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[100% Off] The Complete Data Structures and Algorithms Course in Python Free Course Coupon

Programming Languages — December 14, 2023 · Comments off
[100% Off] The Complete Data Structures and Algorithms Course in Python Free Course Coupon

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




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