Learn Data Structures and Algorithms

A text-based problem solving course for students and professionals who want to master problem solving for their next coding interview.

What will you learn?

  • Problem-solving approaches

  • Designing efficient solutions

  • Writing correct pseudocode

  • Code analysis techniques

Module 1: Coding Interview Guidance

1.

Algorithmic thinking

2.

Why learn DSA?

3.

DSA learning challenges

4.

DSA interview guide

5.

Interview learning plan

6.

Popular approaches in DSA

7.

Competitive coding guide

8.

DSA problem-solving steps

Module 2: Algorithm Fundamentals

1.

What is algorithms?

2.

What is data structures?

3.

Time complexity analysis

4.

How iteration works?

5.

Analysis of loop

6.

How recursion works?

7.

Analysis of recursion

8.

Iteration vs. Recursion

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.

Product except self

7.

Rotate matrix 90 degree

8.

Print spiral matrix

9.

Find min-max in array

Module 4: Recursion and Binary Search

1.

Divide and conquer

2.

Binary search algorithm

3.

Incr and decr array max

4.

First and last positions

5.

Rotated and sorted array min

6.

Search in a sorted matrix

7.

Median of sorted arrays

8.

GCD of two numbers

9.

Find square root

Module 5: Sorting Algorithms

1.

Why learn sorting?

2.

Introcution to sorting

3.

Merge sort algorithm

4.

Quicksort algorithm

5.

Sorting lower bound

6.

Counting sort algorithm

7.

Sorting comparison

8.

Sort 0s, 1s, and 2s

9.

Sort in a waveform

Module 6: Two Pointers and Sliding Window

1.

Move zeroes

2.

Remove duplicates

3.

Most water container

4.

Trapping rainwater

5.

Longest substring

6.

Count distinct elements

7.

Max series of 1s

8.

Max consecutive 1's

9.

N repeated element

Module 7: Hashing and Hash Table

1.

Hashing and hash table

2.

Hash functions

3.

Check equal arrays

4.

Most frequent element

5.

0-sum largest subarray

6.

Longest consecutive sequence

7.

Valid anagram

8.

Sort characters by frequency

9.

First missing positive

Module 8: Additional Problems

1.

Fizz buzz problem

2.

Row with max 1's

3.

Check pair-sum

4.

Triplet with zero-sum

5.

Intersection of arrays

6.

Check subset arrays

7.

Max difference in an array

8.

Maximum index difference

9.

Majority element

Module 9: Array and Linked List

1.

Array data structure

2.

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 linked list loop

Module 10: Stack and Queue

1.

Introduction to stack

2.

Introduction to queue

3.

Sort stack using stack

4.

Next greater element

5.

Queue using stacks

6.

Stack using queues

7.

Largest rectangle histogram

8.

Check balanced parentheses

Module 11: Binary Tree

1.

Introduction to binary tree

2.

Recursive tree traversals

3.

Iterative tree traversals

4.

Level order traversal

5.

Height of a binary tree

6.

Min depth of a binary tree

7.

Merge binary trees

8.

Binary tree left view

Module 12: BST and Heap

1.

Introduction to BST

2.

Validate binary search tree

3.

Min absolute difference BST

4.

Kth largest element in BST

5.

Introduction to heap

6.

Heap operations

7.

Heap sort algorithm

8.

kth smallest element

Module 13: Advanced Data Structures

1.

AVL tree data structure

2.

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 DP

2.

Top-down vs Bottom-up

3.

DP vs Divide and conquer

4.

Climbing stairs problem

5.

Minimum coin change

6.

Maximum subarray sum

7.

Longest common subsequence

8.

Minimum jumps to reach end

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