# Python Data Structures & Algorithms: Ace Coding Interviews

Data Structures and Algorithms in Python | Leetcode + Video Solutions | Animated Explanation | Ace Coding Inteviews

## Description

Welcome to the Data Structures and Algorithms in Python Course!

Are you a Python programmer who wants to write efficient code and improve your programming and problem solving skills ?

Do you have an upcoming coding interview and you want to ace it with confidence ?

If the answer is yes, then this course is the right choice for you!

In this course you will learn everything about Data Structures and Algorithms and how to implement and use them in Python.

The concepts are explained with animations which makes it much more easier to understand and memorize.

You will also apply your knowledge throughout the course via coding exercises and Leetcode coding challenges with video solutions.

The course covers the following topics:

General

• Why Should You Learn Data Structures and Algorithms ?
• What are Data Structures ?
• What are Algorithms ?

Big O Notation

• Linear Complexity – O(n)
• Constant Complexity – O(1)
• Logarithmic Complexity – O(logn)
• Constants in Big O
• Dominant and Non-Dominant Factors in Big O
• Complexities Comparison

Data Structures

• Stacks
• Queues
• Sets
• Trees
• Tries
• Heaps
• Hash Tables
• Graphs

Algorithms

• Linear Search
• Binary Search
• Bubble Sort
• Insertion Sort
• Selection Sort
• Merge Sort
• Recursion
• Tree Traversal
• Graph Traversal

I’m confident that you will enjoy this course, but if you for some reason are not happy with the course it’s backed by Udemy’s 30 day money back guarantee, so nothing to lose 🙂
I’m excited to see you in the course, hit that enroll button and start your mastering Data Structures & Algorithms journey 🙂

## Who this course is for:

• Python Programmers Who Want to Master Data Structures and Algorithms
• Python Programmers Preparing for Coding Interviews
• Python Programmers Who Want to Write More Efficient Code and Improve Their Problem-Solving Skills