Data structures are basically that- they are structures which can preserve some statistics together. In different words they are used to store a collection of associated data. There are four built-in records structures in Python; list, tuple, dictionary and set.
Algorithm is a step by step procedure, which defines a set of instructions to be performed in a certain order to get the preferred output. Knowledge of algorithms and information buildings is beneficial for statistics scientists because our options are inevitably written in code. As such, it is vital to recognize the shape of our data and how to think in terms of algorithms.
Learning about information structures and algorithms makes you a stonking suitable programmer. Data buildings and algorithms are patterns for fixing problems. The greater of them you have in your utility belt, the larger variety of problems you will be capable to solve.
data structures and algorithms in python is a course that will help you in better understanding of basics of Data Structures and how algorithms are implemented in high level programming language. This course consists of lectures on data structures and algorithms which covers the computer science theory + implementation of data structures in python language. This course will also help students to face interviews at the top technology companies. This course is like having personal tutors to teach you about data structures and algorithms.
There’s tons of concepts and content in this course. To begin the course:
• We have a discussion of why we need data structures.

• Then we move on to discuss Analysis of Algorithms ie Time and Space complexity, though the Asymptotic Notation ie 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 programming environment setup to make sure you have all the software you need in order to get the hands on experience in implementing Data structures and algorithms.
Then we get to the essence of the course; algorithms and data structures. 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:
• Recursion
• Stacks, Queues, Deques
• Linked List
• Trees & Binary Trees
• Binary Search Trees
• Priority Queues and Heaps
• Graphs & Graph Traversal Algorithms
• Searching and Sorting algorithms
Again, each of these sections includes theory lectures covering data structures & their Abstract Data Types and/or algorithms. Plus the implementation of these topics in Python.
Basic knowledge:
• Prior knowledge of Programming any high level language
• Basic knowledge of Python Programming
What will you learn:
• Learn Data Structures, Abstract Data Types and their implementation in Python
• Implementation of Searching Algorithms in Python
• Implementation of Stacks, Queues, Linked List, Binary Trees, Heaps and Graphs in Python
• Implementation of Binary Tree Traversal Techniques in Python
• Graph traversals techniques i.e Depth First Search and Breadth-First Search in Python
• Implementation of Sorting Algorithms in Python
• Enhance Analytical Skill and efficiently use searching and sorting algorithms in real applications.

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