Learn Data Structures and Algorithms

A text-based 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 effcient solutions

  • Writing correct pseudocode

  • Analysis and code optimization

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Module 1: Coding Interview Guidance

1.

Develop algorithmic thinking

2.

Why DSA important?

3.

Challenges in learning DSA

4.

Coding interview guide

5.

Coding interview learning plan

6.

Problem solving approaches in DSA

7.

Competitive coding guide

8.

Steps of solving DSA questions

Module 2: Algorithm Fundamentals

1.

What is algorithm?

2.

What is data structure?

3.

Time complexity analysis

4.

Iteration in programming

5.

Analysis of loop in irogramming

6.

Recursion in programming

7.

Analysis of recursive functions

8.

Recursion and iteration comparison

Module 3: Problem Solving Using Loop

1.

Buildings facing sun

2.

Leaders in an array

3.

Valid mountain array

4.

Convert 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

Module 4: Recursion and Binary Search

1.

Divide and conquer

2.

Binary search algorithm

3.

Find maximum in bitonic array

4.

Find first and last index

5.

Min in rotated and sorted array

6.

Search in a sorted matrix

7.

Median of sorted arrays

8.

Find GCD of two numbers

9.

Find square root

Module 5: Sorting Algorithms

1.

Why do we need sorting?

2.

Bubble, selection and 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 0s, 1s, and 2s

9.

Sort array in a waveform

Module 6: Two Pointers and Sliding Window

1.

Move zeroes to end

2.

Remove duplicates from array

3.

Container with most water

4.

Trapping rainwater problem

5.

Longest Unique Substring

6.

Count distinct elements in window

7.

Max Continuous Series of 1s

8.

Max consecutive ones

9.

Find N-repeated element

Module 7: Hashing and Hash Table

1.

Hashing in data structure

2.

Hash function in data structure

3.

Check arrays are equal or not

4.

Find most frequent element

5.

Largest Subarray With 0 Sum

6.

Longest consecutive sequence

7.

Check strings are anagram or not

8.

Sort characters by frequency

9.

First missing positive

Module 8: Additional Problems

1.

Fizz buzz problem

2.

Find row with max ones

3.

Check pair sum in array

4.

Find triplets with zero sum

5.

Intersection of unsorted arrays

6.

Check arrays are subset or not

7.

Find max difference in array

8.

Find maximum index difference

9.

Find majority element

Module 9: Array and Linked List

1.

Array in data structure

2.

Introduction to dynamic array

3.

Introduction to linked list

4.

Middle element in linked list

5.

Reverse linked list

6.

Remove Nth node from end

7.

Intersection of linked lists

8.

Swap nodes in pairs

9.

Detect loop in linked list

Module 10: Stack and Queue

1.

Introduction to stack

2.

Introduction to queue

3.

Sort stack using stack

4.

Next greater element

5.

Implement queue using stacks

6.

Implement stack using queues

7.

Largest rectangle histogram

8.

Check balanced parentheses

Module 11: Binary Tree

1.

Introduction to binary tree

2.

Preorder inorder postorder traversal

3.

Binary tree traversal using stack

4.

Level order traversal

5.

Find height of a binary tree

6.

Find min depth of a binary tree

7.

Merge two binary trees

8.

Find left view of binary tree

Module 12: BST and Heap

2.

Introduction to binary search tree

2.

Validate binary search tree

3.

Minimum absolute difference in BST

4.

Find Kth largest element in BST

5.

Introduction to heap data structure

6.

Heap operations and priority queue

7.

Heap sort algorithm

8.

Find Kth smallest element

Module 13: Advanced Data Structures

1.

AVL tree data structure

2.

Introduction to trie data structure

3.

Fenwick tree data structure

4.

Segment trees part 1

5.

Segment trees part 2

6.

LRU cache implementation

7.

LFU cache implementation

8.

Bloom filter implementation

Module 14: Dynamic Programming

1.

Introduction to dynamic programming

2.

Top-down vs bottom-up approach

3.

DP vs divide and conquer

4.

Climbing stairs problem

5.

Minimum coin change problem

6.

Max subarray sum (kadane’s algorithm)

7.

Longest common subsequence

8.

Minimum jumps to reach end

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