Data Structures and Algorithms Interview Course

A self-paced DSA problem-solving and interview preparation course for students and professionals who want to master data structures and algorithms to crack the coding interview. We recommend you follow modules in a guided order. Enjoy algorithms!

What will you learn?

  • Problem Solving Techniques

  • Designing Efficient Solutions

  • Writing Correct Code

  • Analysis and Code Optimization

enjoyalgorithms dsa course

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DSA Course Modules

(1) DSA Interview Guidance

1.

Why DSA Important?

2.

DSA Learning Challenges

3.

Algorithmic Thinking

4.

DSA Interview Guide

5.

Interview Learning Plan

6.

DSA Problem Solving Techniques

7.

Competitive Coding Guide

8.

DSA Problem Solving Steps

9.

Tips for Problem Solving

(2) Algorithm Fundamentals

1.

Algorithm Introduction

2.

Data Structure Introduction

3.

Time Complexity Analysis

4.

Fundamentals of Iteration

5.

Analysis of Loop and Iteration

6.

Fundamentals of Recursion

7.

Analysis of Recursion

8.

Recursion vs. Iteration

9.

Divide and Conquer

(3) Problem Solving Using Iteration

1.

Buildings Facing Sun

2.

Leaders in an Array

3.

Valid Mountain Array

4.

Roman to Integer

5.

Find Equilibrium Index

6.

Find Product Except Self

7.

Rotate Matrix by 90 Degrees

8.

Spiral Traversal of Matrix

9.

Maximum and Minimum in Array

(4) Problem Solving Using Recursion

1.

Binary Search Algorithm

2.

Fixed Point in Array

3.

Maximum in Bitonic Array

4.

Find First and Last Index

5.

Min in Rotated Sorted Array

6.

Search in a Sorted Matrix

7.

Median of Sorted Arrays

8.

GCD of Two Numbers

9.

Find Square Root

(5) Sorting Algorithms

1.

Why do we need Sorting?

2.

Bubble, Selection, Insertion Sort

3.

Merge Sort Algorithm

4.

Quick Sort Algorithm

5.

Lower Bound of Sorting

6.

Counting Sort Algorithm

7.

Sorting Algorithms Comparison

8.

Sort Array of 0s, 1s, and 2s

9.

Sort Array in a Waveform

(6) Problem Solving Using Two Pointers and Sliding Window

1.

Move Zeroes to End

2.

Remove Duplicates Sorted Array

3.

Container with Most Water

4.

Trapping Rainwater Problem

5.

Longest Unique Substring

6.

Distinct Elements in Window

7.

Max Continuous Series of 1s

8.

Max Consecutive Ones

9.

N-Repeated Element

(7) Problem Solving Using Hashing

1.

What is Hashing?

2.

Popular Hash Functions in DSA

3.

Check Equal Arrays

4.

Most Frequent Element

5.

Largest Subarray with 0 Sum

6.

Longest Consecutive Sequence

7.

Valid Anagram

8.

Sort Characters by Frequency

9.

First Missing Positive

(8) Additional Coding Problems

1.

FizzBuzz Problem

2.

Find Row with Max Ones

3.

Check Pair Sum in Array

4.

Triplets with Zero Sum

5.

Intersection of Two Arrays

6.

Check Subset Arrays

7.

Maximum Difference in Array

8.

Maximum Index Difference

9.

Majority Element in Array

(9) Array and Linked List

1.

Array in Data Structure

2.

Dynamic Array Data Structure

3.

Linked List (coming soon)

4.

Middle Element in Linked List

5.

Reverse a Linked List

6.

Remove Nth Node from List End

7.

Intersection of Two Sorted Lists

8.

Swap List Nodes in Pairs

9.

Detect Loop in a Linked List

(10) Stack and Queue

1.

Introduction to Stack

2.

Queue (coming soon)

3.

Sort Stack Using Stack

4.

Next Greater Element

5.

Implement Queue Using Stacks

6.

Implement Stack Using Queues

7.

Largest Rectangle (coming soon)

8.

Min Stack (coming soon)

(11) Binary Tree

1.

Introduction to Binary Tree

2.

Recursive Binary Tree Traversal

3.

Iterative Binary Tree Traversal

4.

Level Order Traversal

5.

Height of a Binary Tree

6.

Min Depth of a Binary Tree

7.

Merge Two Binary Trees

8.

Left View of Binary Tree

(12) BST and Heap

2.

Binary Search Tree Introduction

2.

Validate Binary Search Tree

3.

Min Absolute Difference in BST

4.

Kth Largest Element in BST

5.

What is Heap Data Structure?

6.

Heap Operations (coming soon)

7.

Heap Sort (coming soon)

8.

Kth Smallest Element in Array

(13) Advanced Data Structures

1.

AVL Tree Data Structure

2.

Introduction to Trie

3.

Fenwick Tree Data Structure

4.

Segment Trees Part 1

5.

Segment Trees Part 2

6.

Design LRU Cache

7.

Design LFU Cache

8.

Design Bloom Filter

9.

N-ary Tree Data Structure

(14) Dynamic Programming

1.

What is Dynamic Programming?

2.

DP Top-down vs Bottom-up

3.

Divide and Conquer vs DP

4.

Type of DP Problems

5.

Climbing Stairs Problem

6.

Minimum Coin Change

7.

Maximum Subarray Sum

8.

Longest Common Subsequence

9.

Minimum Number of Jumps

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