Data structures are ways of organising and storing data — such as arrays, linked lists, stacks, queues, trees, hashmaps and graphs — while algorithms are step-by-step techniques for solving problems efficiently using that data, like sorting, searching or dynamic programming. Tech companies in India rely on DSA rounds because they test problem-solving ability, coding fundamentals and how optimally you can think under constraints, which are hard to evaluate any other way.

Pick one language and stick to it, then move topic by topic: arrays and strings, recursion, linked lists, stacks and queues, hashing, trees, heaps, graphs and finally dynamic programming. Solve two to three problems daily on platforms like LeetCode or HackerRank, maintain notes on patterns you encounter, and move to the next topic only after solving a decent number of problems on the current one. With consistent practice, most people become interview-ready in four to six months.

Get thoroughly comfortable with the Java Collections Framework — ArrayList, HashMap, HashSet, PriorityQueue and Deque — since most interview solutions use them, and then solve problems pattern-wise: two pointers, sliding window, binary search, recursion, graphs and dynamic programming. Start with easy and medium-level questions, since that is where most product company screens sit, and always reason about time and space complexity while coding, because interviewers evaluate your thought process, not just whether the code runs.

It depends on how disciplined you are with self-study. A structured course helps if you need a fixed roadmap, deadlines and doubt support, which is useful when placement season leaves you with limited time. If you are self-driven, a free roadmap plus consistent practice can work just as well. Whichever route you take, prioritise the patterns your target companies repeat, solve previous placement papers, and complete a few mock coding rounds before the real tests begin.

Freshers are mostly tested on fundamentals: OOPs concepts like inheritance, polymorphism, abstraction and encapsulation, String handling and immutability, Collections such as ArrayList vs LinkedList and HashMap internals, exception handling, access modifiers, the static keyword and basic multithreading. Expect one or two live coding questions as well, usually on arrays, strings or loops, so keep practising simple coding problems alongside theory.

At this level, interviewers skip basics and go deep: JVM internals and garbage collection, concurrency topics like volatile, ConcurrentHashMap and ExecutorService, Java 8 features such as Streams and lambdas, Spring Boot internals, microservices design, design patterns, and sometimes messaging systems like Kafka. You will also face scenario questions such as debugging a memory leak in production, so prepare real examples from your own projects to back up every answer.

First build the fundamentals: scalability, load balancing, caching, SQL vs NoSQL, indexing, sharding, replication and message queues. Next, learn a standard answering framework — clarify requirements, estimate scale, sketch the high-level design, deep-dive into components, and close with bottlenecks and trade-offs. Then practice 15 to 20 classic designs like a URL shortener, chat app, news feed and ride-sharing system, and finish with mock interviews, because articulating trade-offs under time pressure is a separate skill from reading material.

The classics repeat across companies: design a URL shortener, a WhatsApp-style chat system, an Instagram feed, Twitter, Uber, a notification system, a rate limiter, YouTube and a payment or wallet system. For each one, interviewers judge how you handle scale, consistency, availability and latency trade-offs, so instead of memorising diagrams, understand the reasoning — for example, why a chat app needs WebSockets and message queues, or how a feed uses caching and fan-out strategies.

A good book builds your vocabulary and shows how standard problems are decomposed, which is essential in the early stage. But system design interviews are interactive discussions, and a book alone cannot prepare you for follow-up questions, pushback on your design or time pressure. Use it as your foundation, then supplement it with practice designs, mock interviews and feedback from experienced engineers — candidates who only read material usually struggle to drive the conversation in the actual interview.

It is a widely used online preparation course that walks through common system design questions — like designing TinyURL, WhatsApp or a Twitter feed — using a repeatable framework and clear diagrams. It is a solid starting point if you are new to design rounds because it teaches you how to structure an answer. Treat it as a foundation rather than complete preparation, though; pair it with newer case studies, hands-on practice and mocks, since interviewers increasingly ask designs beyond the standard list.