Data Structures and Algorithms Python The Complete Bootcamp

DSA Basics To Advanced: Learn, Analyze, Implement Data Structures and Algorithms using Python With Interview Questions
Data Structures and Algorithms Python The Complete Bootcamp
File Size :
3.84 GB
Total length :
20h 2m

Category

Instructor

Shubham Sarda

Language

Last update

Last updated 8/2022

Ratings

4.3/5

Data Structures and Algorithms Python The Complete Bootcamp

What you’ll learn

Understand the fundamentals of the Data Structures and Algorithms
Understand each and every concept from scratch with proper knowledge of their complexities and implementations in Python
Understand concept behind Arrays, Linked Lists, Stacks & Queues, Hash tables, Trees and Graphs
Understand popular algorithms, and how to use them (Searching, Sorting and Traversal)
Improve your problem solving skills and become a confident developer for your next coding interview
Code an implementation of each data structure, so you understand how they work behind the scene

Data Structures and Algorithms Python The Complete Bootcamp

Requirements

Basic Knowledge of Python Programming

Description

Welcome to Data Structures and Algorithms – Coding Interview Bootcamp, One single course to start your DSA journey as a beginner step-by-step. This course touches on each and every important topic through concept, visualization, and implementation. The entire course is designed for beginners with one goal in mind, to understand each and every concept from scratch with proper knowledge of their complexities and implementations in Python.Throughout the course, we will explore the most important Data Structures and Algorithms topics step-by-step:1. Essential Concepts- Big O Notation- Memory- Logarithms- Recursion2. Data structures:- Arrays- Linked Lists (Singly Linked List, Doubly Linked List, Circular Linked List)- Stacks- Queues- Hash Tables- Trees (Binary Tree, Binary Search Tree, AVL Trees, Red-Black Trees)- Heaps (Binary Heaps)- Tries- Graphs3. Algorithms:- Elementary Sorting Algorithms (Bubble Sort, Insertion Sort, Selection Sort)- Advance Searching Algorithms (Quick Sort, Merge Sort)- Tree TraversalBreadth-First Search: Level Order Traversal, Depth First Search: PreOrder, InOrder, PostOrder- Graph Traversal(Breadth-First Search, Depth First Search)4. Interview Questions- Two Sum- MinMax Stack- Design Linked List- Reverse Linked List- Construct Binary Tree- Invert Binary Tree- Construct Binary Search Tree- Detect Capital- Reverse String- Longest Palindromic Substring——————Why this course?Complete course is focused on concept learning approach, you learn every concept through a logical and visual learning approach. Learn all important concepts in the simplest possible way with tons of examples and quizzes. You just need basic Python knowledge, we will cover everything step-by-step from scratch.——————After completing this course you will be ready to work as an Intern, Fresher, or Freelancer and you will also be able to implement everything yourself! Most importantly you will be ready to divide deep with future practice and hard level question of Data Structures. Enroll now, I will make sure you learn best about Data Structures and Algorithms.

Overview

Section 1: Course Introduction

Lecture 1 Course Introduction

Lecture 2 Welcome – Lets Get Started!

Lecture 3 Curriculum Walkthrough

Lecture 4 Code Source – Github

Section 2: Big O Notation

Lecture 5 Section Introduction

Lecture 6 Complexity Analysis

Lecture 7 Why we need Big O Notation?

Lecture 8 Big O(n) Complexity

Lecture 9 Big O(1) Complexity

Lecture 10 Counting Operations

Lecture 11 Simplifying Big O – Part 1

Lecture 12 Big O(n^2) Complexity

Lecture 13 Simplifying Big O – Part 2

Lecture 14 Big O(n!) Complexity

Lecture 15 Space Complexity

Lecture 16 Space Complexity – II

Lecture 17 Section Summary

Section 3: Essential Concepts – I

Lecture 18 Memory

Lecture 19 Logarithm

Section 4: Data Structure – Introduction

Lecture 20 Introduction to Data Structures

Section 5: Data Structures – Array

Lecture 21 Array Introduction

Lecture 22 Array – Common Operations I

Lecture 23 Array – Common Operations II

Lecture 24 Static vs Dynamic Array – Common Operations III

Section 6: Data Structures – Linked List

Lecture 25 Linked List

Lecture 26 Linked List Complexities

Lecture 27 Doubly Linked List

Lecture 28 Circular Linked List and Implementing A Linked List

Section 7: Data Structures – Stack and Queue

Lecture 29 Stack and Queue

Section 8: Data Structures – Hash Tables

Lecture 30 Hash Tables

Section 9: Data Structures – Trees

Lecture 31 Tree – Part 1

Lecture 32 Tree – Part 2

Lecture 33 Binary Tree

Lecture 34 Types Of Binary Tree

Lecture 35 Binary Search Tree

Lecture 36 AVL – Red Back Tree

Section 10: Data Structures – Heaps

Lecture 37 Heaps

Lecture 38 Heap Sort and Priority Queue

Section 11: Data Structures – Trie

Lecture 39 Trie – I

Lecture 40 Trie – II

Lecture 41 Why are Tries Important?

Section 12: Data Structures – Graph

Lecture 42 Graph

Section 13: Essential Concepts – II

Lecture 43 What is Recursion?

Lecture 44 Recursion: Control of a Function

Lecture 45 Recursion: Tracing Tree

Lecture 46 Recursion: Understanding Call Stack

Lecture 47 Recursion: Tree Recursion

Lecture 48 Recursion Example – Factorial of a Number

Section 14: Algorithm: Searching

Lecture 49 Linear Search

Lecture 50 Binary Search

Lecture 51 Binary Search Complexity

Lecture 52 Binary Search Implementation

Lecture 53 Binary Search Implementation – Recursion

Section 15: Algorithm: Sorting Elementary

Lecture 54 Sorting Algorithm Introduction

Lecture 55 Bubble Sort

Lecture 56 Bubble Sort Visualization

Lecture 57 Bubble Sort Implementation

Lecture 58 Bubble Sort Complexity

Lecture 59 Selection Sort

Lecture 60 Selection Sort Visualization

Lecture 61 Selection Sort – Implementation

Lecture 62 Selection Sort – Complexity

Lecture 63 Insertion Sort

Lecture 64 Insertion Sort Implementation

Lecture 65 Insertion Sort Complexity

Lecture 66 Performance Analysis

Section 16: Algorithm: Sorting Advanced

Lecture 67 Divide and Conquer Algorithms

Lecture 68 Quick Sort

Lecture 69 Quick Sort Complexity

Lecture 70 Quick Sort Implementation

Lecture 71 Merge Sort

Lecture 72 Merge Sort Complexity

Lecture 73 Merge Sort Implementation

Section 17: Algorithms: Tree Traversal

Lecture 74 Tree Traversal

Lecture 75 Depth First Search – Preorder Inorder Postorder

Lecture 76 Binary Tree Implementation

Lecture 77 Depth First Search – Implementation

Lecture 78 Depth First Search – Complexity

Lecture 79 Breadth First Search – Level Order

Lecture 80 Breadth First Search – Implementation

Lecture 81 Breadth First Search – Complexity

Section 18: Algorithms: Graph Traversal

Lecture 82 Graph Traversal

Lecture 83 Graph Implementation

Lecture 84 Breadth First Search – Implementation

Lecture 85 Depth First Search – Implementation

Lecture 86 Graph Traversal Complexity

Section 19: Implementations and Interview Questions

Lecture 87 Data Structure Implementation

Lecture 88 Problem Solving Approach

Section 20: Question 1: Two Sum

Lecture 89 Two Sum

Lecture 90 Code Solution: Two Sum

Section 21: Question 2: Min Stack

Lecture 91 Min Stack

Lecture 92 Min Stack Implementation

Lecture 93 Solution: Min Stack

Section 22: Question 3: Max Stack

Lecture 94 Max Stack

Lecture 95 Solution: Max Stack

Section 23: Question 4: Design a Linked List

Lecture 96 Design a Linked List – I

Lecture 97 Design a Linked List – II

Lecture 98 Design a Linked List – III

Lecture 99 Design a Linked List – IV

Lecture 100 Solution: Design Linked List

Section 24: Question 5: Reverse Linked List

Lecture 101 Reverse Linked List – I

Lecture 102 Reverse Linked List – II

Lecture 103 Solution: Reverse Linked List

Section 25: Question 6: Construct Binary Tree

Lecture 104 Traversal (Preorder-Inorder-Postorder)

Lecture 105 Construct BT: From Preorder and Inorder Traversal – I

Lecture 106 Construct BT: From Preorder and Inorder Traversal – II

Lecture 107 Solution: Construct Binary Tree PI

Section 26: Question 7: Invert Binary Tree

Lecture 108 Invert Binary Tree – I

Lecture 109 Invert Binary Tree – II

Lecture 110 Solution: Invert Binary Tree

Section 27: Question 8: Construct Binary Search Tree

Lecture 111 Construct BST: From Preorder Traversal

Lecture 112 Construct BST: From Preorder Traversal – II

Lecture 113 Solution: Construct Binary Search Tree

Section 28: Question 9: Detect Capital

Lecture 114 Detect Capital

Lecture 115 Solution: Detect Capital

Section 29: Question 10: Reverse String

Lecture 116 Reverse String

Lecture 117 Solution: Reverse String

Section 30: Question 11: Longest Palindromic Substring

Lecture 118 Longest Palindromic Substring – I

Lecture 119 Longest Palindromic Substring – II

Lecture 120 Solution: Longest Palindromic Substring

Section 31: Thank You For Being Here!

Lecture 121 Thank You For Being Here!

Lecture 122 Bonus – What’s Next?

Students (Computer Science / Non-Computer Science) who wants to learn Data Structures and Algorithms concepts from the scratch,Anyone who wants to strengthen their problem-solving skills,Students who are preparing for the interviews,Anybody who wants to switch to a product based company,Anyone who wants to refresh their Data Structures and Algorithms concepts

Course Information:

Udemy | English | 20h 2m | 3.84 GB
Created by: Shubham Sarda

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