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tech-interview-handbook/contents/best-practice-questions.md

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id title sidebar_label description keywords
best-practice-questions Best practice questions 🔥 Best practice questions The best practice questions to prepare for algorithmic coding interviews by the author of Blind 75 spread across a 5-week schedule
algorithm
coding
interview
questions
leetcode
blind 75

import AlgorithmCourses from './_courses/AlgorithmCourses.md'

<head> </head>

Hey there, the author of Blind 75 here 👋!

Practicing is the best way to prepare for coding interviews. LeetCode has over a thousand questions. Which should you practice? Hence years ago, I curated a list of the most important 75 questions on LeetCode. Many other LeetCode questions are a mash of the techniques from these individual questions. I used this list in my last job hunt to only do the important questions.

I shared this list on Blind by extracting the questions from my freeCodeCamp article to save peoples' time when revising and someone reposted this list on the LeetCode forum. It somehow blew up and became super famous in the coding interview scene, people even gave it a name - Blind 75. The Blind 75 questions as a LeetCode list can be found here.

Years later, I further distilled the list down into only 50 questions and spread them across a 5-week schedule. Here is the suggested schedule for revising and practicing algorithm questions on LeetCode. Sign up for an account if you don't already have one, it's critical to your success in interviewing!

When practicing, you are advised to treat it like a real coding interview and check through thoroughly before submitting. Consider even manually coming up with some test cases and running through them to verify correctness!

I've created a LeetCode list for the following questions (except the Premium ones). Feel free to use it to track your practice progress.

:::tip Expert tip

If you're running low on time, AlgoMonster aims to help you ace the technical interview in the shortest time possible. By Google engineers, AlgoMonster uses a data-driven approach to teach you most useful key question patterns and has contents to help you quickly revise basic data structures and algorithms. Learn and understand patterns, not memorize answers!

:::

Week 1 - Sequences

In week 1, we will warm up by doing a mix of easy and medium questions on arrays and strings. Arrays and strings are the most common types of questions to be found in interviews; gaining familiarity with them will help in building strong fundamentals to better handle tougher questions.

Optional

Week 2 - Data structures

The focus of week 2 is on linked lists, strings and matrix-based questions. The goal is to learn the common routines dealing with linked lists, traversing matrices and sequence analysis (arrays/strings) techniques such as sliding window, linked list traversal and matrix traversal.

Week 3 - Non-linear data structures

The focus of week 3 is on non-linear data structures like trees, graphs and heaps. You should be familiar with the various tree traversal (in-order, pre-order, post-order) algorithms and graph traversal algorithms such as breadth-first search and depth-first search. In my experience, using more advanced graph algorithms (Dijkstra's and Floyd-Warshall) is quite rare and usually not necessary.

Optional

Week 4 - More data structures

Week 4 builds up on knowledge from previous weeks but questions are of increased difficulty. Expect to see such level of questions during interviews. You get more practice on more advanced data structures such as (but not exclusively limited to) heaps and tries which are less common but are still asked.

Optional

Week 5 - Dynamic programming

Week 5 focuses on Dynamic Programming (DP) questions. Personally as an interviewer, I'm not a fan of DP questions as they are not really applicable to practical scenarios and frankly if I were made to do the tough DP questions during my interviews I'd not have gotten the job. However, companies like Google still ask DP questions and if joining Google is your dream, DP is unavoidable.

DP questions can be hard to master and the best way to get better at them is... you guessed it - practice! Be familiar with the concepts of memoization and backtracking.

Practically speaking the return of investment (ROI) on studying and practicing for DP questions is very low. Hence DP questions are less important/optional and you should only do them if you have time to spare and you're very keen to have all bases covered (and interviewing with Google).

Dynamic programming course

Quality courses

If you want more structured algorithms practice, I recommend the following courses: