Hands On Data Structure & Algorithm with Python: 2 in 1

This video gives an overview of the entire course.  

Introduce divide and algorithm, explain various steps involved in a  divide and conquer algorithm and walk through some of the common divide  and conquer algorithms.           

• Explain Divide and Conquer

• Steps of a Divide and Conquer

• Some examples of Divide and Conquer algorithms

Introduce Greedy Algorithms., look at some examples of Greedy  Algorithms and comparison between Greedy versus Divide and Conquer.           

• Introduce Greedy Algorithms

• Examples of Greedy Algorithms

• Greedy versus Divide and Conquer

Introduce Recursion, compare Iteration vs. Recursion and look at Binary Search using Recursion.

• Introduce Recursion

• Iteration versus Recursion

• Binary Search using Recursion

Introduce Dynamic Programming, talk about properties of DP and Fibonacci using DP.

• Introduce Dynamic Programming

• Properties of DP

• Fibonacci using DP

Introduce Asymptotic Analysis.  And demo Asymptotic Notation and talk about why use Asymptotic Notation.

• Introduce Asymptotic Analysis

• Asymptotic Notation

• Why

Introduce Python list, demo how to use list and List methods and operations.

• Introduce Python list

• How to use list

• List methods/operation

Introduce tuples, compare Tuple vs List and demo how to use tuples.

• What are tuples

• Tuple versus List

• How to use tuples

Introduce Dictionaries, walk through how to create Dictionaries and how to use Dictionaries in code.

• Introduce Dictionaries

• How to create Dictionaries

• How to use Dictionaries

We will understand what a Set data-type is. What is the built-in  type available for Set. Then we shall see a demo of implementing a Set  using Python dictionaries.

• Understand what a Set data-type is

• What is the built-in type available for Set

• Demo of Set using Python dictionaries

Learn whether there are pointers in python, we learn what is  reference and what is the difference between pointer and reference and  see some code examples.

• Learn whether there are pointers in python, we learn what is reference

• What is the difference between pointer and reference

• See some code examples

Get introduced Stack, define an abstract stack data structure  before implementing it and see some examples of stack in programming  world.

• Get introduced to a data structure called as the Stack

• Define and implement an abstract stack data structure

• See some examples of stack in programming world

Look into the structure of Stack implementation using Python and  implement various operations of the stack and then see how to use the  stack.

• Code structure for stack

• Implement stack

• How to u

In this video, we will introduce you to another linear data  structure called as Queue, we shall discuss the Queue as an abstract  data type and then look at a simple implementation of the Queue Data  Structure.           

• Introduce linear data structure called as Queue

• Discuss the Queue as an abstract data type

• Look at a simple implementation of the Queue Data Structure

In this video, we will introduce you to a hybrid linear data  structure called as Deque. We shall discuss Deque as an abstract data  type and then look at a simple implementation of Deque Data Structure.           

• Introduce hybrid linear data structure called as Deque

• Discuss Deque as an abstract data type

• Look at a simple implementation of Deque Data Structure

In this video, we will introduce you to what hash-table is. We  will also present the Hash table as an abstract data type before  proceeding to an implementation of a hash table.           

• Introduce what hash-table is

• Present the Hash table as an abstract data type

• Implement a hash table

Present the first non-linear data structure called as Tree. We  shall understand what a tree is and its components are and then define  the binary tree ADT.           

• Present the first non-linear data structure called as Tree

• We shall understand what a tree is and its components are

• Define the binary tree ADT

In this video, through a demo, we shall fill up the gaps we had in  the last video in implementing an example Binary Tree using Python.           

• Implement insert_left() and insey_right()  methods

• Implement traversal methods

• Run the program

We shall discuss about the heapq python module that provides an  out of the box priority queue. We shall also discuss the binary heap  data structure that is used to implement a priority queue.           

• Introduce heapq module

• Introduce Binary Heap

• Binary Heap implementation

We will present the Min Heap as an abstract data structure. We  shall implement the Binary Min Heap that can help us realize a priority  queue.           

• We will present the Min Heap as an abstract data structure

• We shall implement the Binary Min Heap that can help us realize a priority queue

• Run the program

We will introduce you to binary search trees and learn why  balancing a binary search tree is important. Then we will provide an  overview of a self-balancing binary search tree called as red-black  tree.           

• Introduce binary search trees

• Importance of binary search trees

• Self-balancing binary search tree called as red-black tree

We will introduce you to a search optimized data structure called  as TRIE. We will also present the TRIE as an abstract data type before  proceeding to an implementation of a TRIE.           

• We will introduce you to a search optimized data structure called as TRIE

• We will present the TRIE as an abstract data type

• Implement a TRIE

In this video, we are going to learn what are graphs and where  they are used before we get a hands-on experience in creating and  managing graphs using Python.

• learn what are graphs

• learn where graphs are used

• Get a hands-on experience in creating and managing graphs using Python

In this video, we will look into what undirected graphs are. And  also look into another way of representing graphs programmatically  called as adjacency list through a demo.

• Look into what undirected graphs are

• look into another way of representing graphs programmatically called as adjacency list

• Walk through a demo

In this video, we will learn what a directed graph is. What are  its applications. We shall also define directed graph as an abstract  data type and start with an initial implementation of the same.

• Learn what a directed graph I and its applications

• Define directed graph as an abstract data type

• Start with an initial implementation of the same

In this video, we will continue to build on the Graph class by  completing the remaining operations. Along the way, we also improve on  the Vertex class and add neighbor function to it.

• Continue to build on the Graph class by completing the remaining operations

• Improve on the Vertex class

• Add neighbor function

In this video, we will complete the implementation of get_edges  method in the Graph class and the required function in Vertex class to  get Connections of a vertex.

• Complete the implementation of get_edges method in the Graph class

• Add the required functions in Vertex class to get Connections of a vertex

• Walk through the demo

In this video, we will complete the Graph implementation, by  completing the one missing piece in our implementation to get weight of a  particular edge.

• Complete the Graph implementation

• Add the one missing piece in our implementation to get weight of a particular edge

• Walk through the code demo

In this video, we will learn we provide an overview of various  Graph Operations that we are going to talk over the rest of this course.

• Provide an overview of various Graph Operations

• Discuss traversal operations

• Discuss few others graph algorithms

We are going to learn the Breadth-First Search algorithm and its applications.

• Introduce BFS with an illustration

• Look at BFS applications

• Demo the code

We will learn another graph traversal algorithm called as Depth  First Search or DFS. We shall also look at its applications before we  see an implementation of DFS.

• Introduce DFS

• DFS Applications

• Demo the implementation

We will learn what a shortest path in a graph. And we shall also  discuss a specific shortest path algorithm called as dijkstra’s shortest  path algorithm.

• Learn about shortest path in a graph

• Discuss a specific shortest path algorithm called as dijkstra’s shortest path algorithm

• Walk through the code

We will look into the implementation of dijkstra’s algorithm using Python.

• Walk through the code

We will learn about what spanning trees. What a minimum spanning  tree is. We shall also learn about a data structure called as disjoint sets or union-find that is used in kruskal’s algorithm to find minimum  spanning tree.

• Learn about spanning trees

• Find out what a minimum spanning tree is

• Learn about disjoint sets or union-find that is used in kruskal’s algorithm to find minimum spanning tree

We will implement Kruskal’s algorithm for minimum spanning tree using the union-find data structure.

• Learn about Kruskal’s

• Animated illustration about Kruskal’s

• Walk through Kruskal’s algorithm code

Learn about the coding maximum flow tree algorithm in python and see the example.

• Learn about Coding Maximum Flow tree

• Learn its advantages and applications

• Walkthrough the code

Learn what topological sorting is for a Directed Acyclic Graph or DAG and what are its advantages and how we can use a modified DFS algorithm to find topological sorting of a Directed Acyclic Graph.

• Learn what topological sorting is for a Directed Acyclic Graph or DAG

• Discuss about its advantages

• Demo how we can use a modified DFS algorithm to find topological sorting of a Directed Acyclic Graph