Interview Prep Hub

200+ Questions.
Zero Paywalls.

Curated interview questions across DSA, Python, OOP, AI/ML, and SQL — tagged for FAANG and top Indian startups. Track your progress in your browser. No account, no login, no cost.

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YOUR PROGRESS

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questions completed

DSA47 Qs

Python35+ Qs

OOP15 Qs

AI/ML25+ Qs

SQL40+ Qs

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200+Total Qs

47DSA

35+Python

15OOP

25+AI/ML

40+SQL

Target Company

Which track fits your goal?

Every question is tagged — pick the path that matches your target company type.

PBC Track

Product-Based Companies (FAANG)

Google, Amazon, Meta, Microsoft, and Flipkart focus heavily on DSA depth, system design, and algorithmic thinking. Expect hard graph problems, DP, and complex tree traversals.

Hard DSAGraph Algorithms Dynamic ProgrammingSystem DesignComplexity Analysis

Includes: GoogleAmazonMetaMicrosoftFlipkart

Startup Track

Startups & Growth Companies

Zepto, Razorpay, CRED, and Groww value practical problem solving, backend knowledge, SQL, and shipping fast. More breadth, less extreme depth.

Core DSAPython / Backend SQL QueriesOOP DesignReal-world Problems

Includes: RazorpayZeptoCREDGrowwSwiggy

Interview Tracks

All 5 question banks

Each track is self-contained. Practice the ones that match your interview focus.

Core Track

DSA Interview

ArraysTreesGraphsDPHeaps

The most tested category across all companies. Arrays, linked lists, trees, graphs, sorting, and DP — with difficulty ratings and company tags.

DecoratorsGILGeneratorsOOP

Python-specific questions — decorators, generators, comprehensions, the GIL, memory management, and coding problems written in Python.

SOLIDPatternsInheritancePolymorphism

The four pillars, SOLID principles, common design patterns, and Python-specific OOP features. Asked at every seniority level.

Neural NetworksTransformersLLMsNLPML Math

Machine learning fundamentals, deep learning architecture, NLP, computer vision, transformers, and LLMs. For ML/AI engineer roles at AI-first companies.

JoinsWindow FnsIndexesNormalizationOptimization

SQL queries, joins, subqueries, window functions, indexes, normalization, query optimization, and database design. Tested at virtually every backend and data role.

40+ questions

Practice →

Architecture Track

System Design Interview

ScalabilityCachingCAPMicroservicesCase Studies

Scalability, load balancing, databases, messaging, and FAANG case studies — URL shortener, Twitter timeline, Netflix, and more.

DockerKubernetesCI/CDLinuxSRE

Containers, orchestration, pipelines, observability, cloud IAM, Terraform, and incident response — for platform and SRE interviews.

29 questions

Practice →

Easy

Medium

Hard

— bar shows question distribution per track

Quick Jump

Browse by topic

Jump straight to the concept you need — organized by subject.

DSA

Arrays Linked Lists Binary Trees Dynamic Programming Graphs & BFS/DFS Sliding Window Heaps & Priority Queues Sorting Algorithms

Python

Decorators Generators & Iterators GIL & Threading List Comprehensions Memory Management

OOP

Polymorphism SOLID Principles Design Patterns Inheritance vs Composition

AI/ML

Transformers Overfitting & Bias-Variance Backpropagation Loss Functions Attention Mechanism

SQL

SQL Joins Window Functions Query Optimization Normalization Indexes & Execution Plans

Study Plan

4-week interview prep roadmap

Structured path for engineers with 4 weeks before an interview. Adjust based on your strengths.

WEEK 01

DSA Foundations

Arrays, strings, hashing
Sliding window & two pointers
Stacks & queues
Big-O analysis for every topic
5–7 DSA questions/day

WEEK 02

Trees, Graphs & DP

Binary trees & BST
BFS, DFS, Dijkstra
Dynamic programming patterns
Heaps & priority queues
5 DSA + 3 Python questions/day

WEEK 03

Backend & DB Depth

All SQL question bank
OOP + SOLID principles
Python internals (GIL, decorators)
REST API design basics
10 SQL + 5 OOP questions/day

WEEK 04

Review & Mock

Revisit unchecked questions
AI/ML if targeting ML roles
Timed practice sessions
Explain answers out loud
Full mock interview on Day 7

Prep Strategy

How to use this section effectively

Don't just read — do this instead.

STEP 01

Pick your target track

Are you targeting FAANG or startups? Your answer changes which questions to prioritize. DSA depth matters more for FAANG; SQL and backend matter more for startup roles.

STEP 02

Recall before reading

Cover the answer, think for 60 seconds, then read. Active recall is 3× more effective than passive reading — it's the difference between people who prepare and people who just browse.

STEP 03

Mark, track & revisit

Use checkboxes on each track page. Progress saves to localStorage. In your final days, review only unchecked ones — don't waste time re-reading what you already know cold.