Learn one topic at a time — arrays, strings, two pointers, sliding window, linked lists, stacks, trees, graphs, and dynamic programming — and solve a fixed number of problems daily on a coding platform. Focus on recognizing patterns instead of memorizing solutions, since interviewers usually twist a known problem to test depth. Keep a sheet of problems you failed and re-solve them weekly. In the last 2–3 weeks, move to timed practice and mock interviews to simulate real interview pressure.

Start by restating the problem and clarifying constraints like input size, data range, and edge cases. State a brute-force approach first, analyze its complexity, then improve it step by step while thinking aloud so the interviewer can follow your reasoning. After coding, dry-run your solution on a normal input and an edge case before saying you are done. Interviewers evaluate structure and communication as heavily as the final optimal answer.

Freshers are most often tested on arrays and strings (reversal, rotation, anagrams), linked lists (cycle detection, reversal), stacks and queues, binary trees and BSTs, recursion, searching and sorting, and entry-level dynamic programming like climbing stairs or knapsack. Rather than memorizing answers, learn the pattern behind each question type, because companies in India usually ask the same patterns with a small twist. Working through a curated set of the top 100–150 problems covers the majority of fresher interview rounds.

A PDF is helpful for revision because it condenses frequently asked problems into one place, but reading alone does not build recall. You retain patterns only by coding the solutions yourself under time limits and re-attempting the ones you get wrong. Treat the PDF as a checklist and solve every listed problem hands-on on a coding platform before marking it as done.

Get comfortable with Java's Collections framework — ArrayList, HashMap, HashSet, PriorityQueue, and ArrayDeque — since most solutions depend on quickly picking the right data structure. Implement core structures like linked lists, stacks, and trees at least once to understand their internals, and watch for Java-specific traps such as integer overflow, null handling, and string immutability. Also confirm the company's language policy early, though most product companies in India allow Java for DSA rounds.

It is a round where you design a large-scale system — such as a URL shortener, chat app, or food delivery platform — instead of solving an algorithm puzzle. The interviewer evaluates how you gather requirements, estimate scale, choose databases, handle failures, and justify trade-offs. It is typically asked for mid and senior roles, though many startups in India now include a basic design round even for freshers.

Build fundamentals first: load balancing, caching, database indexing, SQL vs NoSQL, sharding, replication, and consistency models. Then study 10–15 classic design problems — URL shortener, WhatsApp, Twitter feed, Uber, rate limiter — and practice drawing a complete design on a whiteboard within 35–45 minutes. Finish with mock design rounds, because explaining trade-offs aloud is a separate skill from simply knowing the concepts.

Follow a fixed framework: clarify functional and non-functional requirements, estimate traffic and storage, define the API, sketch the data model, draw the high-level architecture, and then deep-dive into bottlenecks like caching, partitioning, and failure handling. Keep verbalizing your reasoning and invite feedback instead of silently drawing. Closing by summarizing the trade-offs you consciously made leaves a stronger impression than a rushed, perfect-looking diagram.

The classics include designing a URL shortener, a WhatsApp-style chat system, a Twitter or Instagram feed, YouTube, Uber, a food delivery app, a notification system, and a rate limiter. These all reuse the same building blocks — consistent hashing, caching, message queues, load balancers, and database scaling — so mastering a dozen designs lets you handle most variations. Interviewers often add a twist like multi-region support or offline mode to test depth.

Volume 1 is a strong starting point because it walks through popular designs like the URL shortener, rate limiter, and chat system with clear diagrams, and Volume 2 adds newer topics such as proximity systems and distributed message queues. On its own it may not be sufficient for senior roles, so pair it with whiteboard practice and mock design interviews. Use the book to learn how to structure an answer, then apply that structure to brand-new problems.

It is a well-known online course that teaches system design through simplified case studies such as URL shorteners, chat apps, and video streaming, using repeatable answer templates. It is beginner-friendly for quickly picking up the vocabulary and flow of a design discussion. Since its depth is limited compared with real interview expectations, treat it as a first step and then practice open-ended designs on your own.

Most candidates doing FAANG interview preparation in India follow a 5–6 month plan: months 1–3 for DSA patterns and roughly 300–400 problems, month 4 for LLD and core CS subjects like OS, DBMS, and networks, month 5 for system design, and the final month for resume shortlisting, behavioral prep, and mock interviews. Adjust the timeline based on whether you are starting from scratch or already solving medium-level problems comfortably. Freshers should also invest in solid projects, while working professionals need a steadier, longer schedule.

It depends on your discipline and starting level. If you can follow a self-made plan with free curated problem lists, a paid course may add little value. It pays off when you need accountability, structured feedback, guided mock interviews, or a compressed timeline. Before paying, check whether the course includes live mocks with working engineers and doubt support, since recorded lectures alone rarely change outcomes.

Experienced candidates get far more weight on system design, architecture decisions, and behavioral rounds that probe impact and leadership, while DSA still appears — usually one solid round. Prioritize refreshing core data structures first, then spend most of your time designing real-scale systems, ideally from your own work domain. Also prepare crisp stories around scale, trade-offs, and failures, because at 3+ years of experience these rounds decide both your level and your compensation.