Algorithms and Data Structures in Python

This course is about data structures and algorithms. We are going to implement the problems in Python. I highly recommend typing out these data structures and algorithms several times on your own in order to get a good grasp of it.

Section 1:

setting up the environment

data structures and abstract data types

Section 2:

what is an array data structure

arrays related interview questions

linked list data structure and its implementation

Section 3:

stacks and queues

related interview questions

Section 4:

what are binary search trees

practical applications of binary search trees

Section 5:

problems with binary trees

balanced trees: AVL trees and red–black trees

Section 6:

what are heaps

heapsort algorithm

Section 7:

associative arrays and dictionaries

how to achieve O(1) constant running time with hashing

ternary search trees as associative arrays

Section 8:

basic graph algorithms

breadth–first and depth–first search

Section 9:

shortest path algorithms

Dijkstra’s algroithm

Bellman–Ford algorithm

Section 10:

what are spanning trees

Kruskal algorithm

Section 11:

sorting algorithms

bubble sort, selection sort and insertion sort

quicksort and merge sort

non–comparison based sorting algorithms

counting sort and radix sort

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.