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The Complete Data Structures and Algorithms Course in Python

Data Structures and Algorithms from Zero to Hero and Crack Top Companies 100+ Interview questions (Python Coding)

4.52 (979 reviews)

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40.5 hours

Content

Jun 2021

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What you will learn

Learn, implement, and use different Data Structures

Learn, implement and use different Algorithms

Become a better developer by mastering computer science fundamentals

Learn everything you need to ace difficult coding interviews

Cracking the Coding Interview with 100+ questions with explanations

Time and Space Complexity of Data Structures and Algorithms

Recursion

Big O


Description

Welcome to the Complete Data Structures and Algorithms in Python Bootcamp, the most modern, and the most complete Data Structures and Algorithms in Python course on the internet.

At 40+ hours, this is the most comprehensive course online to help you ace your coding interviews and learn about Data Structures and Algorithms in Python. You will see 100+ Interview Questions done at the top technology companies such as Apple,Amazon, Google and Microsoft and how to face Interviews with comprehensive visual explanatory video materials which will bring you closer towards landing the tech job of your dreams!

Learning Python is one of the fastest ways to improve your career prospects as it is one of the most in demand tech skills! This course will help you in better understanding every detail of Data Structures and how algorithms are implemented in high level programming language.

We'll take you step-by-step through engaging video tutorials and teach you everything you need to succeed as a professional programmer.

After finishing this course, you will be able to:

Learn basic algorithmic techniques such as greedy algorithms, binary search, sorting and dynamic programming to solve programming challenges.

Learn the strengths and weaknesses of a variety of data structures, so you can choose the best data structure for your data and applications

Learn many of the algorithms commonly used to sort data, so your applications will perform efficiently when sorting large datasets

Learn how to apply graph and string algorithms to solve real-world challenges: finding shortest paths on huge maps and assembling genomes from millions of pieces.


Why this course is so special and different from any other resource available online?


This course will take you from very beginning to a very complex and advanced topics in understanding Data Structures and Algorithms!

You will get video lectures explaining concepts clearly with comprehensive visual explanations throughout the course.

You will also see Interview Questions done at the top technology companies such as Apple,Amazon, Google and Microsoft.

I cover everything you need to know about technical interview process!


So whether you are interested in learning the top programming language in the world in-depth

And interested in learning the fundamental Algorithms, Data Structures and performance analysis that make up the core foundational skillset of every accomplished programmer/designer or software architect and is excited to ace your next technical interview this is the course for you!


And this is what you get by signing up today:


Lifetime access to 40+ hours of HD quality videos. No monthly subscription. Learn at your own pace, whenever you want

Friendly and fast support in the course Q&A whenever you have questions or get stuck

FULL money back guarantee for 30 days!


Who is this course for?

Self-taught programmers who have a basic knowledge in Python and want to be professional in Data Structures and Algorithms and begin interviewing in tech positions!

As well as students currently studying computer science and want supplementary material on Data Structures and Algorithms and interview preparation for after graduation!

As well as professional programmers who need practice for upcoming coding interviews.

And finally anybody interested in learning more about data structures and algorithms or the technical interview process!

This course is designed to help you to achieve your career goals. Whether you are looking to get more into Data Structures and Algorithms , increase your earning potential or just want a job with more freedom, this is the right course for you!

The topics that are covered in this course.

Section 1 - Introduction

  • What are Data Structures?

  • What is an algorithm?

  • Why are Data Structures and Algorithms important?

  • Types of Data Structures

  • Types of Algorithms

Section 2 - Recursion

  • What is Recursion?

  • Why do we need recursion?

  • How Recursion works?

  • Recursive vs Iterative Solutions

  • When to use/avoid Recursion?

  • How to write Recursion in 3 steps?

  • How to find Fibonacci numbers using Recursion?

Section 3 - Cracking Recursion Interview Questions

  • Question 1 - Sum of Digits

  • Question 2 - Power

  • Question 3 - Greatest Common Divisor

  • Question 4 - Decimal To Binary

Section 4 - Bonus CHALLENGING Recursion Problems (Exercises)

  • power

  • factorial

  • productofArray

  • recursiveRange

  • fib

  • reverse

  • isPalindrome

  • someRecursive

  • flatten

  • captalizeFirst

  • nestedEvenSum

  • capitalizeWords

  • stringifyNumbers

  • collectStrings

Section 5 - Big O Notation

  • Analogy and Time Complexity

  • Big O, Big Theta and Big Omega

  • Time complexity examples

  • Space Complexity

  • Drop the Constants and the non dominant terms

  • Add vs Multiply

  • How to measure the codes using Big O?

  • How to find time complexity for Recursive calls?

  • How to measure Recursive Algorithms that make multiple calls?

Section 6 - Top 10 Big O Interview Questions (Amazon, Facebook, Apple and Microsoft)

  • Product and Sum

  • Print Pairs

  • Print Unordered Pairs

  • Print Unordered Pairs 2 Arrays

  • Print Unordered Pairs 2 Arrays 100000 Units

  • Reverse

  • O(N)  Equivalents

  • Factorial Complexity

  • Fibonacci Complexity

  • Powers of 2

Section 7 - Arrays

  • What is an Array?

  • Types of Array

  • Arrays in Memory

  • Create an Array

  • Insertion Operation

  • Traversal Operation

  • Accessing an element of Array

  • Searching for an element in Array

  • Deleting an element from Array

  • Time and Space complexity of One Dimensional Array

  • One Dimensional Array Practice

  • Create Two Dimensional Array

  • Insertion - Two Dimensional Array

  • Accessing an element of Two Dimensional Array

  • Traversal - Two Dimensional Array

  • Searching for an element in Two Dimensional Array

  • Deletion - Two Dimensional Array

  • Time and Space complexity of Two Dimensional Array

  • When to use/avoid array

Section 8 - Python Lists

  • What is a List? How to create it?

  • Accessing/Traversing a list

  • Update/Insert a List

  • Slice/ from a List

  • Searching for an element in a List

  • List Operations/Functions

  • Lists and strings

  • Common List pitfalls and ways to avoid them

  • Lists vs Arrays

  • Time and Space Complexity of List

  • List Interview Questions

Section 9 - Cracking Array/List Interview Questions (Amazon, Facebook, Apple and Microsoft)

  • Question 1 - Missing Number

  • Question 2 - Pairs

  • Question 3 - Finding a number in an Array

  • Question 4 - Max product of two int

  • Question 5 - Is Unique

  • Question 6 - Permutation

  • Question 7 - Rotate Matrix

Section 10 - CHALLENGING Array/List Problems (Exercises)

  • Middle Function

  • 2D Lists

  • Best Score

  • Missing Number

  • Duplicate Number

  • Pairs

Section 11 - Dictionaries

  • What is a Dictionary?

  • Create a Dictionary

  • Dictionaries in memory

  • Insert /Update an element in a Dictionary

  • Traverse through a Dictionary

  • Search for an element in a Dictionary

  • Delete / Remove an element from a Dictionary

  • Dictionary Methods

  • Dictionary operations/ built in functions

  • Dictionary vs List

  • Time and Space Complexity of a Dictionary

  • Dictionary Interview Questions

Section 12 - Tuples

  • What is a Tuple? How to create it?

  • Tuples in Memory / Accessing an element of Tuple

  • Traversing a Tuple

  • Search for an element in Tuple

  • Tuple Operations/Functions

  • Tuple vs List

  • Time and Space complexity of Tuples

  • Tuple Questions

Section 13 - Linked List

  • What is a Linked List?

  • Linked List vs Arrays

  • Types of Linked List

  • Linked List in the Memory

  • Creation of Singly Linked List

  • Insertion in Singly Linked List in Memory

  • Insertion in Singly Linked List Algorithm

  • Insertion Method in Singly Linked List

  • Traversal of Singly Linked List

  • Search for a value in Single Linked List

  • Deletion of node from Singly Linked List

  • Deletion Method in Singly Linked List

  • Deletion of entire Singly Linked List

  • Time and Space Complexity of Singly Linked List

Section 14 - Circular Singly Linked List

  • Creation of Circular Singly Linked List

  • Insertion in Circular Singly Linked List

  • Insertion Algorithm in Circular Singly Linked List

  • Insertion method in Circular Singly Linked List

  • Traversal of Circular Singly Linked List

  • Searching a node in Circular Singly Linked List

  • Deletion of a node from Circular Singly Linked List

  • Deletion Algorithm in Circular Singly Linked List

  • Method in Circular Singly Linked List

  • Deletion of entire Circular Singly Linked List

  • Time and Space Complexity of Circular Singly Linked List

Section 15 - Doubly Linked List

  • Creation of Doubly Linked List

  • Insertion in Doubly Linked List

  • Insertion Algorithm in Doubly Linked List

  • Insertion Method in Doubly Linked List

  • Traversal of Doubly Linked List

  • Reverse Traversal of Doubly Linked List

  • Searching for a node in Doubly Linked List

  • Deletion of a node in Doubly Linked List

  • Deletion Algorithm in Doubly Linked List

  • Deletion Method in Doubly Linked List

  • Deletion of entire Doubly Linked List

  • Time and Space Complexity of Doubly Linked List

Section 16 - Circular Doubly Linked List

  • Creation of Circular Doubly Linked List

  • Insertion in Circular Doubly Linked List

  • Insertion Algorithm in Circular Doubly Linked List

  • Insertion Method in Circular Doubly Linked List

  • Traversal of Circular Doubly Linked List

  • Reverse Traversal of Circular Doubly Linked List

  • Search for a node in Circular Doubly Linked List

  • Delete a node from Circular Doubly Linked List

  • Deletion Algorithm in Circular Doubly Linked List

  • Deletion Method in Circular Doubly Linked List

  • Entire Circular Doubly Linked List

  • Time and Space Complexity of Circular Doubly Linked List

  • Time Complexity of Linked List vs Arrays

Section 17 - Cracking Linked List Interview Questions (Amazon, Facebook, Apple and Microsoft)

  • Linked List Class

  • Question 1 - Remove Dups

  • Question 2 - Return Kth to Last

  • Question 3 - Partition

  • Question 4 - Sum Linked Lists

  • Question 5 - Intersection

Section 18 - Stack

  • What is a Stack?

  • Stack Operations

  • Create Stack using List without size limit

  • Operations on Stack using List (push, pop, peek, isEmpty, )

  • Create Stack with limit (pop, push, peek, isFull, isEmpty, )

  • Create Stack using Linked List

  • Operation on Stack using Linked List (pop, push, peek, isEmpty, )

  • Time and Space Complexity of Stack using Linked List

  • When to use/avoid Stack

  • Stack Quiz

Section 19 - Queue

  • What is Queue?

  • Queue using Python List - no size limit

  • Queue using Python List - no size limit , operations (enqueue, dequeue, peek)

  • Circular Queue - Python List

  • Circular Queue - Python List, Operations (enqueue, dequeue, peek, )

  • Queue - Linked List

  • Queue - Linked List, Operations (Create, Enqueue)

  • Queue - Linked List, Operations (Dequeue(), isEmpty, Peek)

  • Time and Space complexity of Queue using Linked List

  • List vs Linked List Implementation

  • Collections Module

  • Queue Module

  • Multiprocessing module

Section 20 - Cracking Stack and Queue Interview Questions (Amazon,Facebook, Apple, Microsoft)

  • Question 1 - Three in One

  • Question 2 - Stack Minimum

  • Question 3 - Stack of Plates

  • Question 4 - Queue via Stacks

  • Question 5 - Animal Shelter

Section 21 - Tree / Binary Tree

  • What is a Tree?

  • Why Tree?

  • Tree Terminology

  • How to create a basic tree in Python?

  • Binary Tree

  • Types of Binary Tree

  • Binary Tree Representation

  • Create Binary Tree (Linked List)

  • PreOrder Traversal Binary Tree (Linked List)

  • InOrder Traversal Binary Tree (Linked List)

  • PostOrder Traversal Binary Tree (Linked List)

  • LevelOrder Traversal Binary Tree (Linked List)

  • Searching for a node in Binary Tree (Linked List)

  • Inserting a node in Binary Tree (Linked List)

  • Delete a node from Binary Tree (Linked List)

  • Delete entire Binary Tree (Linked List)

  • Create Binary Tree (Python List)

  • Insert a value Binary Tree (Python List)

  • Search for a node in Binary Tree (Python List)

  • PreOrder Traversal Binary Tree (Python List)

  • InOrder Traversal Binary Tree (Python List)

  • PostOrder Traversal Binary Tree (Python List)

  • Level Order Traversal Binary Tree (Python List)

  • Delete a node from Binary Tree (Python List)

  • Entire Binary Tree (Python List)

  • Linked List vs Python List Binary Tree

Section 22 - Binary Search Tree

  • What is a Binary Search Tree? Why do we need it?

  • Create a Binary Search Tree

  • Insert a node to BST

  • Traverse BST

  • Search in BST

  • Delete a node from BST

  • Delete entire BST

  • Time and Space complexity of BST

Section 23 - AVL Tree

  • What is an AVL Tree?

  • Why AVL Tree?

  • Common Operations on AVL Trees

  • Insert a node in AVL (Left Left Condition)

  • Insert a node in AVL (Left Right Condition)

  • Insert a node in AVL (Right Right Condition)

  • Insert a node in AVL (Right Left Condition)

  • Insert a node in AVL (all together)

  • Insert a node in AVL (method)

  • Delete a node from AVL (LL, LR, RR, RL)

  • Delete a node from AVL (all together)

  • Delete a node from AVL (method)

  • Delete entire AVL

  • Time and Space complexity of AVL Tree

Section 24 - Binary Heap

  • What is Binary Heap? Why do we need it?

  • Common operations (Creation, Peek, sizeofheap) on Binary Heap

  • Insert a node in Binary Heap

  • Extract a node from Binary Heap

  • Delete entire Binary Heap

  • Time and space complexity of Binary Heap

Section 25 - Trie

  • What is a Trie? Why do we need it?

  • Common Operations on Trie (Creation)

  • Insert a string in Trie

  • Search for a string in Trie

  • Delete a string from Trie

  • Practical use of Trie

Section 26 - Hashing

  • What is Hashing? Why do we need it?

  • Hashing Terminology

  • Hash Functions

  • Types of Collision Resolution Techniques

  • Hash Table is Full

  • Pros and Cons of Resolution Techniques

  • Practical Use of Hashing

  • Hashing vs Other Data structures

Section 27 - Sort Algorithms

  • What is Sorting?

  • Types of Sorting

  • Sorting Terminologies

  • Bubble Sort

  • Selection Sort

  • Insertion Sort

  • Bucket Sort

  • Merge Sort

  • Quick Sort

  • Heap Sort

  • Comparison of Sorting Algorithms

Section 28 - Searching Algorithms

  • Introduction to Searching Algorithms

  • Linear Search

  • Linear Search in Python

  • Binary Search

  • Binary Search in Python

  • Time Complexity of Binary Search


Section 29 - Graph Algorithms

  • What is a Graph? Why Graph?

  • Graph Terminology

  • Types of Graph

  • Graph Representation

  • Create a graph using Python

  • Graph traversal - BFS

  • BFS Traversal in Python

  • Graph Traversal - DFS

  • DFS Traversal in Python

  • BFS Traversal vs DFS Traversal

  • Topological Sort

  • Topological Sort Algorithm

  • Topological Sort in Python

  • Single Source Shortest Path Problem (SSSPP)

  • BFS for Single Source Shortest Path Problem (SSSPP)

  • BFS for Single Source Shortest Path Problem (SSSPP) in Python

  • Why does BFS not work with weighted Graphs?

  • Why does DFS not work for SSSP?

  • Dijkstra's Algorithm for SSSP

  • Dijkstra's Algorithm in Python

  • Dijkstra Algorithm with negative cycle

  • Bellman Ford Algorithm

  • Bellman Ford Algorithm with negative cycle

  • Why does Bellman Ford run V-1 times?

  • Bellman Ford in Python

  • BFS vs Dijkstra vs Bellman Ford

  • All pairs shortest path problem

  • Dry run for All pair shortest path

  • Floyd Warshall Algorithm

  • Why Floyd Warshall?

  • Floyd Warshall with negative cycle,

  • Floyd Warshall in Python,

  • BFS vs Dijkstra vs Bellman Ford vs Floyd Warshall,

  • Minimum Spanning Tree,

  • Disjoint Set,

  • Disjoint Set in Python,

  • Kruskal Algorithm,

  • Kruskal Algorithm in Python,

  • Prim's Algorithm,

  • Prim's Algorithm in Python,

  • Prim's vs Kruskal

Section 30 - Greedy Algorithms

  • What is Greedy Algorithm?

  • Well known Greedy Algorithms

  • Activity Selection Problem

  • Activity Selection Problem in Python

  • Coin Change Problem

  • Coin Change Problem in Python

  • Fractional Knapsack Problem

  • Fractional Knapsack Problem in Python

Section 31 - Divide and Conquer Algorithms

  • What is a Divide and Conquer Algorithm?

  • Common Divide and Conquer algorithms

  • How to solve Fibonacci series using Divide and Conquer approach?

  • Number Factor

  • Number Factor in Python

  • House Robber

  • House Robber Problem in Python

  • Convert one string to another

  • Convert One String to another in Python

  • Zero One Knapsack problem

  • Zero One Knapsack problem in Python

  • Longest Common Sequence Problem

  • Longest Common Subsequence in Python

  • Longest Palindromic Subsequence Problem

  • Longest Palindromic Subsequence in Python

  • Minimum cost to reach the Last cell problem

  • Minimum Cost to reach the Last Cell in 2D array using Python

  • Number of Ways to reach the Last Cell with given Cost

  • Number of Ways to reach the Last Cell with given Cost in Python

Section 32 - Dynamic Programming

  • What is Dynamic Programming? (Overlapping property)

  • Where does the name of DC come from?

  • Top Down with Memoization

  • Bottom Up with Tabulation

  • Top Down vs Bottom Up

  • Is Merge Sort Dynamic Programming?

  • Number Factor Problem using Dynamic Programming

  • Number Factor : Top Down and Bottom Up

  • House Robber Problem using Dynamic Programming

  • House Robber : Top Down and Bottom Up

  • Convert one string to another using Dynamic Programming

  • Convert String using Bottom Up

  • Zero One Knapsack using Dynamic Programming

  • Zero One Knapsack - Top Down

  • Zero One Knapsack - Bottom Up

Section 33 - CHALLENGING Dynamic Programming Problems

  • Longest repeated Subsequence Length problem

  • Longest Common Subsequence Length problem

  • Longest Common Subsequence  problem

  • Diff Utility

  • Shortest Common Subsequence  problem

  • Length of Longest Palindromic Subsequence

  • Subset Sum Problem

  • Egg Dropping Puzzle

  • Maximum Length Chain of Pairs

Section 34 - A Recipe for Problem Solving

  • Introduction

  • Step 1 - Understand the problem

  • Step 2 - Examples

  • Step 3 - Break it Down

  • Step 4 - Solve or Simplify

  • Step 5 - Look Back and Refactor



Screenshots

The Complete Data Structures and Algorithms Course in Python
The Complete Data Structures and Algorithms Course in Python
The Complete Data Structures and Algorithms Course in Python
The Complete Data Structures and Algorithms Course in Python

Content

Introduction

What are Data Structures?

What is an algorithm?

Why are Data Structures and Algorithms important?

Types of Data Structures

Types of Algorithms

Introduction to DS and Algorithms

Recursion

What is Recursion?

Why do we need recursion?

How Recursion works?

Recursive vs Iterative Solutions

When to use/avoid Recursion?

How to write Recursion in 3 steps?

How to find Fibonacci numbers using Recursion?

Download the Resources

Feedback Time

Cracking Recursion Interview Questions

Question 1

Question 2

Question 3

Question 4

Download the Resources

Feedback Time

Big O Notation

Analogy and Time Complexity

Big O, Big Theta and Big Omega

Time complexity examples

Space Complexity

Drop the Constants and the non dominant terms

Add vs Multiply

How to measure the codes using Big O?

How to find time complexity for Recursive calls?

How to measure Recursive Algorithms that make multiple calls?

Time Complexities

Download the Resources

Feedback Time

Top 10 Big O Interview Questions (Amazon, Facebook, Apple and Microsoft)

Question 1

Question 2

Question 3

Question 4

Question 5

Question 6

Question 7

Question 8

Question 9

Question 10

Download the Resources

Feedback Time

Arrays

What is an Array?

Types of Array

Arrays in Memory

Create an Array

Insertion Operation

Traversal Operation

Accessing an element of Array

Searching for an element in Array

Deleting an element from Array

Time and Space complexity of One Dimensional Array

One Dimensional Array Practice

Create Two Dimensional Array

Insertion - Two Dimensional Array

Accessing an element of Two Dimensional Array

Traversal - Two Dimensional Array

Searching for an element in Two Dimensional Array

Deletion - Two Dimensional Array

Time and Space complexity of Two Dimensional Array

When to use/avoid array

Download the Resources

Feedback Time

Python Lists

What is a List? How to create it?

Accessing/Traversing a list

Update/Insert a List

Slice/Delete from a List

Searching for an element in a List

List Operations/Functions

Lists and strings

Common List pitfalls and ways to avoid them

Lists vs Arrays

Time and Space Complexity of List

List Interview Questions

Download the Resources

Feedback Time

Cracking Array/List Interview Questions (Amazon, Facebook, Apple and Microsoft)

Question 1 - Missing Number

Question 2 - Pairs

Question 3 - Finding a number in an Array

Question 4 - Max product of two int

Question 5 - Is Unique

Question 6 - Permutation

Question 7 - Rotate Matrix

Download the Resources

Feedback Time

Dictionaries

What is a Dictionary?

Create a Dictionary

Dictionaries in memory

Insert /Update an element in a Dictionary

Traverse through a Dictionary

Search for an element in a Dictionary

Delete/ Remove an element from a Dictionary

Dictionary Methods

Dictionary operations/ built in functions

Dictionary vs List

Time and Space Complexity of a Dictionary

Dictionary Interview Questions

Download the Resources

Feedback Time

Tuples

What is a Tuple? How to create it?

Tuples in Memory / Accessing an element of Tuple

Traversing a Tuple

Search for an element in Tuple

Tuple Operations/Functions

Tuple vs List

Time and Space complexity of Tuples

Tuple Questions

Download the Resources

Feedback Time

Linked List

What is a Linked List?

Linked List vs Arrays

Types of Linked List

Linked List in the Memory

Creation of Singly Linked List

Insertion in Singly Linked List in Memory

Insertion in Singly Linked List Algorithm

Insertion Method in Singly Linked List

Traversal of Singly Linked List

Search for a value in Single Linked List

Deletion of node from Singly Linked List

Deletion Method in Singly Linked List

Deletion of entire Singly Linked List

Time and Space Complexity of Singly Linked List

Creation of Circular Singly Linked List

Insertion in Circular Singly Linked List

Insertion Algorithm in Circular Singly Linked List

Insertion method in Circular Singly Linked List

Traversal of Circular Singly Linked List

Searching a node in Circular Singly Linked List

Deletion of a node from Circular Singly Linked List

Deletion Algorithm in Circular Singly Linked List

Delete Method in Circular Singlu Linked List

Deletion of entire Circular Singly Linked List

Time and Space Complexity of Circular Singly Linked List

Creation of Doubly Linked List

Insertion in Doubly Linked List

Insertion Algorithm in Doubly Linked List

Insertion Method in Doubly Linked List

Traversal of Doubly Linked List

Reverse Traversal of Doubly Linked List

Searching for a node in Doubly Linked List

Deletion of a node in Doubly Linked List

Deletion Algorithm in Doubly Linked List

Deletion Method in Doubly Linked List

Deletion of entire Doubly Linked List

Time and Space Complexity of Doubly Linked List

Creation of Circular Doubly Linked List

Insertion in Circular Doubly Linked List

Insertion Algorithm in Circular Doubly Linked List

Insertion Method in Circular Doubly Linked List

Traversal of Circular Doubly Linked List

Reverse Traversal of Circular Doubly Linked List

Search for a node in Circular Doubly Linked List

Delete a node from Circular Doubly Linked List

Deletion Algorithm in Circular Doubly Linked List

Deletion Method in Circular Doubly Linked List

Delete Entire Circular Doubly Linked List

Time and Space Complexity of Circular Doubly Linked List

Time Complexity of Linked List vs Arrays

Download the Resources

Feedback Time

Cracking Linked List Interview Questions (Amazon, Facebook, Apple and Microsoft)

Linked List Class

Question 1 - Remove Dups

Question 2 - Return Kth to Last

Question 3 - Partition

Question 4 - Sum Linked Lists

Question 5 - Intersection

Download the Resources

Feedback Time

Stack

What is a Stack?

Stack Operations

Create Stack using List without size limit

Operations on Stack using List (push, pop, peek, isEmpty, Delete)

Create Stack with limit (pop, push, peek, isFull, isEmpty, delete)

Create Stack using Linked List

Operation on Stack using Linked List (pop, push, peek, isEmpty, delete)

Time and Space Complexity of Stack using Linked List

When to use/avoid Stack

Stack Quiz

Download the Resources

Feedback Time

Queue

What is Queue?

Queue using Python List - no size limit

Queue using Python List - no size limit , operations (enqueue, dequeue, peek)

Circular Queue - Python List

Circular Queue - Python List, Operations (enqueue, dequeue, peek, delete)

Queue - Linked List

Queue - Linked List, Operations (Create, Enqueue)

Queue - Linked List, Operations (Dequeue(), isEmpty, Peek)

Time and Space complexity of Queue using Linked List

List vs Linked List Implementation

Collections Module

Queue Module

Multiprocessing module

Download the Resources

Feedback Time

Cracking Stack and Queue Interview Questions (Amazon,Facebook, Apple, Microsoft)

Question 1 - Three in One

Question 2 - Stack Minimum

Question 3 - Stack of Plates

Question 4 - Queue via Stacks

Question 5 - Animal Shelter

Download Resources

Feedback Time

Tree / Binary Tree

What is a Tree?

Why Tree?

Tree Terminology

How to create basic tree in Python?

Binary Tree

Types of Binary Tree

Binary Tree Representation

Create Binary Tree (Linked List)

PreOrder Traversal Binary Tree (Linked List)

InOrder Traversal Binary Tree (Linked List)

PostOrder Traversal Binary Tree (Linked List)

LevelOrder Traversal Binary Tree (Linked List)

Searching for a node in Binary Tree (Linked List)

Inserting a node in Binary Tree (Linked List)

Delete a node from Binary Tree (Linked List)

Delete entire Binary Tree (Linked List)

Create Binary Tree (Python List)

Insert a value Binary Tree (Python List)

Search for a node in Binary Tree (Python List)

PreOrder Traversal Binary Tree (Python List)

InOrder Traversal Binary Tree (Python List)

PostOrder Traversal Binary Tree (Python List)

Level Order Traversal Binary Tree (Python List)

Delete a node from Binary Tree (Python List)

Delete Entire Binary Tree (Python List)

Linked List vs Python List Binary Tree

Download the Resources

Feedback Time

Binary Search Tree

What is a Binary Search Tree? Why do we need it?

Create a Binary Search Tree

Insert a node to BST

Traverse BST

Search in BST

Delete a node from BST

Delete entire BST

Time and Space complexity of BST

Download the Resources

Feedback Time

AVL Tree

What is an AVL Tree?

Why AVL Tree?

Common Operations on AVL Trees

Insert a node in AVL (Left Left Condition)

Insert a node in AVL (Left Right Condition)

Insert a node in AVL (Right Right Condition)

Insert a node in AVL (Right Left Condition)

Insert a node in AVL (all together)

Insert a node in AVL (method)

Delete a node from AVL (LL, LR, RR, RL)

Delete a node from AVL (all together)

Delete a node from AVL (method)

Delete entire AVL

Time and Space complexity of AVL Tree

Download the Resources

Feeback Time

Binary Heap

What is Binary Heap? Why do we need it?

Common operations (Creation, Peek, sizeofheap) on Binary Heap

Insert a node in Binary Heap

Extract a node from Binary Heap

Delete entire Binary Heap

Time and space complexity of Binary Heap

Download the Resources

Feedback Time

Trie

What is a Trie? Why we need it?

Common Operations on Trie (Creation)

Insert a string in Trie

Search for a string in Trie

Delete a string from Trie

Practical use of Trie

Download the Resources

Feedback Time

Hashing

What is Hashing? Why we need it?

Hashing Terminology

Hash Functions

Types of Collision Resolution Techniques

Hash Table is Full

Pros and Cons of Resolution Techniques

Practical Use of Hashing

Hashing vs Other DS

Download the Resources

Feedback Time

Sort Algorithms

What is Sorting?

Types of Sorting

Sorting Terminologies

Bubble Sort

Selection Sort

Insertion Sort

Bucket Sort

Merge Sort

Quick Sort

Heap Sort

Comparison of Sorting Algorithms

Download Resources

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Graph Algorithms

What is a Graph? Why Graph?

Graph Terminology

Types of Graph

Graph Representation

Create a graph using Python

Graph traversal - BFS

BFS Traversal in Python

Graph Traversal - DFS

DFS Traversal in Python

BFS Traversal vs DFS Traversal

Topological Sort

Topological Sort Algorithm

Topological Sort in Python

Single Source Shortest Path Problem (SSSPP)

BFS for SSSPP

BFS for SSSPP in Python

Why does BFS not work with weighted Graph?

Why does DFS not work for SSSP?

Dijkstra's Algorithm for SSSP

Dijkstra's Algorithm in Python

Dijkstra Algorithm with negative cycle

Bellman Ford Algorithm

Bellman Ford Algorithm with negative cycle

Why Bellman Ford runs V-1 times?

Bellman Ford in Python

BFS vs Dijkstra vs Bellman Ford

All pairs shortest path problem

Dry run for All pair shortest path

Floyd Warshall Algorithm

Why Floyd Warshall?

Floyd Warshall with negative cycle

Floyd Warshall in Python

BFS vs Dijkstra vs Bellman Ford vs Floyd Warshall

Minimum Spanning Tree

Disjoint Set

Disjoint Set in Python

Kruskal Algorithm

Kruskal Algorithm in Python

Prim's Algorithm

Prim's Algorithm in Python

Prim's vs Kruskal

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Reviews

H
Hrudaya29 January 2021

Awesome course for beginners to become advanced in coding. Just loved the teaching way of Elshad sir.

K
Karthik12 January 2021

Pros: 1. Good explanation with graphical representation so that beginners will understand clear 2. Many questions are solved with explanation. Cons: Nothing major but some small typos here and there.

V
Vighnesh30 December 2020

The best ever course I have come across from beginners to expert anyone can try it thank you and I am enjoying coding the examples.

I
Ismail27 December 2020

Great explaining and has a ton of exercises, and he is updating it till this day. He codes a lot in the course, and he is fast at it, so for people looking for a fast paced course, this is a great option!

D
Dinesh23 December 2020

The person who explaining was make it just like a theory: what i'm saying is more interact with show practical code with explain by implementing code each time.

M
M16 December 2020

One of the best DS & Algorithm in python course out there. Intstructor has explained every concept in detail. Well structured course with lots of excercises to build solid concepts. Will recommend to all.

S
Sophie8 December 2020

Well explained, good video, good content ! I just regret the lack of quizz after each section. And I regret most of the exercices are at the end of the course and not after each section.

J
Jagadeesan25 November 2020

Actually I am from a not CSE/IT background. But I am quite interested in learning python. This course helped me a lot to understand the course from the scrach. I recommend everyone take this course. Thankyou so much Elshad for your continous effort to make this course as simple to understand. Thanks once again!

N
Nirmal22 November 2020

it very helpful for me to understand data structure and algorithm in the easiest programing language I can choose, that is the python

Y
Yogesh16 November 2020

Thank you so much sir for teaching the Datastructure and algorithm in a very detailed way with practical examples.

A
Avirup12 November 2020

This guy is great. Just have literally started the course but the amount of stuff he is covering will definitely help me in mastering data structures and algorithms.

M
More5 November 2020

Yes This is very nice course and This Course is very simple and in this course help to improve My Knowledge

F
Freddy29 October 2020

I love how much he breaks everything down. For a beginner, algorithms can be pretty scary. This course is very thorough with the explanations and making it easy for anyone to understand.

P
Precious1 October 2020

The teacher is great! he explains everything in full details especially with real life examples. he uses the right algorithm in making his teaching methods effective so students don't get bored and sleepy.

J
Johana21 September 2020

Excellent course for those looking to understand data structures and algorithms from beginner to advanced level. The theoretical explanations are well done, along with concrete real life examples. All data structures and algorithms described and then implemented, which makes the concepts easier to understand and gives you a chance to apply them in a real practice. The top tech's interview questions and answers sections are excellent bonus which allow for preparing real interviews.


Coupons

DateDiscountStatus
9/20/2020100% OFFExpired
10/14/2020100% OFFExpired
4/11/202192% OFFExpired

2648040

Udemy ID

11/9/2019

Course created date

9/20/2020

Course Indexed date
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