Crack Python Coding Interview Pattern: Sliding Window

Part of Series focused on Sliding Window Pattern Problems asked on all Top Tech Coding Interviews

What you'll learn
Solve Easy to Hard Difficulty problems using different data structures and algorithms
Breaking down the coding interview problems in a step by step, systematic manner and provided explanation, different approaches, pseudo code and python code
How to solve all possible types of problems asked by major tech companies that can be solved using Sliding window logic
Create logic building capability to solve coding interview problems efficiently
Requirements
Basic Knowledge of fundamental data structures and algorithms is preferred
Basic Knowledge of python is preferred
If you want to code yourself, you should be familiar with leetcode and or jupyter notebook or any python ide
Description
It's usually difficult to start preparing for coding interviews immediately with limited knowledge of Data Structures and Algorithms. Through grinding on leetcode for FAANG interviews, candidates have started decoding the patterns behind the questions which instantaneously directs them to apply the most efficient logic interviewer is testing us on. Understanding the interview questions based on the patterns and practicing problems having the same patterns helps prepare for interviews faster, with less effort, more confidence, with less chance of forgetting and/or getting confused during the interviews. Interviewers usually test us on multiple patterns of coding interviews. This course covers one type of pattern where we discuss most types of problems that can be solved using sliding window. It’s a very common pattern asked in interview questions. The plan is to create a series of such courses which will cover all the patterns asked in the interview. Completing this course will strong foundation for sliding window. I have tried to make this course brief and have divided the course to 4 hours of video lectures and 4 hours of self-practice assignments, since there are quite a few patterns and candidate may not want to dedicate all time to learning just one pattern.

Overview

Section 1: Introduction

Lecture 1 Brute Force Approach

Section 2: What is Sliding window?

Lecture 2 What is sliding window?

Lecture 3 Find Maximum Sum

Lecture 4 Smallest Subarray

Section 3: String Problems

Lecture 5 String Section

Lecture 6 Longest Possible Substring

Lecture 7 Challenge Problem : Fruit Problem

Lecture 8 Solution : Fruit Problem

Lecture 9 Find Unique Characters

Lecture 10 Find Permutations

Lecture 11 Challenge : Find Anagrams in String

Lecture 12 Solution : Anagrams in String

Lecture 13 Minimum Window Substring

Lecture 14 Concatenation of All Words

Section 4: Solve Together

Lecture 15 Solve Together Section

Lecture 16 Best Time to Buy and Sell Stock

Lecture 17 Binary Subarrays Sum

Lecture 18 Subarrays with K different integers

Lecture 19 Max Consecutive Ones

Lecture 20 Min Swaps to Group All 1s Togeher

Lecture 21 Diet Plan Performance

Lecture 22 Get Equal Substrings Within Budget

Lecture 23 Replace the Substring for Balanced

Lecture 24 Count Number of Nice Subarrays

Lecture 25 Number of Substrings Containing all Three Characters

Getting ready for your software engineering coding interview? This is the place for you.,This Sliding Window Series is one part of Series of Solving Coding Interview Questions. This covers all sliding window and discusses some alternative approaches,Python knowledge is not mandatory, Course discusses logic to solve, pseudo code and python code, students can try coding in any language of their choice while referring to this course,Want to get better at coding interviews?,Strengthen your competitive programming muscles