Data Structures and Algorithms in Python - Full Course (Part 2/7)

Welcome to the Complete Data Structures and Algorithms in Python Bootcamp. This is the most comprehensive course 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.

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.

The topics that are covered in this part course.

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

#DataStructures #Algorithms #Python #Morioh

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