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Algorithms and Data Structures in Python - Part II

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Algorithms and Data Structures in Python – Part II

 

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What you’ll learn
  • Have a good grasp of algorithmic thinking
  • Be able to develop your own algorithms
  • Be able to detect and correct inefficient code snippets

 

 

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Requirements
  • Python basics
  • Some theoretical background ( big O notation )
 
Description

This course is for those who are interested in computer science and want to implement the algorithmsand given data structures in Python. In every chapter you will learn about the theory of a given data structure or algorithm and then you will implement them from scratch.

Chapter 1: Binary Indexed Trees (Fenwick Trees)

  • theory behind the binary indexed tree or Fenwick tree data structure
  • how to use this data structure in computer vision and artificial intelligence
  • implementation in Python

Chapter 2: LRU Caches

  • what are caches and why are they so important
  • theory behind LRU caches
  • implementation in Python

Chapter 3: Prefix Trees (Tries)

  • what are tries or prefix trees
  • real world applications of tries
  • implementation in Python

Chapter 4: Substring Search Algorithms

  • what are substring search algorithms and why are they important in real world softwares
  • brute-force substring search algorithm
  • Boyer-Moore algortihm
  • Knuth-Morris-Pratt substring search algorithm
  • implementation in Python

Thanks for joining my course, let’s get started!

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

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Algorithms and Data Structures in Python – Part II


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