Algorithms and Data Structures in Python - Part II

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

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 algorithms and 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

Who is the target audience?

This course is suited for anyone who has some basic knowledge in Python