)
▪ Variables, loops, functions, recursion
▪ Time & space complexity basics
▪ Introduction to problem-solving patterns
▪ Hands-on coding sessions + daily practice

📌 Outcome: Strong logical thinking & coding confidence

🧠 Month 2: Data Structures – Core

▪ Arrays, Strings, Hashing
▪ Stacks, Queues, Linked Lists
▪ Sliding window & two-pointer techniques
▪ Pattern-based problem solving
▪ LeetCode / InterviewBit-style problems

📌 Outcome: Crack easy–medium coding rounds confidently

🌲 Month 3: Data Structures – Advanced

▪ Trees, Binary Search Trees
▪ Heaps & Priority Queues
▪ Graphs (BFS, DFS, shortest path)
▪ Recursion & Backtracking
▪ Dynamic Programming (intro to advanced)

📌 Outcome: Handle complex interview-level problems

🧱 Month 4: System Design – Foundations

▪ How large-scale systems work
▪ Load balancing, caching, databases
▪ CAP theorem, consistency models
▪ REST APIs, monolith vs microservices
▪ Low-level design (LLD) basics

📌 Design Case Studies:
✔ URL Shortener
✔ Notification System
✔ File Storage System

🏗️ Month 5: System Design – Advanced

▪ High-level design (HLD)
▪ Scalable backend architectures
▪ Database sharding & replication
▪ Message queues (Kafka / RabbitMQ)
▪ Designing for millions of users

📌 Design Case Studies:
✔ E-commerce platform (Amazon-style)
✔ Food delivery system (Blinkit-style)
✔ Fintech transaction system

☁️ Month 6: Cloud-Native Development

▪ Backend development using Node.js / Python
▪ REST APIs with authentication & authorization
▪ Cloud basics (AWS/GCP/Azure overview)
▪ Deploying applications on cloud
▪ Real-time databases & storage

📌 Project:
Deploy a production-ready backend service on cloud

🤖 Month 7: AI-Assisted Software Development

▪ Using AI tools for engineering productivity
▪ Prompt engineering for developers
▪ AI for debugging, refactoring & testing
▪ Intro to ML concepts for engineers
▪ Integrating AI APIs into applications

📌 Project:
AI-powered feature inside a real application

⚙️ Month 8: DevOps, MLOps & Production Engineering

▪ CI/CD pipelines (Git, Jenkins/GitHub Actions)
▪ Docker & containerization
▪ Kubernetes basics
▪ Monitoring, logging & alerts
▪ Secure deployments & DevSecOps concepts

📌 Project:
End-to-end CI/CD + cloud deployment pipeline

🎓 Month 9: Capstone Projects & Placement Prep

▪ 2–3 industry-grade capstone projects
▪ Mock interviews (DSA + System Design)
▪ Resume & GitHub optimization
▪ Behavioral & HR interview prep
▪ Placement pipeline & referrals

📌 Capstone Examples:
✔ Scalable SaaS backend (Deloitte-style)
✔ AI-driven analytics platform (PwC/KPMG-style)
✔ Cloud-native enterprise system (TCS-style)

🧪 Key Program Highlights

✔ Live instructor-led classes
✔ Daily coding practice & evaluations
✔ Real-world system design projects
✔ AI-integrated development workflow
✔ Cloud deployment & production exposure
✔ Placement-focused learning path

💼 Placement Model

• Learners pay only 50% fee during the program

• Remaining 50% payable after placement

• Complimentary interview preparation

• Dedicated placement & referral support