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All capabilities · Programming foundations

Solve coding interview problems

Arrays, hashing, trees, graphs, DP at the level asked in Indian product-company screens.

~60 focused hoursintermediate
Explore 3 tools for this project
Market relevance

Which roles ask for this — and how often

Share of job postings in India, per role, that name this capability.

No job posting names this. Interview rounds ask for it anyway — which is why it stays on the map, and why there is no share to show.
What employers mean

You should be able to…

  1. Solve an array/hashmap problem in under 20 minutes with correct edge-case handling
  2. Traverse and modify trees and graphs (BFS/DFS, topological sort)
  3. Write a dynamic programming solution and explain the recurrence out loud
  4. Analyze time and space complexity of your own solution correctly
  5. Debug a failing solution against hidden test cases in a live coding round
  6. Explain trade-offs between two approaches (e.g. hashmap vs two-pointer) before coding
  7. Handle a follow-up that changes constraints (e.g. 'now the input doesn't fit in memory')

Needs first: Write production-quality Python for AI work

Learn — free, link-checked

The few resources that matter

Watch · beginner · 360 min · youtube.com

Data Structures and Algorithms in Python - Full Course for Beginners

Builds every core data structure from scratch in Python, cementing both DSA concepts and idiomatic Python at once. — freeCodeCamp.org
Read · intermediate · 30 min · techinterviewhandbook.org

Algorithms Study Cheatsheet

Pattern-based cheatsheet (sliding window, two pointers, backtracking) that turns hundreds of practice problems into a handful of recognizable techniques. — Tech Interview Handbook (Yangshun Tay)
Use · intermediate · 60 min · neetcode.io

NeetCode Roadmap

A curated, ordered problem list (arrays to graphs to DP) that mirrors what Indian product-company screens actually ask, with free video solutions per problem. — NeetCode
Tools for practice

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Go to the practice brief

3 tools to explore

Practices & references

  • Arrays and hash maps
  • Trees and graphs
  • Dynamic programming

Selected for practice by RoleGPS. No paid placements or affiliate links.
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Practice

40-problem DSA interview log with pattern notes

Work at least 40 problems across arrays and hashing, trees, graphs, dynamic programming and intervals from the free NeetCode roadmap over two to three weeks. Keep a public log repo where every solution carries its time and space complexity and a line on the pattern it belongs to. Anything you could not solve in 25 minutes goes back on the list and gets re-attempted cold a week later.

Start from

NeetCode 150 roadmap — interview problems grouped by pattern, free to work through in any language

Milestones
  1. Arrays, hashing and two pointers — 12 problems with complexity notes · ~13h
  2. Trees and graphs — 14 problems, writing the traversal template once and reusing it · ~16h
  3. Dynamic programming and intervals — 14 problems · ~16h
  4. Re-solve the five you timed out on, cold, a week later · ~5h
  5. Write the pattern cheat sheet and the weakness README · ~2.5h
Done when
  • At least 40 problems solved and committed, spanning all 5 core patterns (array, hashmap, tree, graph, DP)
  • Each solution file has a comment stating time/space complexity
  • At least 5 problems have a documented second attempt after initially failing/timing out
  • A README summarizing which patterns you're weakest on and your practice plan for them
Prove it

Evidence a recruiter can check

  • 40+ solution files, each headed with its time and space complexity and the pattern it belongs to
  • Five problems with two dated attempts a week apart, and a note on what unlocked the second one
  • A pattern cheat sheet in your own words — the tell that picks each pattern and the template it uses
  • A README naming the two patterns you are weakest on, with the drill list you built for them
Signal it

Worked 40+ NeetCode interview problems across arrays, trees, graphs and DP with complexity analysis on every solution — and re-solved every timed-out problem cold a week later.

Interview

Questions you'll get asked

  1. Given an array of transaction amounts, find two that sum to a target UPI limit.
  2. Detect a cycle in a directed graph of microservice dependencies.
  3. Find the longest increasing subsequence in a list of stock prices.
  4. How would you find the k most frequent search queries from a large log file?
  5. Reverse a linked list iteratively and then recursively.
  6. Given a matrix of city grid distances, find the shortest path (Dijkstra/BFS).
  7. What's the time complexity of your solution, and can you do better?
  8. How would this solution change if the input were too large to fit in memory?
See which roles to aim at