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Guides for your first job

DSA prep that fitsin four weeks, not four months.

Six topics, not five hundred problems. Arrays, hashing, two pointers, stacks, BFS/DFS, basic DP — how to talk through brute force to optimal out loud, and a realistic schedule.

  • Six topicsthat cover most fresher rounds
  • Talk it throughbrute force to optimal
  • 4-weekrealistic schedule

Arrays

Traversal, in-place manipulation, prefix sums, sliding window. The most common building block for everything else on this list.

Hashing

Hash maps and sets for O(1) lookups — turns a huge share of "find pairs" and "count occurrences" problems from brute-force O(n²) into O(n).

Two pointers

Sorted-array and string problems where moving two indices inward or across avoids nested loops — a small pattern that shows up constantly.

Stacks

Matching brackets, next-greater-element, monotonic stack problems — a compact topic with high interview-frequency for its size.

BFS / DFS

Graph and tree traversal — the base for most "connected components", "shortest path in unweighted graph" and "explore all paths" questions.

Basic DP

Just the foundational patterns — 1D DP (climbing stairs, house robber style), simple 2D DP (grid paths). Skip advanced DP for a first-round prep pass.

Explaining brute force to optimal, out loud

This is the part most self-study misses — solving a problem silently doesn\'t train the skill an interview actually tests.

1. State the brute force first, out loud

Even if it's obviously slow, say it: "the simplest approach would be to check every pair, which is O(n²)". This shows you can reason from first principles, and it's a normal, expected first step, not a weakness to hide.

2. Name the bottleneck

"The nested loop is what makes this slow — we're re-checking information we've already seen." Naming exactly why it's slow is what leads naturally into the better approach.

3. Introduce the optimisation

"If I store what I've seen in a hash map, I can look it up in O(1) instead of re-scanning." Connect the optimisation directly to the bottleneck you just named.

4. State the final complexity

"This brings it down to O(n) time, O(n) space." Interviewers are listening for this explicitly — say it, don't make them ask.

A 4-week schedule

Week 1
Arrays + Hashing

10-12 problems split across both topics, all easy-to-medium. Goal: comfortable, not fast yet.

Week 2
Two pointers + Stacks

8-10 problems. Start timing yourself loosely — aim to at least state an approach within 5 minutes.

Week 3
BFS / DFS

8-10 problems on graphs and trees. This topic takes longer to feel natural — budget extra review time here.

Week 4
Basic DP + full mixed review

6-8 DP problems, then spend the rest of the week doing mixed, untimed-then-timed problems across all six topics, explaining your approach out loud every single time.

Practise the whole interview

DSA is one part. Practise the rest too.

QUESTIONS? WE'VE GOT ANSWERS

Common questions

DSA prep without the overwhelm

Is six topics really enough to prepare for fresher interviews?
For most Indian intern and SDE-1 rounds, yes — these six topics cover the large majority of what actually gets asked at that level. Advanced topics (segment trees, advanced DP, complex graph algorithms) show up far less often for freshers and are a poor use of limited prep time relative to their frequency.
Should I memorise solutions to common problems?
No — memorising a specific solution falls apart the moment the interviewer changes one detail of the problem, which they often do deliberately. Practise the patterns and the reasoning process instead, so you can derive a solution to a problem you haven't seen before.
How many total problems should I solve?
Roughly 40-50 well-chosen problems across the six topics, done properly (explained out loud, not just submitted), will serve a fresher far better than 300 done passively. Depth of understanding on fewer problems beats breadth with no retention.
What if I freeze up and can't think of the optimal approach in the interview?
State the brute force clearly and start coding it while you think — a working brute-force solution, explained well, is far better than silence or an unfinished optimal attempt. Most interviewers give partial credit for a correct, well-reasoned suboptimal solution.
Should I practise on a whiteboard or just in an editor?
Practise explaining out loud regardless of the medium — that's the actual interview skill, and it's easy to neglect when practising silently on a laptop. Record yourself talking through a few problems if you can; it's uncomfortable at first and very effective.
Do QA, support or analyst roles need this level of DSA prep?
Generally less — DSA-heavy rounds are most common for development-focused roles (SDE, backend). Roles like QA, support, data analyst and business analyst tend to weight domain skills and SQL more heavily than deep algorithmic problem-solving; see the role map for what each role actually screens for.
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