Placement Preparation — Complete Campus & Off-Campus Guide
Before you start: no specific prerequisite technology is required, though [DSA](/academies/education/dsa/overview) is heavily referenced — the coding-round and technical-interview sections assume that foundation.
Getting placed at a top tech company requires strategy. This guide covers the full journey — aptitude rounds, coding tests, technical interviews, and HR — with what actually works.
Why This Exists (The Hook)
Being technically capable and getting an offer are not the same thing — plenty of strong engineers get rejected because their resume never got past an automated screening tool, or because they froze in an HR round they dismissed as "just a formality." Placement prep exists because the hiring funnel has multiple genuinely different filters (ATS keyword matching, aptitude speed, DSA correctness, communication in an HR round) and being unprepared for any single one of them can end the process — regardless of how strong you are at the others.
Analogy — Think of the hiring funnel like a multi-stage obstacle course, not one big exam. A marathon tests one thing (endurance) end to end. An obstacle course tests several different, unrelated skills in sequence — climbing, balance, sprinting — and being excellent at climbing doesn't help you at all if you can't clear the balance beam. Being a strong coder (DSA round) doesn't automatically carry you through an ATS keyword filter or an HR round testing communication — each stage needs its own specific preparation.
Try it (2 minutes) — Reason through why the guide says constraints like "n ≤ 10⁵" should tell you the expected time complexity before you even start coding, without looking anything up: competitive judges typically expect a solution to run in about one second, and a modern CPU can execute roughly 10⁸ simple operations per second. If a problem's input size is n ≤ 10⁵, and an O(n²) solution would mean roughly (10⁵)² = 10¹⁰ operations — far more than a CPU can do in a second — what does that tell you about whether an O(n²) approach can possibly be the intended solution, before you've written a single line of code?
The Hiring Process
1. Resume Screening
ATS + human
→
2. Online Assessment
Aptitude + coding
→
3-4. Technical Rounds
DSA + CS fundamentals
→
5. System Design
Senior roles only
→
6. HR Round
Communication, fit
Most companies follow this funnel:
1. Resume Screening (ATS + Human)
2. Online Assessment (Aptitude + Coding)
3. Technical Interview Round 1 (DSA)
4. Technical Interview Round 2 (DSA + CS fundamentals)
5. Technical Interview Round 3 (System Design — for senior roles)
6. HR/Managerial Round
7. Offer
Campus placement timeline (India):
August–October: PSU, core companies
October–December: Product companies (Tier 1)
November–February: Service companies (TCS, Infosys, Wipro, etc.)
Year-round: Startups via LinkedIn/referrals
Resume — Getting Past ATS
One page rule: For freshers, strictly one page
Format: Simple, ATS-friendly (no tables, columns, graphics)
Sections:
1. Contact (name, email, phone, LinkedIn, GitHub)
2. Education (CGPA if > 7.5)
3. Skills (Technologies you actually know)
4. Projects (2-3 strong ones)
5. Internships (if any)
6. Achievements (coding competitions, hackathons)
Project descriptions — use STAR format:
Bad: "Made an e-commerce website"
Good: "Built full-stack e-commerce app with React + Node.js,
handling 1000+ products, JWT auth, Razorpay integration.
Reduced page load by 40% with Redis caching."
Skills section — be specific:
Languages: Python, Java, JavaScript, C++
Frameworks: React, Node.js, Spring Boot, Django
Databases: PostgreSQL, MongoDB, Redis
Tools: Git, Docker, AWS (EC2, S3), Linux
DO NOT list: MS Word, PowerPoint, "good communication"
ATS keywords: Match the job description language
JD says "proficient in Java" → your resume says "Java"
JD says "REST APIs" → your resume mentions "REST APIs"
Aptitude Test Strategy
Tests usually 60-90 min, 3 sections:
QUANTITATIVE APTITUDE (30-40 min, 20-25 questions)
Speed: 70-90 seconds per question
Formulae to memorize:
Time & Work:
Work = 1/n per day (person finishing in n days)
Together: 1/a + 1/b = 1/T → T = ab/(a+b)
Time Speed Distance:
D = S × T, Average speed = 2xy/(x+y) for equal distances
Train problems: Add lengths, use relative speed
Percentage:
% change = (new-old)/old × 100
Successive: a% then b% = a+b+ab/100
Probability:
P(A) = favorable outcomes / total outcomes
P(A∩B) = P(A) × P(B) for independent events
Permutation & Combination:
nPr = n!/(n-r)! nCr = n!/[r!(n-r)!]
Arrange n items = n!
Select r from n = nCr
LOGICAL REASONING (20-30 min)
Directions, Blood relations, Syllogisms, Puzzles
Syllogism approach:
Draw Venn diagrams mentally
"All A are B, Some B are C"
→ Some A are C (not definite), Some C are A (not definite)
Blood relations: Draw a family tree, always
VERBAL ABILITY (15-20 min)
Reading Comprehension: Read passage → answer ONLY from passage
Error identification: Subject-verb agreement, tenses, prepositions
Fill in the blanks: Context clues
Coding Round Strategy
Most common: 2-3 coding problems in 60-90 minutes (HackerRank/HackerEarth/Codility)
Difficulty:
Service companies (TCS, Infosys): Easy — loops, arrays, strings
Product MNC (Amazon, Microsoft, Adobe): Medium — DSA
Top product (Google, Atlassian): Medium-Hard — advanced DSA
How to approach each problem:
1. Read COMPLETELY before coding
2. Check constraints: n ≤ 10⁶ → O(n log n) at worst
3. Write brute force first, then optimize
4. Test with examples on paper
5. Handle edge cases: empty input, single element, max value
Constraints → expected time complexity:
n ≤ 10: O(n!) — backtracking, permutations
n ≤ 20: O(2ⁿ) — DP with bitmask
n ≤ 500: O(n³) — 3 nested loops
n ≤ 5000: O(n²) — 2 nested loops
n ≤ 10⁵: O(n log n) — sorting, binary search, heap
n ≤ 10⁶: O(n) — single pass, hash map
n ≤ 10⁸: O(log n) — binary search only
n ≤ 10¹⁸: O(1) — math formula
Must-know patterns:
Arrays: Two pointers, sliding window, prefix sum, sorting
Strings: Two pointers, hashing, KMP, sliding window
Linked Lists: Two pointers (fast/slow), reversal, merge
Trees: DFS/BFS, recursion, level order
Graphs: BFS (shortest path), DFS (connected components), Dijkstra
DP: 1D (Fibonacci variants), 2D (LCS, LIS), interval DP
Technical Interview — What They Really Ask
Round 1 typically: 1 medium DSA problem + discussion
FORMAT:
"Tell me about yourself" — 2 minute pitch, not your whole life
"Explain this project" — pick your strongest project, know it deeply
DSA problem — think aloud, code cleanly, test it
"Any questions for me?" — always have 2-3 questions ready
DSA Interview Approach:
1. Clarify edge cases and constraints (2-3 min)
2. Describe your approach before coding
3. Write clean code with good variable names
4. Test with the example input
5. State time and space complexity
Common mistakes:
→ Jumping to code without thinking
→ Using single-letter variable names (x, y, z)
→ Not testing your code
→ Saying "I don't know" without attempting
When stuck:
Start with brute force — "Naively this would be O(n²) by..."
Think aloud — interviewer may give hints
Draw an example — concrete often reveals pattern
Consider patterns: is this a BFS? sliding window? DP?
Projects — questions you WILL be asked:
"What was the most challenging part?"
"How would you scale this to 1 million users?"
"What would you do differently now?"
"Explain your database schema"
"Why did you choose X technology over Y?"
CS Fundamentals they test:
OOP: Polymorphism, Encapsulation, Inheritance, Abstraction
OS: Process vs Thread, Deadlock, Virtual Memory
DBMS: Normalization, SQL queries, Indexing, Transactions
Networks: TCP vs UDP, HTTP vs HTTPS, REST API
HR Round
HR isn't formality — it CAN eliminate you
Questions and what they're really asking:
"Tell me about yourself" — Can you communicate professionally?
Template: "I'm a [year] student at [college] studying [branch].
I've been focusing on [your specialty]. I built [project] which [impact].
Most recently I [recent achievement]. I'm excited about [specific thing
about this company]."
"Why our company?" — Did you research us or are you spray applying?
Research: Company's recent work, products, culture, what they solve
Bad: "Great company, good package, great opportunity"
Good: "I've been using [product] and was impressed by how it handles [X].
I'd love to work on [specific team/problem]."
"Weakness" — Self-awareness + growth mindset
Bad: "I work too hard" (cliché)
Bad: "I don't have weaknesses" (arrogant)
Good: "I sometimes get too detail-oriented and lose track of deadline.
I've been working on this by setting time-boxes for each task."
"Where do you see yourself in 5 years?" — Ambitious but committed?
"I want to grow into a strong engineer, contributing to meaningful products.
I'd like to take on more responsibility as I build expertise. I see [company]
as a place where that growth is possible."
Salary negotiation:
Never be first to name a number
Research market rate first (LinkedIn Salary, Glassdoor, Levels.fyi)
"I'm flexible and open to discussing based on the role and responsibilities"
If pressed: give a range with your target at the bottom
Company-Wise Preparation
FAANG (Google, Amazon, Microsoft, Meta, Apple):
Focus: DSA excellence (Leetcode Medium/Hard), System Design
Timeline: 3-6 months preparation
Platform: Leetcode (company-tagged questions)
Books: CTCI, EPI
Indian Product Companies (Flipkart, Swiggy, Razorpay, CRED, Zepto):
Focus: DSA (Medium), system design basics, 1 good project
Timeline: 2-3 months
MNC (Adobe, Atlassian, Intuit, ThoughtWorks):
Focus: DSA (Easy-Medium), CS fundamentals, projects
Service Companies (TCS, Infosys, Wipro, HCL, Cognizant):
Focus: Aptitude, verbal, basic coding
Timeline: 2-4 weeks
Note: Large intake, most CS graduates who apply get offers
Startups:
Focus: Can you ship features? Projects matter more than competitive DSA
Interview: More practical — take-home project, code review
Upside: More responsibility, equity, learning
Downside: Risk, may not have strong mentorship
