This guide consists of different chapters on data structures and algorithms which covers the computer science theory + implementation of data structures in python language. This guide will also help students to face interviews at the top technology companies. This guide was purposely written for Students who want to have a better understanding of Data Structures, Students who want to have a better understanding of Data Structures, Python programmers curious about Data Structures, and IT Professional experimenting with the implementation of Data Structures in Python.
Some of the concepts and content in this guide include:Why need data structuresAnalysis of Algorithms i.e., Time and Space complexity, though the Asymptotic Notation i.e., Big O, Omega, and Theta are taken up at the end of this course so that you do not get confused and concentrate on understanding the concepts of data structures.We have a programming environment set up to make sure you have all the software you need to get the hands-on experience in implementing Data structures and algorithms.Each of the specific algorithms and data structures is divided into two sections. Theory lectures and implementation of those concepts in Python. We then move on to learn:ArraysStacks, Queues, DequesLinked ListTrees & Binary TreesBinary Search TreesHash tableGraphs & Graph Traversal AlgorithmsSearching and Sorting algorithmsRecursionBubble sort, Quick sort, Merge sorting, and so onAgain, each of these sections includes theory discussing covering data structures & their Abstract Data Types and/or algorithms. Plus, the implementation of these topics in Python.