Algorithms and Data Structures in Python

Algorithms and Data Structures in Python

Created by Holczer Balazs
Last updated 11/2017
English
English [Auto-generated]
Created by Holczer Balazs
Created by Holczer Balazs
Last updated 11/2017
Last updated 11/2017
Last updated 11/2017
English
English [Auto-generated]
English
English [Auto-generated]
English
English [Auto-generated]
English [Auto-generated]
What Will I Learn?
  • Have a good grasp of algorithmic thinking
  • Be able to develop your own algorithms
  • Be able to detect and correct inefficient code snippets
What Will I Learn?
Requirements
  • Python basics
  • Some theoretical background ( big O notation )
Requirements
  • Python basics
  • Some theoretical background ( big O notation )
Description

This course is about data structures and algorithms. We are going to implement the problems in Python, but I try to do it as generic as possible: so the core of the algorithms can be used in C++ or Java. I highly recommend typing out these data structures and algorithms several times on your own in order to get a good grasp of it.

In the first part of the course we are going to learn about basic data structures such as linked lists, stacks, queues, binary search trees, heaps and some advanced ones such as AVL trees and red-black trees.. The second part will be about graph algorithms such as spanning trees, shortest path algorithms and graph traversing. We will try to optimize each data structure as much as possible.

In each chapter I am going to talk about the theoretical background of each algorithm or data structure, then we are going to write the code step by step in Python.

Most of the advanced algorithms relies heavily on these topics so it is definitely worth understanding the basics. These principles can be used in several fields: in investment banking, artificial intelligence or electronic trading algorithms on the stock market. Research institutes use Python as a programming language in the main: there are a lot of library available for the public from machine learning to complex networks.

Who is the target audience?
  • This course is suited for anyone who has some basic knowledge in python

Size: 1.65G

Description
Who is the target audience?
  • This course is suited for anyone who has some basic knowledge in python

Size: 1.65G

Who is the target audience?

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