Summary of "If I Had to Crack Placements in Just 3 Months (Here's EXACTLY What I'd Do)"

This video provides a comprehensive, no-nonsense, 3-month step-by-step roadmap for students—especially those from tier 2 and tier 3 colleges or those lacking placement support—to prepare effectively for software engineering placements and off-campus jobs. The creator emphasizes hard work, consistency, and discipline, rejecting shortcuts or fancy technologies, focusing instead on core skills, practical projects, and communication.

Main Ideas and Lessons

Target Audience:
- Students serious about their software engineering career.
- Beginners or those with little prior preparation.
- Students from less reputed colleges.
- Those willing to commit full-time effort for 3 months.
- Not for people looking for shortcuts or distractions like blockchain, AI, etc.
Overall Commitment:
- 8 hours per day dedicated to preparation.
- Strict discipline and consistency.
- Avoid distractions, especially Instagram.
- Sleep and physical workout are essential for mental health and learning retention.
Core Components of Preparation:
- Data Structures and Algorithms (DSA).
- Building projects (front-end and full-stack).
- Core computer science subjects (Networking, Operating Systems).
- Communication skills and interview preparation.
- Resume building and social media presence.
- Applying for jobs and networking.

Detailed 3-Month Roadmap

Daily Time Allocation (General)

2 hours of DSA in the morning (most mentally fresh time).
1 hour of DSA in the evening (problem solving + revision).
3 hours dedicated to project work (continuous, distraction-free).
1 hour for core subjects/theory/revision.
1 hour mindful use of social media (posting progress and networking).
Workout and 8+ hours of sleep daily.

Month 1: Foundation and Basics

DSA Topics (1 week each):
- Arrays + Searching + Sorting
- Recursion
- Strings
- Linked Lists
DSA Focus:
- Solve 2-3 easy problems daily (aim for 60-90 problems in the month).
- Avoid hard problems initially.
- Use one programming language consistently (recommended: JavaScript).
- Follow one resource/platform only (recommended: LeetCode).
Projects:
- Build 1 basic front-end project using React and JavaScript.
- Learn React basics: JSX, conditional rendering, API calls.
- Commit code daily on GitHub.
- "Build in public": Post daily progress on LinkedIn and Twitter (~15 mins).
Core Subjects:
- 1 hour daily for Networking (first 2 weeks).
- 1 hour daily for Operating Systems (next 2 weeks).
- Focus on interview-relevant topics (e.g., TCP/IP, deadlocks, scheduling).
- Make concise notes for revision.
Social Media:
- 15 minutes posting progress.
- 45 minutes leisure browsing (only after posting).

Month 2: Intermediate Data Structures and Full-Stack Project

DSA Topics (1 week each):
- Stacks and Queues
- Binary Search
- Two Pointers
- Trees (Binary Trees)
DSA Focus:
- Continue solving 2-3 problems daily.
- Revision of previously solved problems (10-15 mins daily).
- Aim to complete at least 12 modules by end of month.
Projects:
- Build a full-stack project using Node.js and Express.
- Learn backend basics: servers, middleware, REST APIs (GET, POST, PUT, DELETE).
- Database fundamentals: querying, aggregation, optimization.
- Advanced backend topics: authentication (JWT, cookies), email sending, payment gateway integration.
- Deploy project live using AWS, Nginx, custom domain.
- Continue daily GitHub commits and social media updates.
Core Subjects:
- Continue revision and theory related to projects (databases, backend concepts).
Resume & Profile Building:
- Dedicate 1 week to build/update resume and LinkedIn profile.
- Showcase proof of work (GitHub, LeetCode stats, projects).
Communication Skills:
- Spend 2 weeks practicing introduction, project explanation, and fluency.
- Practice speaking in front of mirror or recording yourself.
- English fluency is critical for interviews.

Month 3: Advanced Topics, Project Enhancement, and Job Application

DSA Topics (1 week each):
- Backtracking and Greedy algorithms
- Binary Search Trees (BST) and Heaps (basic level)
- Dynamic Programming (focus on classic problems)
- Graphs (classic problems)
DSA Focus: