DATA STRUCTURES AND ALGORITHM IN PYTHON

Data structures and algorithms or DSA is the concept in programming that every programmer has to be perfect in, to create a code by efficiently making the best use of the available resources. Irrespective of the programming language, DSA is more of a general concept. This tutorial covers the basic foundation of DSA using the Python programming language.

Python is the language of choice for many advanced data tasks for a very good reason.

Python is one of the easiest advanced programming languages to learn. Intuitive structures

and semantics mean that for people who are not computer scientists, but maybe biologists,

statisticians, or the directors of a start-up, Python is a straightforward way to perform a

wide variety of data tasks. It is not just a scripting language, but a full-featured object-

oriented programming language.

In Python, there are many useful data structures and algorithms built in to the language.

Also, because Python is an object-based language, it is relatively easy to create custom data objectsPython has several built-in data structures, including lists, dictionaries, and sets, that we

use to build customized objects. In addition, there are a number of internal libraries, such as

collections and the math object, which allow us to create more advanced structures as well

as perform calculations on those structures. Finally, there are the external libraries such as

those found in the SciPy packages. These allow us to perform a range of advanced data

tasks such as logistic and linear regression, visualization, and mathematical calculations

such as operations on matrixes and vectors. External libraries can be very useful for an out-

of-the-box solution. However, we must also be aware that there is often a performance

penalty compared to building customized objects from the ground up. By learning how to

code these objects ourselves, we can target them to specific tasks, making them more

efficient.

"Data Structures and Algorithms In Python" tutorial will help you develop a strong background in Data Structures and Algorithms (DSA). The course is broken down into easy to assimilate short lectures, and after each topic there is a quiz that can help you to test your newly acquired knowledge. The examples are explained with animations to simplify the learning of this complex topic. Complete working programs are shown for each concept that is explained.

This Data Structures and Algorithms in Python course provides a comprehensive explanation of data structures like linked lists, stacks and queues, binary search trees, heap, searching and hashing. Various sorting algorithms with implementation and analysis are included in this tutorial.

This Data Structures in Python course covers following topics with Python implementation :

Algorithm Analysis, Big O notation, Time complexity, Singly linked list, Reversing a linked list, Doubly linked list, Circular linked list, Linked list concatenation, Sorted linked list.

Stack, Queue, Circular Queue, Dequeue, Priority queue, Polish Notations, Infix to Postfix, Evaluation of Postfix, Binary Tree, Binary Search Tree, Tree Traversal (inorder, preorder, postorder, level order), Heap, Searching, Hashing

Sorting : Selection, Bubble, Insertion, Shell, Merging, Recursive Merge, Iterative Merge, Quick, Heap, Binary tree, Radix, Address calculation sort.